chore: remove updated screenshot asset

Co-authored-by: Dax <mail@thdxr.com>

.changeset/calm-services-start.md

@@ -0,0 +1,7 @@
+---
+"@opencode-ai/client": patch
+"@opencode-ai/protocol": patch
+"@opencode-ai/cli": patch
+---
+
+Expose background-service lifecycle status, preserve one process-held owner through startup and failure, reconnect TUIs without activating replacement, and stop exact service instances gracefully.

.changeset/calm-sessions-header.md

@@ -0,0 +1,5 @@
+---
+"@opencode-ai/cli": patch
+---
+
+Expose a TUI plugin slot at the top of the session view.

.changeset/clean-sessions-generate.md

@@ -0,0 +1,7 @@
+---
+"@opencode-ai/client": patch
+"@opencode-ai/plugin": patch
+"@opencode-ai/protocol": patch
+---
+
+Expose transient, read-only session generation through the HTTP API, generated clients, and V2 plugin session context.

.changeset/fresh-composers-slot.md

@@ -0,0 +1,5 @@
+---
+"@opencode-ai/cli": patch
+---
+
+Expose a TUI plugin slot above the session composer.

.gitattributes

@@ -1,2 +1,3 @@
 packages/core/migration/**/snapshot.json linguist-generated
 packages/core/src/database/migration.gen.ts linguist-generated
+packages/core/src/**/*.txt text eol=lf

.github/CODEOWNERS

@@ -1,5 +1,3 @@
 # web + desktop packages
-packages/app/      @adamdotdevin
-packages/tauri/    @adamdotdevin
-packages/desktop/src-tauri/  @brendonovich
-packages/desktop/  @adamdotdevin
+packages/app/      @Hona @Brendonovich
+packages/desktop/  @Hona @Brendonovich

.github/ISSUE_TEMPLATE/config.yml

@@ -2,4 +2,4 @@ blank_issues_enabled: false
 contact_links:
   - name: 💬 Discord Community
     url: https://discord.gg/opencode
-    about: For quick questions or real-time discussion. Note that issues are searchable and help others with the same question.
+    about: For support, troubleshooting, how-to questions, and real-time discussion.

.github/ISSUE_TEMPLATE/question.yml

@@ -1,10 +0,0 @@
-name: Question
-description: Ask a question
-body:
-  - type: textarea
-    id: question
-    attributes:
-      label: Question
-      description: What's your question?
-    validations:
-      required: true

.github/TEAM_MEMBERS

@@ -1,4 +1,5 @@
 adamdotdevin
+arvsrn
 Brendonovich
 fwang
 Hona
@@ -7,11 +8,14 @@ jayair
 jlongster
 kitlangton
 kommander
+ludvigrask
 MrMushrooooom
 nexxeln
 R44VC0RP
 rekram1-node
 thdxr
 simonklee
+Slickstef11
+usrnk1
 vimtor
-starptech
+StarpTech

.github/actions/setup-bun/action.yml

@@ -8,6 +8,13 @@ inputs:
 runs:
   using: "composite"
   steps:
+    # node-gyp@latest (invoked via bunx for native install scripts) requires Node >=22;
+    # some runner images ship an older system Node on PATH
+    - name: Setup Node
+      uses: actions/setup-node@49933ea5288caeca8642d1e84afbd3f7d6820020 # v4.4.0
+      with:
+        node-version: "24"
+
     - name: Get baseline download URL
       id: bun-url
       shell: bash

.github/workflows/compliance-close.yml

@@ -34,10 +34,48 @@ jobs:
 
             const now = Date.now();
             const twoHours = 2 * 60 * 60 * 1000;
+            const orgMemberAssociations = new Set(['OWNER', 'MEMBER']);
+            const agentLogin = 'opencode-agent[bot]';
+            const { data: file } = await github.rest.repos.getContent({
+              owner: context.repo.owner,
+              repo: context.repo.repo,
+              path: '.github/TEAM_MEMBERS',
+              ref: 'dev',
+            });
+            const teamMembers = new Set(
+              Buffer.from(file.content, 'base64')
+                .toString()
+                .split('\n')
+                .map((line) => line.trim().toLowerCase())
+                .filter(Boolean)
+            );
+
+            function isExempt(item) {
+              const login = item.user?.login?.toLowerCase();
+              return (
+                login === agentLogin ||
+                orgMemberAssociations.has(item.author_association) ||
+                (login && teamMembers.has(login))
+              );
+            }
 
             for (const item of items) {
               const isPR = !!item.pull_request;
               const kind = isPR ? 'PR' : 'issue';
+              const login = item.user?.login;
+
+              if (isExempt(item)) {
+                core.info(`Skipping ${kind} #${item.number}; author ${login || 'unknown'} is exempt`);
+                try {
+                  await github.rest.issues.removeLabel({
+                    owner: context.repo.owner,
+                    repo: context.repo.repo,
+                    issue_number: item.number,
+                    name: 'needs:compliance',
+                  });
+                } catch (e) {}
+                continue;
+              }
 
               const { data: comments } = await github.rest.issues.listComments({
                 owner: context.repo.owner,

.github/workflows/duplicate-issues.yml

@@ -17,12 +17,31 @@ jobs:
         with:
           fetch-depth: 1
 
+      - name: Check exempt issue author
+        id: author
+        run: |
+          LOGIN="${{ github.event.issue.user.login }}"
+          ASSOCIATION="${{ github.event.issue.author_association }}"
+
+          if [ "$LOGIN" = "opencode-agent[bot]" ] ||
+             [ "$ASSOCIATION" = "OWNER" ] ||
+             [ "$ASSOCIATION" = "MEMBER" ] ||
+             grep -qxiF "$LOGIN" .github/TEAM_MEMBERS; then
+            echo "skip=true" >> "$GITHUB_OUTPUT"
+            echo "Skipping issue automation for exempt author: $LOGIN ($ASSOCIATION)"
+          else
+            echo "skip=false" >> "$GITHUB_OUTPUT"
+          fi
+
       - uses: ./.github/actions/setup-bun
+        if: steps.author.outputs.skip != 'true'
 
       - name: Install opencode
+        if: steps.author.outputs.skip != 'true'
         run: curl -fsSL https://opencode.ai/install | bash
 
       - name: Check duplicates and compliance
+        if: steps.author.outputs.skip != 'true'
         env:
           OPENCODE_API_KEY: ${{ secrets.OPENCODE_API_KEY }}
           GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
@@ -38,6 +57,7 @@ jobs:
           opencode run -m opencode/claude-sonnet-4-6 "A new issue has been created:
 
           Issue number: ${{ github.event.issue.number }}
+          Issue author association: ${{ github.event.issue.author_association }}
 
           Lookup this issue with gh issue view ${{ github.event.issue.number }}.
 
@@ -49,6 +69,8 @@ jobs:
 
           Check whether the issue follows our contributing guidelines and issue templates.
 
+          If the issue author association is OWNER or MEMBER, skip this compliance check. Do not add the needs:compliance label for organization-owned issues.
+
           This project has three issue templates that every issue MUST use one of:
 
           1. Bug Report - requires a Description field with real content
@@ -83,7 +105,7 @@ jobs:
 
           Based on your findings, post a SINGLE comment on issue #${{ github.event.issue.number }}. Build the comment as follows:
 
-          If the issue is NOT compliant, start the comment with:
+          If the issue is NOT compliant and the author association is not OWNER or MEMBER, start the comment with:
           <!-- issue-compliance -->
           Then explain what needs to be fixed and that they have 2 hours to edit the issue before it is automatically closed. Also add the label needs:compliance to the issue using: gh issue edit ${{ github.event.issue.number }} --add-label needs:compliance
 
@@ -129,12 +151,31 @@ jobs:
         with:
           fetch-depth: 1
 
+      - name: Check exempt issue author
+        id: author
+        run: |
+          LOGIN="${{ github.event.issue.user.login }}"
+          ASSOCIATION="${{ github.event.issue.author_association }}"
+
+          if [ "$LOGIN" = "opencode-agent[bot]" ] ||
+             [ "$ASSOCIATION" = "OWNER" ] ||
+             [ "$ASSOCIATION" = "MEMBER" ] ||
+             grep -qxiF "$LOGIN" .github/TEAM_MEMBERS; then
+            echo "skip=true" >> "$GITHUB_OUTPUT"
+            echo "Skipping issue automation for exempt author: $LOGIN ($ASSOCIATION)"
+          else
+            echo "skip=false" >> "$GITHUB_OUTPUT"
+          fi
+
       - uses: ./.github/actions/setup-bun
+        if: steps.author.outputs.skip != 'true'
 
       - name: Install opencode
+        if: steps.author.outputs.skip != 'true'
         run: curl -fsSL https://opencode.ai/install | bash
 
       - name: Recheck compliance
+        if: steps.author.outputs.skip != 'true'
         env:
           OPENCODE_API_KEY: ${{ secrets.OPENCODE_API_KEY }}
           GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
@@ -148,9 +189,12 @@ jobs:
             }
         run: |
           opencode run -m opencode/claude-sonnet-4-6 "Issue #${{ github.event.issue.number }} was previously flagged as non-compliant and has been edited.
+          Issue author association: ${{ github.event.issue.author_association }}
 
           Lookup this issue with gh issue view ${{ github.event.issue.number }}.
 
+          If the issue author association is OWNER or MEMBER, remove the needs:compliance label if present, delete the previous compliance comment if present, and do not post a new comment.
+
           Re-check whether the issue now follows our contributing guidelines and issue templates.
 
           This project has three issue templates that every issue MUST use one of:

.github/workflows/nix-hashes.yml

@@ -56,14 +56,24 @@ jobs:
           BUILD_LOG=$(mktemp)
           trap 'rm -f "$BUILD_LOG"' EXIT
 
-          # Build with fakeHash to trigger hash mismatch and reveal correct hash
-          nix build ".#packages.${SYSTEM}.node_modules_updater" --no-link 2>&1 | tee "$BUILD_LOG" || true
+          HASH=""
+          MAX_ATTEMPTS=3
+          for ((ATTEMPT = 1; ATTEMPT <= MAX_ATTEMPTS; ATTEMPT++)); do
+            # Build with fakeHash to trigger hash mismatch and reveal correct hash
+            nix build ".#packages.${SYSTEM}.node_modules_updater" --no-link 2>&1 | tee "$BUILD_LOG" || true
 
-          # Extract hash from build log with portability
-          HASH="$(nix run --inputs-from . nixpkgs#gnugrep -- -oP 'got:\s*\Ksha256-[A-Za-z0-9+/=]+' "$BUILD_LOG" | tail -n1 || true)"
+            HASH="$(nix run --inputs-from . nixpkgs#gnugrep -- -oP 'got:\s*\Ksha256-[A-Za-z0-9+/=]+' "$BUILD_LOG" | tail -n1 || true)"
+
+            [ -n "$HASH" ] && break
+
+            if [ "$ATTEMPT" -lt "$MAX_ATTEMPTS" ]; then
+              echo "::warning::Attempt ${ATTEMPT}/${MAX_ATTEMPTS} produced no hash for ${SYSTEM}; retrying in $((ATTEMPT * 10))s"
+              sleep $((ATTEMPT * 10))
+            fi
+          done
 
           if [ -z "$HASH" ]; then
-            echo "::error::Failed to compute hash for ${SYSTEM}"
+            echo "::error::Failed to compute hash for ${SYSTEM} after ${MAX_ATTEMPTS} attempts"
             cat "$BUILD_LOG"
             exit 1
           fi

.github/workflows/publish.yml

@@ -6,6 +6,7 @@ on:
     branches:
       - ci
       - dev
+      - v2
       - beta
       - fix/npm-native-binary-install
       - snapshot-*
@@ -31,6 +32,9 @@ permissions:
   contents: write
   packages: write
 
+env:
+  OPENCODE_CHANNEL: ${{ (github.ref_name == 'v2' && 'next') || '' }}
+
 jobs:
   version:
     runs-on: blacksmith-4vcpu-ubuntu-2404
@@ -90,6 +94,7 @@ jobs:
         id: build
         run: |
           ./packages/opencode/script/build.ts ${{ (github.ref_name == 'beta' && '--sourcemaps') || '' }}
+          ./packages/cli/script/build.ts ${{ (github.ref_name == 'beta' && '--sourcemaps') || '' }}
         env:
           OPENCODE_VERSION: ${{ needs.version.outputs.version }}
           OPENCODE_RELEASE: ${{ needs.version.outputs.release }}
@@ -107,15 +112,70 @@ jobs:
         with:
           name: opencode-cli-windows
           path: packages/opencode/dist/opencode-windows*
+
+      - uses: actions/upload-artifact@ea165f8d65b6e75b540449e92b4886f43607fa02 # v4.6.2
+        with:
+          name: opencode-preview-cli
+          path: packages/cli/dist/cli-*
+
     outputs:
       version: ${{ needs.version.outputs.version }}
 
+  build-node-cli:
+    needs: version
+    if: github.repository == 'anomalyco/opencode'
+    strategy:
+      fail-fast: false
+      matrix:
+        settings:
+          - target: linux-arm64
+            host: blacksmith-4vcpu-ubuntu-2404-arm
+          - target: linux-x64
+            host: blacksmith-4vcpu-ubuntu-2404
+          - target: darwin-arm64
+            host: macos-26
+          - target: windows-arm64
+            host: blacksmith-4vcpu-windows-2025
+          - target: windows-x64
+            host: blacksmith-4vcpu-windows-2025
+    runs-on: ${{ matrix.settings.host }}
+    defaults:
+      run:
+        shell: bash
+    steps:
+      - uses: actions/checkout@f43a0e5ff2bd294095638e18286ca9a3d1956744 # v3.6.0
+
+      - uses: ./.github/actions/setup-bun
+        with:
+          install-flags: --os=* --cpu=*
+
+      - uses: actions/setup-node@49933ea5288caeca8642d1e84afbd3f7d6820020 # v4.4.0
+        with:
+          node-version: "26.4.0"
+
+      - name: Build
+        run: bun packages/cli/script/build-node.ts --target=${{ matrix.settings.target }} --skip-install --outdir=dist/node
+        env:
+          OPENCODE_VERSION: ${{ needs.version.outputs.version }}
+          OPENCODE_RELEASE: ${{ needs.version.outputs.release }}
+
+      - name: Verify service lifecycle
+        if: matrix.settings.target != 'windows-arm64'
+        working-directory: packages/cli
+        run: bun run script/service-smoke.ts --node
+
+      - uses: actions/upload-artifact@ea165f8d65b6e75b540449e92b4886f43607fa02 # v4.6.2
+        with:
+          name: opencode-node-cli-${{ matrix.settings.target }}
+          path: packages/cli/dist/node/cli-node-*
+          if-no-files-found: error
+
   sign-cli-windows:
     needs:
       - build-cli
       - version
     runs-on: blacksmith-4vcpu-windows-2025
-    if: github.repository == 'anomalyco/opencode'
+    if: github.repository == 'anomalyco/opencode' && github.ref_name != 'v2'
     env:
       AZURE_CLIENT_ID: ${{ secrets.AZURE_CLIENT_ID }}
       AZURE_TENANT_ID: ${{ secrets.AZURE_TENANT_ID }}
@@ -214,7 +274,7 @@ jobs:
     needs:
       - build-cli
       - version
-    if: github.repository == 'anomalyco/opencode'
+    if: github.repository == 'anomalyco/opencode' && github.ref_name != 'v2'
     continue-on-error: false
     env:
       AZURE_CLIENT_ID: ${{ secrets.AZURE_CLIENT_ID }}
@@ -318,6 +378,7 @@ jobs:
         run: bun run build
         working-directory: packages/desktop
         env:
+          NODE_OPTIONS: --max-old-space-size=4096
           OPENCODE_CHANNEL: ${{ (github.ref_name == 'beta' && 'beta') || 'prod' }}
           SENTRY_AUTH_TOKEN: ${{ secrets.SENTRY_AUTH_TOKEN }}
           SENTRY_ORG: ${{ vars.SENTRY_ORG }}
@@ -327,9 +388,9 @@ jobs:
           VITE_SENTRY_ENVIRONMENT: ${{ (github.ref_name == 'beta' && 'beta') || 'production' }}
           VITE_SENTRY_RELEASE: desktop@${{ needs.version.outputs.version }}
 
-      - name: Package and publish
+      - name: Package
         if: needs.version.outputs.release
-        run: npx electron-builder ${{ matrix.settings.platform_flag }} --publish always --config electron-builder.config.ts
+        run: npx electron-builder ${{ matrix.settings.platform_flag }} --publish never --config electron-builder.config.ts
         working-directory: packages/desktop
         timeout-minutes: 60
         env:
@@ -349,11 +410,9 @@ jobs:
         env:
           OPENCODE_CHANNEL: ${{ (github.ref_name == 'beta' && 'beta') || 'prod' }}
 
-      - name: Create and upload macOS .app.tar.gz
+      - name: Create macOS .app.tar.gz
         if: runner.os == 'macOS' && needs.version.outputs.release
         working-directory: packages/desktop/dist
-        env:
-          GH_TOKEN: ${{ steps.committer.outputs.token }}
         run: |
           if [[ "${{ matrix.settings.target }}" == "x86_64-apple-darwin" ]]; then
             APP_DIR="mac"
@@ -371,7 +430,6 @@ jobs:
             exit 1
           fi
           tar -czf "$OUT_NAME" -C "$(dirname "$APP_PATH")" "$(basename "$APP_PATH")"
-          gh release upload "v${{ needs.version.outputs.version }}" "$OUT_NAME" --clobber --repo "${{ needs.version.outputs.repo }}"
 
       - name: Verify signed Windows Electron artifacts
         if: runner.os == 'Windows'
@@ -404,6 +462,7 @@ jobs:
     needs:
       - version
       - build-cli
+      - build-node-cli
       - sign-cli-windows
       - build-electron
     if: always() && !failure() && !cancelled()
@@ -442,16 +501,35 @@ jobs:
           path: packages/opencode/dist
 
       - uses: actions/download-artifact@d3f86a106a0bac45b974a628896c90dbdf5c8093 # v4.3.0
+        if: github.ref_name != 'v2'
         with:
           name: opencode-cli-signed-windows
           path: packages/opencode/dist
 
+      - uses: actions/download-artifact@d3f86a106a0bac45b974a628896c90dbdf5c8093 # v4.3.0
+        with:
+          name: opencode-preview-cli
+          path: packages/cli/dist
+
+      - uses: actions/download-artifact@d3f86a106a0bac45b974a628896c90dbdf5c8093 # v4.3.0
+        with:
+          pattern: opencode-node-cli-*
+          path: packages/cli/dist/node
+          merge-multiple: true
+
       - uses: actions/download-artifact@d3f86a106a0bac45b974a628896c90dbdf5c8093 # v4.3.0
         if: needs.version.outputs.release
         with:
           pattern: latest-yml-*
           path: /tmp/latest-yml
 
+      - uses: actions/download-artifact@d3f86a106a0bac45b974a628896c90dbdf5c8093 # v4.3.0
+        if: needs.version.outputs.release
+        with:
+          pattern: opencode-desktop-*
+          path: /tmp/desktop
+          merge-multiple: true
+
       - name: Setup git committer
         id: committer
         uses: ./.github/actions/setup-git-committer
@@ -478,6 +556,19 @@ jobs:
           git config --global user.name "opencode"
           ssh-keyscan -H aur.archlinux.org >> ~/.ssh/known_hosts || true
 
+      - name: Upload desktop release assets
+        if: needs.version.outputs.release
+        env:
+          GH_TOKEN: ${{ steps.committer.outputs.token }}
+        run: |
+          shopt -s nullglob
+          files=(/tmp/desktop/*.{exe,blockmap,dmg,zip,AppImage,deb,rpm} /tmp/desktop/*.app.tar.gz)
+          if (( ${#files[@]} == 0 )); then
+            echo "No desktop release assets found"
+            exit 1
+          fi
+          gh release upload "v${{ needs.version.outputs.version }}" "${files[@]}" --clobber --repo "${{ needs.version.outputs.repo }}"
+
       - run: ./script/publish.ts
         env:
           OPENCODE_VERSION: ${{ needs.version.outputs.version }}

.github/workflows/storybook.yml

@@ -9,6 +9,7 @@ on:
       - "bun.lock"
       - "packages/storybook/**"
       - "packages/ui/**"
+      - "packages/session-ui/**"
   pull_request:
     branches: [dev]
     paths:
@@ -17,6 +18,7 @@ on:
       - "bun.lock"
       - "packages/storybook/**"
       - "packages/ui/**"
+      - "packages/session-ui/**"
   workflow_dispatch:
 
 concurrency:

.github/workflows/sync-zed-extension.yml

@@ -1,35 +0,0 @@
-name: "sync-zed-extension"
-
-on:
-  workflow_dispatch:
-  release:
-    types: [published]
-
-jobs:
-  zed:
-    name: Release Zed Extension
-    runs-on: blacksmith-4vcpu-ubuntu-2404
-    steps:
-      - uses: actions/checkout@34e114876b0b11c390a56381ad16ebd13914f8d5 # v4.3.1
-        with:
-          fetch-depth: 0
-
-      - uses: ./.github/actions/setup-bun
-
-      - name: Get version tag
-        id: get_tag
-        run: |
-          if [ "${{ github.event_name }}" = "release" ]; then
-            TAG="${{ github.event.release.tag_name }}"
-          else
-            TAG=$(git tag --list 'v[0-9]*.*' --sort=-version:refname | head -n 1)
-          fi
-          echo "tag=${TAG}" >> $GITHUB_OUTPUT
-          echo "Using tag: ${TAG}"
-
-      - name: Sync Zed extension
-        run: |
-          ./script/sync-zed.ts ${{ steps.get_tag.outputs.tag }}
-        env:
-          ZED_EXTENSIONS_PAT: ${{ secrets.ZED_EXTENSIONS_PAT }}
-          ZED_PR_PAT: ${{ secrets.ZED_PR_PAT }}

.github/workflows/test.yml

@@ -4,6 +4,7 @@ on:
   push:
     branches:
       - dev
+      - v2
   pull_request:
   workflow_dispatch:
 
@@ -64,37 +65,41 @@ jobs:
             turbo-${{ runner.os }}-
 
       - name: Run unit tests
-        run: bun turbo test:ci
+        timeout-minutes: 20
+        run: GITHUB_ACTIONS=false bun turbo test
         env:
           OPENCODE_EXPERIMENTAL_DISABLE_FILEWATCHER: ${{ runner.os == 'Windows' && 'true' || 'false' }}
 
-      - name: Run HttpApi exerciser gates
+      - name: Verify compiled service lifecycle
+        if: always()
+        timeout-minutes: 10
+        working-directory: packages/cli
+        run: |
+          bun run script/build.ts --single --skip-install
+          bun run script/service-smoke.ts
+
+      - name: Setup Node build runtime
+        if: always()
+        uses: actions/setup-node@49933ea5288caeca8642d1e84afbd3f7d6820020 # v4.4.0
+        with:
+          node-version: "26.4.0"
+
+      - name: Verify Node build
+        if: always()
+        timeout-minutes: 15
+        working-directory: packages/cli
+        run: |
+          bun run script/build-node.ts --single --skip-install --outdir=dist/node
+          bun run script/service-smoke.ts --node
+
+      - name: Check generated client
         if: runner.os == 'Linux'
-        working-directory: packages/opencode
-        run: bun run test:httpapi
-
-      - name: Publish unit reports
-        if: always()
-        uses: mikepenz/action-junit-report@bccf2e31636835cf0874589931c4116687171386 # v6.4.0
-        with:
-          report_paths: packages/*/.artifacts/unit/junit.xml
-          check_name: "unit results (${{ matrix.settings.name }})"
-          detailed_summary: true
-          include_time_in_summary: true
-          fail_on_failure: false
-
-      - name: Upload unit artifacts
-        if: always()
-        uses: actions/upload-artifact@ea165f8d65b6e75b540449e92b4886f43607fa02 # v4.6.2
-        with:
-          name: unit-${{ matrix.settings.name }}-${{ github.run_attempt }}
-          include-hidden-files: true
-          if-no-files-found: ignore
-          retention-days: 7
-          path: packages/*/.artifacts/unit/junit.xml
+        working-directory: packages/client
+        run: bun run check:generated
 
   e2e:
     name: e2e (${{ matrix.settings.name }})
+    if: github.ref_name != 'v2' && github.head_ref != 'v2'
     strategy:
       fail-fast: false
       matrix:
@@ -118,7 +123,8 @@ jobs:
       - name: Setup Node
         uses: actions/setup-node@49933ea5288caeca8642d1e84afbd3f7d6820020 # v4.4.0
         with:
-          node-version: "24"
+          # Playwright 1.59 hangs while extracting Chromium with Node 24.16.
+          node-version: "24.15"
 
       - name: Setup Bun
         uses: ./.github/actions/setup-bun
@@ -150,7 +156,6 @@ jobs:
         run: bun --cwd packages/app test:e2e:local
         env:
           CI: true
-          PLAYWRIGHT_JUNIT_OUTPUT: e2e/junit-${{ matrix.settings.name }}.xml
         timeout-minutes: 30
 
       - name: Upload Playwright artifacts
@@ -161,6 +166,5 @@ jobs:
           if-no-files-found: ignore
           retention-days: 7
           path: |
-            packages/app/e2e/junit-*.xml
             packages/app/e2e/test-results
             packages/app/e2e/playwright-report

.github/workflows/triage.yml

@@ -16,13 +16,32 @@ jobs:
         with:
           fetch-depth: 1
 
+      - name: Check exempt issue author
+        id: author
+        run: |
+          LOGIN="${{ github.event.issue.user.login }}"
+          ASSOCIATION="${{ github.event.issue.author_association }}"
+
+          if [ "$LOGIN" = "opencode-agent[bot]" ] ||
+             [ "$ASSOCIATION" = "OWNER" ] ||
+             [ "$ASSOCIATION" = "MEMBER" ] ||
+             grep -qxiF "$LOGIN" .github/TEAM_MEMBERS; then
+            echo "skip=true" >> "$GITHUB_OUTPUT"
+            echo "Skipping issue automation for exempt author: $LOGIN ($ASSOCIATION)"
+          else
+            echo "skip=false" >> "$GITHUB_OUTPUT"
+          fi
+
       - name: Setup Bun
+        if: steps.author.outputs.skip != 'true'
         uses: ./.github/actions/setup-bun
 
       - name: Install opencode
+        if: steps.author.outputs.skip != 'true'
         run: curl -fsSL https://opencode.ai/install | bash
 
       - name: Triage issue
+        if: steps.author.outputs.skip != 'true'
         env:
           OPENCODE_API_KEY: ${{ secrets.OPENCODE_API_KEY }}
           GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}

.github/workflows/typecheck.yml

@@ -2,9 +2,9 @@ name: typecheck
 
 on:
   push:
-    branches: [dev]
+    branches: [dev, v2]
   pull_request:
-    branches: [dev]
+    branches: [dev, v2]
   workflow_dispatch:
 
 jobs:

.gitignore

@@ -11,10 +11,14 @@ node_modules
 playground
 tmp
 dist
+dist-node
 ts-dist
 .turbo
+.typecheck-profiles
 **/.serena
 .serena/
+**/.omo
+.omo/
 /result
 refs
 Session.vim
@@ -22,6 +26,7 @@ Session.vim
 a.out
 target
 .scripts
+.cache
 .direnv/
 
 # Local dev files

.opencode/agent/triage.md

@@ -1,7 +1,7 @@
 ---
 mode: primary
 hidden: true
-model: opencode/gpt-5.4-nano
+model: opencode/gpt-5.4-mini
 color: "#44BA81"
 tools:
   "*": false

.opencode/command/translate.md

@@ -1,6 +1,6 @@
 ---
 description: translate English to other languages
-model: opencode/claude-opus-4-7
+model: opencode/claude-opus-4-8
 ---
 
 run git diff and translate changed english doc and UI copy files to other international languages. Translate all languages in parallel to save time.

.opencode/opencode.jsonc

@@ -2,8 +2,15 @@
   "$schema": "https://opencode.ai/config.json",
   "provider": {},
   "permission": {},
-  "reference": {
-    "effect": "github.com/Effect-TS/effect-smol",
+  "references": {
+    "effect": {
+      "repository": "github.com/Effect-TS/effect-smol",
+      "description": "Use for Effect v4 and effect-smol implementation details",
+    },
+    "opencode-local": {
+      "path": "~/.local/share/opencode",
+      "description": "Contains opencode logs and data",
+    },
   },
   "mcp": {},
   "tools": {

.opencode/skills/opencode-drive/SKILL.md

@@ -0,0 +1,254 @@
+---
+name: opencode-drive
+description: Use when an agent needs drive OpenCode via a script or interact with an isolated instance
+---
+
+# OpenCode Drive
+
+Use `opencode-drive` to launch an isolated OpenCode instance and control it via commands or a script.
+
+There are two modes. Always default to using a script unless specifically directed to be interactive (connect
+to an existing running instance, or start a new one, and make a few changes to the UI and read it, and iterate
+on changes).
+
+Scripts allow you to run a full walkthrough in one run. When the script is done opencode-drive exits,
+stops all processes, and cleans up all artifacts.
+
+# Prepare The Environment
+
+Use `init` when files must be added to the isolated home or project before OpenCode starts. It prints the artifact directory without launching OpenCode. A later `start` with the same name reuses it.
+
+```bash
+artifacts=$(opencode-drive init --name demo)
+cp -R ./fixtures/home/. "$artifacts/"
+cp -R ./fixtures/project/. "$artifacts/files/"
+opencode-drive start --name demo --dev ~/projects/opencode
+```
+
+The simulated project is under `$artifacts/files`. Running `start` without a prior `init` initializes the artifacts automatically.
+
+# Scripted usage
+
+You can write scripts that walk through entire flows, and gives you full access to controlling
+the backend too. See examples of the script API at the bottom of this file.
+
+After creating or editing a script, always typecheck it before running. Never skip this step:
+
+```bash
+opencode-drive check ./reproduce-stale-exploring-empty.ts
+```
+
+Run it by passing `--script` to start:
+
+```bash
+opencode-drive start --name auto-stop-reproduction --script ./reproduce-stale-exploring-empty.ts
+```
+
+It will output information about the run, including paths to log files which you can read
+to inspect what happened. If you need to dig into failures that aren't clear, read those log
+files. If the script is unsuccessful, automatically fix the script and run it again.
+
+Scripts use one typed definition object. `setup` runs before OpenCode starts,
+and `fs.writeFile` always writes inside the simulated project.
+
+You can read the full typed API here: https://raw.githubusercontent.com/jlongster/opencode-drive/refs/heads/main/src/script/types.ts
+
+```ts
+import { defineScript } from "opencode-drive"
+
+export default defineScript({
+  async setup({ fs, config }) {
+    config.autoupdate = false
+    await fs.writeFile("src/example.ts", "export const value = 1\n")
+  },
+
+  async run({ ui, llm }) {
+    await ui.submit("Open src/example.ts")
+    await llm.send(llm.text("The file exports `value`."))
+    await ui.waitFor("The file exports `value`.")
+  },
+})
+```
+
+`setup` receives the current OpenCode config object, which starts from the
+default drive config unless the prepared instance already has one. When a script
+needs custom config, mutate this `config` parameter instead of generating and
+writing a new config object from scratch, so the script keeps the default
+provider/model settings unless it intentionally changes them.
+
+Note that the simulated model is a GPT model type, and opencode uses the `patch` tool for working with files Do not use a `edit` or `write` tool to edit files.
+
+Use `launch: "manual"` when the script needs to launch the server and every TUI
+itself (this is extremely rare, do not use this unless explicitly asked). In this
+mode `ui` is typed as `null`; call `server.launch()` exactly
+once before launching clients. Each `clients.launch(name)` result provides the
+same UI methods as the automatic client. You can see an example of this API
+here: https://raw.githubusercontent.com/jlongster/opencode-drive/refs/heads/main/examples/multiple-clients.ts
+
+Use the exported `wait(milliseconds)` utility for an unconditional delay.
+
+`await llm.send(...)` waits for the next request and resolves after OpenCode
+acknowledges its complete response. `llm.queue(...)` declares responses in
+advance. Chunks may be built with `text`, `reasoning`, `toolCall`, `raw`,
+`finish`, and `disconnect`. A normal response receives `finish("stop")`
+automatically unless it yields or queues an explicit terminal event.
+
+`llm.text(text, { delay, chunkSize })` defaults to a 2 ms delay and a
+15-character target varied by plus or minus 5 per chunk.
+
+`llm.reasoning` accepts the same options, and `llm.pause(milliseconds)` adds a
+delay between any two outputs.
+
+Use `llm.serve` for an ongoing typed response generator:
+
+```ts
+llm.serve(async function* (request, index) {
+  yield llm.reasoning(`Handling request ${index + 1}`)
+  yield llm.text(`Received ${request.id}`)
+  yield llm.finish("stop")
+})
+```
+
+The backend connection, response cleanup, cancellation, and recording
+completion are automatic.
+
+You can see some example scripts here:
+
+- https://raw.githubusercontent.com/jlongster/opencode-drive/refs/heads/main/examples/simple.ts
+- https://raw.githubusercontent.com/jlongster/opencode-drive/refs/heads/main/examples/serve.ts
+
+## Prune
+
+- `prune` removes artifact directories. These are always cleaned up after running a script
+  successfully, but leftover on failed runs. Always call this if a script fails.
+
+```bash
+opencode-drive prune --name demo
+
+// --force cleans up all artifcat directories
+opencode-dirve prune --force
+```
+
+# Live interaction usage
+
+- Always give headless instances a unique `--name`. Visible instances may omit it.
+- A normal headless `start` detaches automatically and returns after the instance is ready.
+- Do not add `&`; the long-running owner already runs in the background.
+- Configure simulated model responses after startup when needed.
+- Send ordered UI commands with `send`.
+- Always stop the instance when finished.
+
+```bash
+opencode-drive start --name demo
+
+opencode-drive send --name demo \
+  --command.ui.type '{"text":"Explain this project"}' \
+  --command.ui.enter
+
+opencode-drive stop --name demo
+```
+
+## Send UI Commands
+
+- Every `send` opens a connection to the named instance, runs its commands in order, and exits.
+- Combine typing and Enter in one command when submitting a prompt.
+- JSON-valued commands require one JSON argument.
+- Multiple command flags execute from left to right.
+
+Commands:
+
+- `--command.ui.type <json>` types into the focused editor. Arguments: `text` string.
+- `--command.ui.press <json>` presses a key. Arguments: `key` string; optional `modifiers` object with boolean `ctrl`, `shift`, `meta`, `super`, or `hyper`.
+- `--command.ui.enter` presses Enter. Arguments: none.
+- `--command.ui.arrow <json>` presses an arrow key. Arguments: `direction` is `up`, `down`, `left`, or `right`.
+- `--command.ui.focus <json>` focuses an element. Arguments: `target` is the numeric element `num` returned by `ui.state`.
+- `--command.ui.click <json>` clicks an element. Arguments: numeric `target`, `x`, and `y`; use the element `num` returned by `ui.state` as `target`.
+- `--command.ui.state` prints focus and interactive element metadata as JSON. Arguments: none.
+- `--command.ui.matches <json>` prints whether literal, case-sensitive text appears on screen. Arguments: `text` string.
+
+```bash
+opencode-drive send --name demo \
+  --command.ui.type '{"text":"Find the relevant code and explain it"}' \
+  --command.ui.enter
+
+opencode-drive send --name demo \
+  --command.ui.press '{"key":"p","modifiers":{"ctrl":true}}'
+
+opencode-drive send --name demo \
+  --command.ui.arrow '{"direction":"down"}'
+
+opencode-drive send --name demo \
+  --command.ui.focus '{"target":12}'
+
+opencode-drive send --name demo \
+  --command.ui.click '{"target":12,"x":4,"y":1}'
+
+opencode-drive send --name demo \
+  --command.ui.matches '{"text":"OpenCode"}'
+```
+
+To read the UI state and see information about interactable elements, use the `ui.state` command:
+
+```bash
+opencode-drive send --name demo --command.ui.state
+```
+
+## Configure LLM Responses
+
+- `responses` controls what the LLM responds with
+- Only use this if you are wanting to reproduce an exact type of response
+- Defaults are `text,reasoning,diff,tool` with `write,apply_patch`.
+- Supported types are `text`, `reasoning`, `diff`, and `tool`.
+- `--tools` limits generated tool calls to names offered by OpenCode.
+
+```bash
+opencode-drive responses --name demo \
+  --types text,reasoning,diff,tool \
+  --tools write,apply_patch
+
+opencode-drive responses --name demo \
+  --types tool \
+  --tools read,glob,grep
+```
+
+## Inspect The UI
+
+- `ui.state` prints focus and interactive element metadata as JSON.
+- `ui.matches` checks for literal, case-sensitive screen text.
+- `screenshot` prints the generated image path.
+
+```bash
+opencode-drive screenshot --name demo
+```
+
+## Lifecycle
+
+- `stop` waits for recording export and owner cleanup before returning.
+
+```bash
+opencode-drive stop --name demo
+```
+
+# Record The UI
+
+- Start with `--record` to capture a headless instance from its first rendered frame.
+- `stop` finishes the recording, exports an MP4, and prints its path.
+
+```bash
+opencode-drive start --name demo --record
+
+opencode-drive send --name demo \
+  --command.ui.type '{"text":"Show me the current architecture"}' \
+  --command.ui.enter
+
+opencode-drive stop --name demo
+```
+
+# Artifacts dir
+
+- `dir` prints the artifact directory for the instance.
+
+```bash
+opencode-drive dir --name demo
+```
+

.opencode/skills/sample-skill/SKILL.md

@@ -0,0 +1,31 @@
+---
+name: sample-skill
+description: Use when the user says sample skill, skill demo, or asks how an opencode SKILL.md should be structured; demonstrates a tiny project-local skill with practical assistant workflow guidance.
+---
+
+# Sample Skill
+
+This is a minimal project-local opencode skill. It exists as a reference for how a skill is structured and as a tiny reusable workflow the assistant can load when the user asks for a skill example.
+
+## When To Use
+
+- Use when the user asks for a sample skill or skill template.
+- Use when demonstrating the required `SKILL.md` frontmatter and body format.
+- Do not use for unrelated coding tasks just because a skill exists.
+
+## Workflow
+
+- Confirm the specific outcome the user wants if the request is ambiguous.
+- Inspect the relevant files before changing anything.
+- Make the smallest correct change.
+- Verify the result with a focused read, typecheck, test, or other lightweight check when available.
+- Summarize the changed files and any required restart or reload step.
+
+## Example Response Style
+
+When this skill is relevant, keep responses direct and actionable:
+
+```text
+I created a project-local skill at .opencode/skills/sample-skill/SKILL.md.
+Restart opencode for the new skill to be discovered by future sessions.
+```

.opencode/tool/github-triage.ts

@@ -4,7 +4,7 @@ import { tool } from "@opencode-ai/plugin"
 const TEAM = {
   tui: ["kommander", "simonklee"],
   desktop_web: ["Hona", "Brendonovich"],
-  core: ["jlongster", "rekram1-node", "nexxeln", "kitlangton", "starptech"],
+  core: ["jlongster", "rekram1-node", "nexxeln", "kitlangton"],
   inference: ["fwang", "MrMushrooooom", "starptech"],
   windows: ["Hona"],
 } as const

.prettierignore

@@ -1,2 +1,4 @@
 sst-env.d.ts
 packages/desktop/src/bindings.ts
+packages/client/src/generated/
+packages/client/src/generated-effect/

AGENTS.md

@@ -1,7 +1,16 @@
-- To regenerate the JavaScript SDK, run `./packages/sdk/js/script/build.ts`.
+- To regenerate the legacy JavaScript SDK, run `./packages/sdk/js/script/build.ts`.
+- After changing the public Protocol or Server `HttpApi`, run `bun run generate` from `packages/client`. Do not edit `src/generated` or `src/generated-effect` directly.
+- Keep runtime dependencies directed from Schema to Core and Protocol, then from Core and Protocol to Server. Client runtime code may depend on Schema and Protocol but never Core or Server; `sdk-next` composes Client, Core, and Server.
+- Do not modify `packages/opencode` unless the user explicitly asks for V1 work. `packages/opencode` is the V1 implementation and is present for reference only. New implementation changes should land in the V2 package set: `packages/core`, `packages/cli`, `packages/server`, `packages/protocol`, `packages/schema`, and related generated client surfaces when required.
 - The default branch in this repo is `dev`.
 - Local `main` ref may not exist; use `dev` or `origin/dev` for diffs.
 
+## Branch Names
+
+Use a short branch name of at most three words, separated by hyphens. Do not use slashes or type prefixes such as `feat/` or `fix/`.
+
+Examples: `session-recovery`, `fix-scroll-state`, `regenerate-sdk`.
+
 ## Commits and PR Titles
 
 Use conventional commit-style messages and PR titles: `type(scope): summary`.
@@ -16,12 +25,14 @@ Examples: `fix(tui): simplify thinking toggle styling`, `docs: update contributi
 
 - Keep things in one function unless composable or reusable
 - Do not extract single-use helpers preemptively. Inline the logic at the call site unless the helper is reused, hides a genuinely complex boundary, or has a clear independent name that improves the caller.
+- Before adding complexity for a speculative or vanishingly unlikely race or security edge case, explain the concrete failure mode, likelihood, and complexity cost to the user and get their buy-in. Do not silently expand scope for theoretical robustness.
 - Avoid `try`/`catch` where possible
 - Avoid using the `any` type
 - Use Bun APIs when possible, like `Bun.file()`
 - Rely on type inference when possible; avoid explicit type annotations or interfaces unless necessary for exports or clarity
 - Prefer functional array methods (flatMap, filter, map) over for loops; use type guards on filter to maintain type inference downstream
 - In `src/config`, follow the existing self-export pattern at the top of the file (for example `export * as ConfigAgent from "./agent"`) when adding a new config module.
+- In Effect generators, bind services to named variables before calling methods. Do not use nested service yields such as `yield* (yield* Foo.Service).bar()`.
 
 Reduce total variable count by inlining when a value is only used once.
 
@@ -131,10 +142,25 @@ const table = sqliteTable("session", {
 
 ## Testing
 
-- Avoid mocks as much as possible
+- Avoid mocks as much as possible, you shouldn't be using globalThis.\* at all unless it's the only option.
 - Test actual implementation, do not duplicate logic into tests
 - Tests cannot run from repo root (guard: `do-not-run-tests-from-root`); run from package dirs like `packages/opencode`.
 
 ## Type Checking
 
 - Always run `bun typecheck` from package directories (e.g., `packages/opencode`), never `tsc` directly.
+
+## V2 Session Core
+
+- Keep durable events minimal: record irreducible new facts and do not repeat state derivable by folding the ordered aggregate history. Enrich projections and read models with previous or derived state when consumers need self-contained views.
+- Keep durable prompt admission separate from model execution. `SessionV2.prompt(...)` admits one durable `session_pending` row before scheduling advisory `SessionExecution.wake(sessionID)` unless `resume: false` requests admit-only behavior. The serialized runner promotes admitted inputs into visible user messages at safe boundaries, consuming the pending row in the same event transaction; `session_pending` stores only unconsumed work.
+- Reusing a Session ID adopts the existing Session. Reusing a prompt message ID reconciles an exact retry only when Session, prompt, and delivery mode match; conflicting reuse fails. Retry of an already-promoted input reconciles against the projected message and the durable admitted event rather than a retained row.
+- Keep `SessionExecution` process-global and Session-ID based. Its local implementation owns the process-local Session coordinator and discovers placement through `SessionStore` plus `LocationServiceMap.get(session.location)` only when a drain starts; no layer should take a Session ID. V2 interruption targets the active process-local ownership chain for that Session; interruption of a known but idle or locally unowned Session is a no-op, while the public API rejects an unknown Session.
+- Keep `SessionRunner`, model resolution, tool registry, permissions, and filesystem Location-scoped. Omitted `Location.workspaceID` means implicit-local placement; explicit workspace identity remains reserved for future placement semantics.
+- Preserve one explicit `llm.stream(request)` call per Physical Attempt and reload projected history before durable continuation. Most Steps have one Physical Attempt; overflow-triggered compaction recovery may rebuild one Step for a second attempt. Do not bridge through legacy `SessionPrompt.loop(...)` or delegate orchestration to an in-memory tool loop.
+- Keep local Session drains process-local until clustering is implemented. `SessionRunCoordinator` joins explicit same-Session resumes, coalesces prompt wakeups, and allows different Sessions to run concurrently. Advisory wakes drain eligible durable inbox rows only; post-crash continuation recovery requires a separate explicit design before it may retry provider work. A drain has no durable identity or transcript boundary.
+- Keep delivery vocabulary explicit. Prompts steer by default and promote at the next safe step boundary while the current drain requires continuation. An explicit `queue` input remains pending until the Session would otherwise become idle; promote one queued input at that boundary, then reevaluate continuation before promoting another. Promoting any new user input resets the selected agent's step allowance; a batch of steers resets it once.
+- One step is one logical LLM call; its durable record covers only the model-visible span. Do not write "provider turn", and do not use bare "turn" for a single call: "turn" is reserved for the future assistant-turn unit containing all steps from prompt promotion until the session would go idle.
+- Keep EventV2 replay owner claims separate from clustered Session execution ownership.
+- Keep the Instructions algebra and built-ins in `src/instructions`; keep instruction producers with their observed domains, and keep Session History selection plus `InstructionState` and `InstructionEntry` persistence Session-owned. `InstructionDiscovery` observes ambient global and upward-project instructions. The runner composes built-ins, discovery, guidance, and entries explicitly in `loadInstructions`; there is no instruction registry.
+- `session.instructions.updated` stores only changed source keys and content hashes. Blob values live once in `instruction_blob`; `instruction_state` is a rebuildable fold cache, never primary state. Render initial instructions and chronological updates from values during request assembly. Completed compaction moves the instruction epoch; Session movement and committed revert clear it. Unavailable sources retain the last value and block only the initial complete delta.

README.zh.md

@@ -125,4 +125,4 @@ OpenCode 内置两种 Agent，可用 `Tab` 键快速切换：
 
 ---
 
-**加入我们的社区** [飞书](https://applink.feishu.cn/client/chat/chatter/add_by_link?link_token=738j8655-cd59-4633-a30a-1124e0096789&qr_code=true) | [X.com](https://x.com/opencode)
+**加入我们的社区** [飞书](https://applink.feishu.cn/client/chat/chatter/add_by_link?link_token=52ao9352-5623-4fa0-b7dd-3407c392c1af&qr_code=true) | [X.com](https://x.com/opencode)

README.zht.md

@@ -125,4 +125,4 @@ OpenCode 內建了兩種 Agent，您可以使用 `Tab` 鍵快速切換。
 
 ---
 
-**加入我們的社群** [飞书](https://applink.feishu.cn/client/chat/chatter/add_by_link?link_token=738j8655-cd59-4633-a30a-1124e0096789&qr_code=true) | [X.com](https://x.com/opencode)
+**加入我們的社群** [飞书](https://applink.feishu.cn/client/chat/chatter/add_by_link?link_token=52ao9352-5623-4fa0-b7dd-3407c392c1af&qr_code=true) | [X.com](https://x.com/opencode)

artifacts/glm52-rise-video/.gitignore

@@ -0,0 +1,3 @@
+node_modules
+.remotion
+out/frame-*.png

artifacts/glm52-rise-video/bun.lock

@@ -0,0 +1,483 @@
+{
+  "lockfileVersion": 1,
+  "configVersion": 1,
+  "workspaces": {
+    "": {
+      "name": "glm52-rise-video",
+      "dependencies": {
+        "@remotion/cli": "^4.0.384",
+        "react": "^19.2.3",
+        "react-dom": "^19.2.3",
+        "remotion": "^4.0.384",
+      },
+      "devDependencies": {
+        "@types/react": "^19.2.8",
+        "@types/react-dom": "^19.2.3",
+        "typescript": "^5.8.2",
+      },
+    },
+  },
+  "packages": {
+    "@babel/helper-string-parser": ["@babel/helper-string-parser@7.29.7", "", {}, "sha512-Pb5ijPrZ89GDH8223L4UP8i6QApWxs04RbPQJTeWDV0/keR2E36MeKnyr6LYmUUvqRRI+Iv87SuF1W6ErINzYw=="],
+
+    "@babel/helper-validator-identifier": ["@babel/helper-validator-identifier@7.29.7", "", {}, "sha512-qehxGkRj55h/ff8EMaJ+cYhyaKlHIxqYDn682wQD7RNp9UujOQsHog2uS0r2vzr4pW+sXf90NeeayjcNaX3fFg=="],
+
+    "@babel/parser": ["@babel/parser@7.24.1", "", { "bin": "./bin/babel-parser.js" }, "sha512-Zo9c7N3xdOIQrNip7Lc9wvRPzlRtovHVE4lkz8WEDr7uYh/GMQhSiIgFxGIArRHYdJE5kxtZjAf8rT0xhdLCzg=="],
+
+    "@babel/types": ["@babel/types@7.24.0", "", { "dependencies": { "@babel/helper-string-parser": "^7.23.4", "@babel/helper-validator-identifier": "^7.22.20", "to-fast-properties": "^2.0.0" } }, "sha512-+j7a5c253RfKh8iABBhywc8NSfP5LURe7Uh4qpsh6jc+aLJguvmIUBdjSdEMQv2bENrCR5MfRdjGo7vzS/ob7w=="],
+
+    "@emnapi/core": ["@emnapi/core@1.11.1", "", { "dependencies": { "@emnapi/wasi-threads": "1.2.2", "tslib": "^2.4.0" } }, "sha512-RSvbQmHzdKzNsLYa/wHrbc3KN4sYLKAdPZxqiM2HATqv/SBk2/ENSHpvXGaLOMcsAyz0poEGqkmmKYG3OWiJEQ=="],
+
+    "@emnapi/runtime": ["@emnapi/runtime@1.11.1", "", { "dependencies": { "tslib": "^2.4.0" } }, "sha512-vgj7R3y3Wgx24IQaGPA/R6YFXLHVMOZ0uVEyIQPaWs+rd1AzfEMXlAC22FYwO1XkKR6NPsq7mUandH8oIRdZFw=="],
+
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+    "tapable": ["tapable@2.3.3", "", {}, "sha512-uxc/zpqFg6x7C8vOE7lh6Lbda8eEL9zmVm/PLeTPBRhh1xCgdWaQ+J1CUieGpIfm2HdtsUpRv+HshiasBMcc6A=="],
+
+    "terser": ["terser@5.48.0", "", { "dependencies": { "@jridgewell/source-map": "^0.3.3", "acorn": "^8.15.0", "commander": "^2.20.0", "source-map-support": "~0.5.20" }, "bin": { "terser": "bin/terser" } }, "sha512-J/9An6vs9Us6wKRriSFXBWdRZapREHqFzdNUKk0pmu804EMR6dr6winwo7e5JDxN4xahxQsuysyYFwlwj4XN/Q=="],
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+    "terser-webpack-plugin": ["terser-webpack-plugin@5.6.1", "", { "dependencies": { "@jridgewell/trace-mapping": "^0.3.25", "jest-worker": "^27.4.5", "schema-utils": "^4.3.0", "terser": "^5.31.1" }, "peerDependencies": { "webpack": "^5.1.0" } }, "sha512-201R5j+sJpK8nFWwKVyNfZot8FaJbLZDq5evriVzbV1wDtSXDjRUDRfJzHpAaxFDMEhsZL1QkeqM61wgsS3KaQ=="],
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+    "tiny-invariant": ["tiny-invariant@1.3.3", "", {}, "sha512-+FbBPE1o9QAYvviau/qC5SE3caw21q3xkvWKBtja5vgqOWIHHJ3ioaq1VPfn/Szqctz2bU/oYeKd9/z5BL+PVg=="],
+
+    "to-fast-properties": ["to-fast-properties@2.0.0", "", {}, "sha512-/OaKK0xYrs3DmxRYqL/yDc+FxFUVYhDlXMhRmv3z915w2HF1tnN1omB354j8VUGO/hbRzyD6Y3sA7v7GS/ceog=="],
+
+    "tr46": ["tr46@1.0.1", "", { "dependencies": { "punycode": "^2.1.0" } }, "sha512-dTpowEjclQ7Kgx5SdBkqRzVhERQXov8/l9Ft9dVM9fmg0W0KQSVaXX9T4i6twCPNtYiZM53lpSSUAwJbFPOHxA=="],
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+    "tslib": ["tslib@2.8.1", "", {}, "sha512-oJFu94HQb+KVduSUQL7wnpmqnfmLsOA/nAh6b6EH0wCEoK0/mPeXU6c3wKDV83MkOuHPRHtSXKKU99IBazS/2w=="],
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+    "undici-types": ["undici-types@8.3.0", "", {}, "sha512-j375ScV60dom+YkPFIfTLcOiPxkN/buHz5GobjLhixFuANaNs3C9l4GmrWqejgXWJ7BbJcFYpTEUkS1Ge8bpZQ=="],
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+    "zod": ["zod@4.3.6", "", {}, "sha512-rftlrkhHZOcjDwkGlnUtZZkvaPHCsDATp4pGpuOOMDaTdDDXF91wuVDJoWoPsKX/3YPQ5fHuF3STjcYyKr+Qhg=="],
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+    "css-loader/semver": ["semver@7.8.5", "", { "bin": { "semver": "bin/semver.js" } }, "sha512-Y7/KDsb8LjooZpwaqGyulO6DQlksgCncchHGk+sZIY4SBvUocMBEFH5Ur1fI4dV+Jvl0w6cjvucaIi40puRioA=="],
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+    "esrecurse/estraverse": ["estraverse@5.3.0", "", {}, "sha512-MMdARuVEQziNTeJD8DgMqmhwR11BRQ/cBP+pLtYdSTnf3MIO8fFeiINEbX36ZdNlfU/7A9f3gUw49B3oQsvwBA=="],
+
+    "recast/source-map": ["source-map@0.6.1", "", {}, "sha512-UjgapumWlbMhkBgzT7Ykc5YXUT46F0iKu8SGXq0bcwP5dz/h0Plj6enJqjz1Zbq2l5WaqYnrVbwWOWMyF3F47g=="],
+
+    "source-map-support/source-map": ["source-map@0.6.1", "", {}, "sha512-UjgapumWlbMhkBgzT7Ykc5YXUT46F0iKu8SGXq0bcwP5dz/h0Plj6enJqjz1Zbq2l5WaqYnrVbwWOWMyF3F47g=="],
+  }
+}

artifacts/glm52-rise-video/package.json

@@ -0,0 +1,24 @@
+{
+  "name": "glm52-rise-video",
+  "private": true,
+  "type": "module",
+  "scripts": {
+    "render": "remotion render src/index.tsx GLM52Rise out/glm-52-broke-out.mp4 --codec h264 --pixel-format yuv420p",
+    "render:sheep": "remotion render src/index.tsx NZSheep out/nz-sheep.mp4 --codec h264 --pixel-format yuv420p",
+    "render:novel": "remotion render src/index.tsx NovelTokens out/novel-1984.mp4 --codec h264 --pixel-format yuv420p",
+    "render:flash": "remotion render src/index.tsx FlashShare out/flash-share.mp4 --codec h264 --pixel-format yuv420p",
+    "render:minimax": "remotion render src/index.tsx MiniMaxClimb out/minimax-climb.mp4 --codec h264 --pixel-format yuv420p",
+    "still:june": "remotion still src/index.tsx JuneTotals out/june-totals.png --frame=0"
+  },
+  "dependencies": {
+    "@remotion/cli": "^4.0.384",
+    "react": "^19.2.3",
+    "react-dom": "^19.2.3",
+    "remotion": "^4.0.384"
+  },
+  "devDependencies": {
+    "@types/react": "^19.2.8",
+    "@types/react-dom": "^19.2.3",
+    "typescript": "^5.8.2"
+  }
+}

artifacts/glm52-rise-video/src/data.ts

@@ -0,0 +1,156 @@
+// Verified against the production opencode-stats PlanetScale DB.
+// Scope: tier='Go' (OpenCode Go), dataset='zen', client='all', source='all', grain='day'.
+// metric = total_tokens. Daily token volume per model; GLM-5.2 (zhipu) launched Jun 17.
+// Segments per day (tokens): glm-5.2, deepseek-v4-flash, deepseek-v4-pro, minimax-m3, all others.
+
+export type Day = {
+  date: string
+  total: number
+  glm: number
+  dsf: number
+  dsp: number
+  mm: number
+  others: number
+}
+
+export const days: Day[] = [
+  {
+    date: "Jun 12",
+    total: 2_283_799_449_383,
+    glm: 0,
+    dsf: 1_176_701_653_509,
+    dsp: 569_527_034_307,
+    mm: 159_016_250_684,
+    others: 378_554_510_883,
+  },
+  {
+    date: "Jun 13",
+    total: 2_008_462_388_420,
+    glm: 0,
+    dsf: 995_338_131_997,
+    dsp: 445_817_536_548,
+    mm: 211_743_241_967,
+    others: 355_563_477_908,
+  },
+  {
+    date: "Jun 14",
+    total: 2_007_785_405_251,
+    glm: 0,
+    dsf: 983_954_176_228,
+    dsp: 428_151_999_341,
+    mm: 262_476_527_930,
+    others: 333_202_701_752,
+  },
+  {
+    date: "Jun 15",
+    total: 2_694_736_103_062,
+    glm: 0,
+    dsf: 1_255_893_953_859,
+    dsp: 632_223_338_376,
+    mm: 352_507_442_991,
+    others: 454_111_367_836,
+  },
+  {
+    date: "Jun 16",
+    total: 2_838_153_758_908,
+    glm: 0,
+    dsf: 1_336_625_283_800,
+    dsp: 676_480_415_730,
+    mm: 305_268_829_013,
+    others: 519_779_230_365,
+  },
+  {
+    date: "Jun 17",
+    total: 2_778_964_711_109,
+    glm: 70_095_977_043,
+    dsf: 1_339_831_523_555,
+    dsp: 660_414_395_220,
+    mm: 251_302_096_157,
+    others: 457_320_719_134,
+  },
+  {
+    date: "Jun 18",
+    total: 2_806_992_430_656,
+    glm: 201_130_231_172,
+    dsf: 1_295_599_996_869,
+    dsp: 595_665_008_776,
+    mm: 322_205_104_324,
+    others: 392_392_089_515,
+  },
+  {
+    date: "Jun 19",
+    total: 2_419_611_630_232,
+    glm: 199_086_413_910,
+    dsf: 1_115_750_468_802,
+    dsp: 475_965_869_304,
+    mm: 303_586_698_735,
+    others: 325_222_179_481,
+  },
+  {
+    date: "Jun 20",
+    total: 2_188_278_916_865,
+    glm: 193_931_516_396,
+    dsf: 1_050_194_681_012,
+    dsp: 395_303_435_278,
+    mm: 281_998_000_337,
+    others: 266_851_283_842,
+  },
+  {
+    date: "Jun 21",
+    total: 2_042_309_961_344,
+    glm: 181_894_043_118,
+    dsf: 985_164_570_580,
+    dsp: 368_194_079_542,
+    mm: 259_812_551_324,
+    others: 247_244_716_780,
+  },
+  {
+    date: "Jun 22",
+    total: 2_893_934_325_663,
+    glm: 301_759_048_475,
+    dsf: 1_298_124_282_989,
+    dsp: 581_012_596_194,
+    mm: 371_581_117_839,
+    others: 341_457_280_166,
+  },
+  {
+    date: "Jun 23",
+    total: 3_109_009_321_480,
+    glm: 282_277_235_158,
+    dsf: 1_423_571_678_821,
+    dsp: 627_374_654_587,
+    mm: 429_416_300_508,
+    others: 346_369_452_406,
+  },
+  {
+    date: "Jun 24",
+    total: 2_939_149_971_595,
+    glm: 256_497_442_533,
+    dsf: 1_373_583_023_234,
+    dsp: 601_270_997_775,
+    mm: 391_586_493_231,
+    others: 316_212_014_822,
+  },
+  {
+    date: "Jun 25",
+    total: 3_029_641_552_948,
+    glm: 256_279_657_734,
+    dsf: 1_481_084_002_776,
+    dsp: 602_077_167_287,
+    mm: 375_985_302_874,
+    others: 314_215_422_277,
+  },
+]
+
+export const launchIndex = 5 // Jun 17, first day of GLM-5.2 usage
+// GLM-5.2 weekly token volume, Jun 19-25 (sum of glm): 1,671,725,357,324 = 1.67T
+export const glmWeekTokensT = 1.672
+
+// stacked segments, bottom -> top. GLM-5.2 is the hero (blue); the rest are the field it cut into.
+export const segments = [
+  { key: "glm", label: "GLM-5.2", color: "#3b5cf6", hero: true },
+  { key: "dsf", label: "deepseek-v4-flash", color: "#9ca3ad" },
+  { key: "dsp", label: "deepseek-v4-pro", color: "#b3b9c1" },
+  { key: "mm", label: "minimax-m3", color: "#c8cdd3" },
+  { key: "others", label: "other models", color: "#dde0e4" },
+] as const

artifacts/glm52-rise-video/src/flash.tsx

@@ -0,0 +1,185 @@
+import React from "react"
+import { AbsoluteFill, Easing, interpolate, spring, useCurrentFrame, useVideoConfig } from "remotion"
+
+// stats.opencode.ai design tokens (light theme)
+const c = {
+  bg: "#ffffff",
+  ink: "#161616",
+  muted: "#5c5c5c",
+  faint: "#808080",
+  line: "#e6e6e6",
+  dot: "#e4e4e4",
+  gray: "#aab0b8",
+  accent: "#3b5cf6",
+  accentHi: "#5b78ff",
+}
+const MONO = '"IBM Plex Mono", ui-monospace, SFMono-Regular, Menlo, Monaco, Consolas, monospace'
+
+const DOT_MASK =
+  "url(\"data:image/svg+xml,%3Csvg viewBox='0 0 6 6' xmlns='http://www.w3.org/2000/svg'%3E%3Cpath d='M0 0H2V2H0V0Z' fill='black'/%3E%3C/svg%3E\")"
+
+// verified: OpenCode Go, week of Jun 22-28, 2026 (2026-W26). share = % of 19.64T total Go tokens.
+const bars = [
+  { label: "deepseek-v4-flash", share: 48.3, hero: true },
+  { label: "deepseek-v4-pro", share: 19.4 },
+  { label: "minimax-m3", share: 13.0 },
+  { label: "glm-5.2", share: 8.3 },
+  { label: "mimo-v2.5", share: 4.3 },
+  { label: "kimi-k2.7-code", share: 2.6 },
+  { label: "other models", share: 4.1 },
+]
+
+function DataWordmark({ height = 30 }: { height?: number }) {
+  return (
+    <svg width={(height * 66) / 20} height={height} viewBox="0 0 66 20" fill="none" style={{ color: c.ink }}>
+      <path opacity="0.2" d="M12 16H4V8H12V16Z" fill="currentColor" />
+      <path d="M12 4H4V16H12V4ZM16 20H0V0H16V20Z" fill="currentColor" />
+      <path
+        d="M63.3543 16L62.5119 12.8711H58.6437L57.8013 16H55.7383L59.2454 4H61.9618L65.4689 16H63.3543ZM61.0678 7.851L60.6896 5.94269H60.4489L60.0707 7.851L59.1595 11.1347H61.9962L61.0678 7.851Z"
+        fill="currentColor"
+      />
+      <path d="M52.5951 5.87392V16H50.4461V5.87392H47.4375V4H55.6209V5.87392H52.5951Z" fill="currentColor" />
+      <path
+        d="M45.2059 16L44.3635 12.8711H40.4953L39.6529 16H37.5898L41.097 4H43.8133L47.3205 16H45.2059ZM42.9194 7.851L42.5411 5.94269H42.3004L41.9222 7.851L41.011 11.1347H43.8477L42.9194 7.851Z"
+        fill="currentColor"
+      />
+      <path
+        d="M28 4H32.0917C32.8138 4 33.4556 4.11461 34.0172 4.34384C34.5903 4.5616 35.0716 4.9169 35.4613 5.40974C35.8625 5.89112 36.1662 6.51003 36.3725 7.26648C36.5788 8.02292 36.6819 8.9341 36.6819 10C36.6819 11.0659 36.5788 11.9771 36.3725 12.7335C36.1662 13.49 35.8625 14.1146 35.4613 14.6075C35.0716 15.0888 34.5903 15.4441 34.0172 15.6734C33.4556 15.8911 32.8138 16 32.0917 16H28V4ZM32.0917 14.1261C32.8252 14.1261 33.3926 13.9026 33.7937 13.4556C34.1948 12.9971 34.3954 12.3152 34.3954 11.4097V8.59026C34.3954 7.68481 34.1948 7.0086 33.7937 6.5616C33.3926 6.10315 32.8252 5.87392 32.0917 5.87392H30.149V14.1261H32.0917Z"
+        fill="currentColor"
+      />
+    </svg>
+  )
+}
+
+export function FlashShare() {
+  const frame = useCurrentFrame()
+  const { fps } = useVideoConfig()
+
+  const grow = (i: number) =>
+    Math.min(
+      1,
+      Math.max(0, spring({ frame: frame - 18 - i * 7, fps, config: { damping: 18, stiffness: 120, mass: 0.6 } })),
+    )
+
+  return (
+    <AbsoluteFill style={{ background: c.bg, color: c.ink, fontFamily: MONO, padding: 72, boxSizing: "border-box" }}>
+      <div style={{ height: "100%", display: "flex", flexDirection: "column" }}>
+        {/* header */}
+        <div style={{ display: "flex", justifyContent: "space-between", alignItems: "center" }}>
+          <DataWordmark height={30} />
+          <div style={{ fontSize: 20, fontWeight: 500, color: c.faint, letterSpacing: 1 }}>JUN 22–28, 2026</div>
+        </div>
+
+        {/* headline (static) */}
+        <div style={{ marginTop: 50 }}>
+          <div style={{ fontSize: 23, fontWeight: 600, color: c.muted, letterSpacing: 2 }}>
+            OPENCODE GO · SHARE OF TOKENS
+          </div>
+          <div
+            style={{ display: "flex", justifyContent: "space-between", alignItems: "baseline", gap: 24, marginTop: 14 }}
+          >
+            <div style={{ fontSize: 62, fontWeight: 600, letterSpacing: -2, lineHeight: 1 }}>DeepSeek V4 Flash</div>
+            <div
+              style={{
+                fontSize: 88,
+                fontWeight: 600,
+                letterSpacing: -2,
+                lineHeight: 1,
+                color: c.accent,
+                fontVariantNumeric: "tabular-nums",
+              }}
+            >
+              48%
+            </div>
+          </div>
+        </div>
+
+        {/* bar chart */}
+        <div style={{ flex: 1, display: "flex", flexDirection: "column", justifyContent: "center", gap: 16 }}>
+          {bars.map((b, i) => {
+            const g = grow(i)
+            const pct = b.share * g
+            return (
+              <div key={b.label} style={{ display: "flex", alignItems: "center", gap: 18 }}>
+                <div
+                  style={{
+                    width: 268,
+                    fontSize: 23,
+                    fontWeight: b.hero ? 600 : 500,
+                    color: b.hero ? c.ink : c.muted,
+                    textAlign: "right",
+                    whiteSpace: "nowrap",
+                  }}
+                >
+                  {b.label}
+                </div>
+                <div style={{ position: "relative", flex: 1, height: 48 }}>
+                  {/* dotted 100% track — height is a multiple of the 12px tile, anchored bottom, so dots never clip */}
+                  <div
+                    style={{
+                      position: "absolute",
+                      inset: 0,
+                      background: c.dot,
+                      WebkitMaskImage: DOT_MASK,
+                      maskImage: DOT_MASK,
+                      WebkitMaskSize: "12px 12px",
+                      maskSize: "12px 12px",
+                      WebkitMaskRepeat: "repeat",
+                      maskRepeat: "repeat",
+                      WebkitMaskPosition: "left bottom",
+                      maskPosition: "left bottom",
+                    }}
+                  />
+                  {/* fill */}
+                  <div
+                    style={{
+                      position: "absolute",
+                      left: 0,
+                      top: 0,
+                      bottom: 0,
+                      width: `${pct}%`,
+                      background: b.hero ? c.accent : c.gray,
+                      borderRight: b.hero ? `2px solid ${c.accentHi}` : "none",
+                    }}
+                  />
+                </div>
+                <div
+                  style={{
+                    width: 84,
+                    fontSize: 24,
+                    fontWeight: b.hero ? 600 : 500,
+                    color: b.hero ? c.accent : c.muted,
+                    textAlign: "right",
+                    fontVariantNumeric: "tabular-nums",
+                  }}
+                >
+                  {Math.round(pct)}%
+                </div>
+              </div>
+            )
+          })}
+        </div>
+
+        {/* footer */}
+        <div
+          style={{
+            display: "flex",
+            justifyContent: "space-between",
+            alignItems: "center",
+            marginTop: 24,
+            paddingTop: 22,
+            borderTop: `1px solid ${c.line}`,
+            fontSize: 20,
+            fontWeight: 500,
+          }}
+        >
+          <div style={{ display: "inline-flex", alignItems: "center", gap: 9, color: c.muted }}>
+            <span style={{ width: 13, height: 13, background: c.accent, display: "inline-block" }} />
+            DeepSeek V4 Flash · 9.48T tokens · 83.6M requests
+          </div>
+          <div style={{ color: c.ink }}>opencode.ai/data</div>
+        </div>
+      </div>
+    </AbsoluteFill>
+  )
+}

artifacts/glm52-rise-video/src/index.tsx

@@ -0,0 +1,36 @@
+import { Composition, registerRoot } from "remotion"
+import { GLM52Rise } from "./video"
+import { NZSheep } from "./sheep"
+import { NovelTokens } from "./novel"
+import { FlashShare } from "./flash"
+import { MiniMaxClimb } from "./minimax"
+import { JuneTotals } from "./june"
+
+function Root() {
+  return (
+    <>
+      <Composition id="GLM52Rise" component={GLM52Rise} durationInFrames={240} fps={30} width={1080} height={1080} />
+      <Composition id="NZSheep" component={NZSheep} durationInFrames={150} fps={30} width={1080} height={1080} />
+      <Composition
+        id="NovelTokens"
+        component={NovelTokens}
+        durationInFrames={150}
+        fps={30}
+        width={1080}
+        height={1080}
+      />
+      <Composition id="FlashShare" component={FlashShare} durationInFrames={165} fps={30} width={1080} height={1080} />
+      <Composition
+        id="MiniMaxClimb"
+        component={MiniMaxClimb}
+        durationInFrames={165}
+        fps={30}
+        width={1080}
+        height={1080}
+      />
+      <Composition id="JuneTotals" component={JuneTotals} durationInFrames={1} fps={30} width={1080} height={1080} />
+    </>
+  )
+}
+
+registerRoot(Root)

artifacts/glm52-rise-video/src/june.tsx

@@ -0,0 +1,144 @@
+import React from "react"
+import { AbsoluteFill } from "remotion"
+
+const c = {
+  bg: "#ffffff",
+  ink: "#161616",
+  muted: "#5c5c5c",
+  faint: "#808080",
+  line: "#e6e6e6",
+  dot: "#dcdcdc",
+  accent: "#3b5cf6",
+}
+const MONO = '"IBM Plex Mono", ui-monospace, SFMono-Regular, Menlo, Monaco, Consolas, monospace'
+
+const DOT_MASK =
+  "url(\"data:image/svg+xml,%3Csvg viewBox='0 0 6 6' xmlns='http://www.w3.org/2000/svg'%3E%3Cpath d='M0 0H2V2H0V0Z' fill='black'/%3E%3C/svg%3E\")"
+
+// verified: OpenCode Go (tier=Go, dataset=zen), June 1-30, 2026.
+// 72.78T tokens · 651.4M requests · 11.42M sessions -> rounded headline figures.
+
+function DataWordmark({ height = 30 }: { height?: number }) {
+  return (
+    <svg width={(height * 66) / 20} height={height} viewBox="0 0 66 20" fill="none" style={{ color: c.ink }}>
+      <path opacity="0.2" d="M12 16H4V8H12V16Z" fill="currentColor" />
+      <path d="M12 4H4V16H12V4ZM16 20H0V0H16V20Z" fill="currentColor" />
+      <path
+        d="M63.3543 16L62.5119 12.8711H58.6437L57.8013 16H55.7383L59.2454 4H61.9618L65.4689 16H63.3543ZM61.0678 7.851L60.6896 5.94269H60.4489L60.0707 7.851L59.1595 11.1347H61.9962L61.0678 7.851Z"
+        fill="currentColor"
+      />
+      <path d="M52.5951 5.87392V16H50.4461V5.87392H47.4375V4H55.6209V5.87392H52.5951Z" fill="currentColor" />
+      <path
+        d="M45.2059 16L44.3635 12.8711H40.4953L39.6529 16H37.5898L41.097 4H43.8133L47.3205 16H45.2059ZM42.9194 7.851L42.5411 5.94269H42.3004L41.9222 7.851L41.011 11.1347H43.8477L42.9194 7.851Z"
+        fill="currentColor"
+      />
+      <path
+        d="M28 4H32.0917C32.8138 4 33.4556 4.11461 34.0172 4.34384C34.5903 4.5616 35.0716 4.9169 35.4613 5.40974C35.8625 5.89112 36.1662 6.51003 36.3725 7.26648C36.5788 8.02292 36.6819 8.9341 36.6819 10C36.6819 11.0659 36.5788 11.9771 36.3725 12.7335C36.1662 13.49 35.8625 14.1146 35.4613 14.6075C35.0716 15.0888 34.5903 15.4441 34.0172 15.6734C33.4556 15.8911 32.8138 16 32.0917 16H28V4ZM32.0917 14.1261C32.8252 14.1261 33.3926 13.9026 33.7937 13.4556C34.1948 12.9971 34.3954 12.3152 34.3954 11.4097V8.59026C34.3954 7.68481 34.1948 7.0086 33.7937 6.5616C33.3926 6.10315 32.8252 5.87392 32.0917 5.87392H30.149V14.1261H32.0917Z"
+        fill="currentColor"
+      />
+    </svg>
+  )
+}
+
+function DotBand() {
+  return (
+    <div
+      style={{
+        height: 12,
+        background: c.dot,
+        WebkitMaskImage: DOT_MASK,
+        maskImage: DOT_MASK,
+        WebkitMaskSize: "12px 12px",
+        maskSize: "12px 12px",
+        WebkitMaskRepeat: "repeat",
+        maskRepeat: "repeat",
+        WebkitMaskPosition: "left top",
+        maskPosition: "left top",
+      }}
+    />
+  )
+}
+
+function Metric({ value, label }: { value: string; label: string }) {
+  return (
+    <div>
+      <div
+        style={{
+          fontSize: 92,
+          fontWeight: 600,
+          letterSpacing: -3,
+          lineHeight: 1,
+          fontVariantNumeric: "tabular-nums",
+          marginLeft: -8, // align the glyph's visual left edge to the column
+        }}
+      >
+        {value}
+      </div>
+      <div style={{ marginTop: 16, fontSize: 24, fontWeight: 500, color: c.muted, letterSpacing: 1 }}>{label}</div>
+    </div>
+  )
+}
+
+export function JuneTotals() {
+  return (
+    <AbsoluteFill style={{ background: c.bg, color: c.ink, fontFamily: MONO, padding: 72, boxSizing: "border-box" }}>
+      <div style={{ height: "100%", display: "flex", flexDirection: "column" }}>
+        {/* header */}
+        <div style={{ display: "flex", justifyContent: "space-between", alignItems: "center", marginBottom: 22 }}>
+          <DataWordmark height={30} />
+          <div style={{ fontSize: 20, fontWeight: 500, color: c.faint, letterSpacing: 1 }}>MONTHLY RECAP</div>
+        </div>
+        <DotBand />
+
+        {/* hero */}
+        <div style={{ flex: 1, display: "flex", flexDirection: "column", justifyContent: "center" }}>
+          <div style={{ fontSize: 25, fontWeight: 600, color: c.muted, letterSpacing: 3 }}>OPENCODE GO · JUNE 2026</div>
+          <div style={{ marginTop: 14 }}>
+            <div
+              style={{
+                fontSize: 300,
+                fontWeight: 600,
+                letterSpacing: -10,
+                lineHeight: 0.82,
+                color: c.accent,
+                marginLeft: -22,
+              }}
+            >
+              73T
+            </div>
+            <div style={{ fontSize: 50, fontWeight: 600, color: c.ink, marginTop: 10 }}>tokens processed</div>
+          </div>
+
+          {/* supporting metrics */}
+          <div
+            style={{
+              display: "grid",
+              gridTemplateColumns: "1fr 1fr",
+              marginTop: 60,
+              paddingTop: 40,
+              borderTop: `1px solid ${c.line}`,
+            }}
+          >
+            <Metric value="650M" label="requests" />
+            <Metric value="11M" label="sessions" />
+          </div>
+        </div>
+
+        {/* footer */}
+        <DotBand />
+        <div
+          style={{
+            display: "flex",
+            justifyContent: "flex-end",
+            alignItems: "center",
+            marginTop: 22,
+            fontSize: 20,
+            fontWeight: 500,
+          }}
+        >
+          <div style={{ color: c.ink }}>opencode.ai/data</div>
+        </div>
+      </div>
+    </AbsoluteFill>
+  )
+}

artifacts/glm52-rise-video/src/minimax.tsx

@@ -0,0 +1,201 @@
+import React from "react"
+import { AbsoluteFill, interpolate, spring, useCurrentFrame, useVideoConfig } from "remotion"
+
+const c = {
+  bg: "#ffffff",
+  ink: "#161616",
+  muted: "#5c5c5c",
+  faint: "#808080",
+  line: "#e6e6e6",
+  dot: "#e4e4e4",
+  accent: "#3b5cf6",
+  accentHi: "#5b78ff",
+  accentDim: "#aebcf3",
+}
+const MONO = '"IBM Plex Mono", ui-monospace, SFMono-Regular, Menlo, Monaco, Consolas, monospace'
+
+const DOT_MASK =
+  "url(\"data:image/svg+xml,%3Csvg viewBox='0 0 6 6' xmlns='http://www.w3.org/2000/svg'%3E%3Cpath d='M0 0H2V2H0V0Z' fill='black'/%3E%3C/svg%3E\")"
+
+// verified: minimax-m3, OpenCode Go (tier=Go, dataset=zen), weekly total_tokens.
+// W26 2.559T is +23.2% / +482.3B vs W25 2.077T.
+const weeks = [
+  { label: "May 25", t: 0.008 },
+  { label: "Jun 1", t: 0.429 },
+  { label: "Jun 8", t: 1.192 },
+  { label: "Jun 15", t: 2.077 },
+  { label: "Jun 22", t: 2.559, latest: true },
+]
+const AXIS_MAX = 3.0
+
+function DataWordmark({ height = 30 }: { height?: number }) {
+  return (
+    <svg width={(height * 66) / 20} height={height} viewBox="0 0 66 20" fill="none" style={{ color: c.ink }}>
+      <path opacity="0.2" d="M12 16H4V8H12V16Z" fill="currentColor" />
+      <path d="M12 4H4V16H12V4ZM16 20H0V0H16V20Z" fill="currentColor" />
+      <path
+        d="M63.3543 16L62.5119 12.8711H58.6437L57.8013 16H55.7383L59.2454 4H61.9618L65.4689 16H63.3543ZM61.0678 7.851L60.6896 5.94269H60.4489L60.0707 7.851L59.1595 11.1347H61.9962L61.0678 7.851Z"
+        fill="currentColor"
+      />
+      <path d="M52.5951 5.87392V16H50.4461V5.87392H47.4375V4H55.6209V5.87392H52.5951Z" fill="currentColor" />
+      <path
+        d="M45.2059 16L44.3635 12.8711H40.4953L39.6529 16H37.5898L41.097 4H43.8133L47.3205 16H45.2059ZM42.9194 7.851L42.5411 5.94269H42.3004L41.9222 7.851L41.011 11.1347H43.8477L42.9194 7.851Z"
+        fill="currentColor"
+      />
+      <path
+        d="M28 4H32.0917C32.8138 4 33.4556 4.11461 34.0172 4.34384C34.5903 4.5616 35.0716 4.9169 35.4613 5.40974C35.8625 5.89112 36.1662 6.51003 36.3725 7.26648C36.5788 8.02292 36.6819 8.9341 36.6819 10C36.6819 11.0659 36.5788 11.9771 36.3725 12.7335C36.1662 13.49 35.8625 14.1146 35.4613 14.6075C35.0716 15.0888 34.5903 15.4441 34.0172 15.6734C33.4556 15.8911 32.8138 16 32.0917 16H28V4ZM32.0917 14.1261C32.8252 14.1261 33.3926 13.9026 33.7937 13.4556C34.1948 12.9971 34.3954 12.3152 34.3954 11.4097V8.59026C34.3954 7.68481 34.1948 7.0086 33.7937 6.5616C33.3926 6.10315 32.8252 5.87392 32.0917 5.87392H30.149V14.1261H32.0917Z"
+        fill="currentColor"
+      />
+    </svg>
+  )
+}
+
+const CHART_H = 420 // multiple of 12 so the dotted tracks never clip
+
+export function MiniMaxClimb() {
+  const frame = useCurrentFrame()
+  const { fps } = useVideoConfig()
+
+  const grow = (i: number) =>
+    Math.min(
+      1,
+      Math.max(0, spring({ frame: frame - 22 - i * 9, fps, config: { damping: 18, stiffness: 110, mass: 0.6 } })),
+    )
+
+  return (
+    <AbsoluteFill style={{ background: c.bg, color: c.ink, fontFamily: MONO, padding: 72, boxSizing: "border-box" }}>
+      <div style={{ height: "100%", display: "flex", flexDirection: "column" }}>
+        {/* header */}
+        <div style={{ display: "flex", justifyContent: "space-between", alignItems: "center" }}>
+          <DataWordmark height={30} />
+          <div style={{ fontSize: 20, fontWeight: 500, color: c.faint, letterSpacing: 1 }}>JUN 22–28, 2026</div>
+        </div>
+
+        {/* headline (static) */}
+        <div style={{ marginTop: 50 }}>
+          <div style={{ fontSize: 23, fontWeight: 600, color: c.muted, letterSpacing: 2 }}>
+            OPENCODE GO · WEEKLY TOKENS
+          </div>
+          <div
+            style={{ display: "flex", justifyContent: "space-between", alignItems: "baseline", gap: 24, marginTop: 14 }}
+          >
+            <div style={{ fontSize: 62, fontWeight: 600, letterSpacing: -2, lineHeight: 1 }}>MiniMax M3</div>
+            <div style={{ textAlign: "right", flexShrink: 0 }}>
+              <div
+                style={{
+                  fontSize: 84,
+                  fontWeight: 600,
+                  letterSpacing: -2,
+                  lineHeight: 1,
+                  color: c.accent,
+                  fontVariantNumeric: "tabular-nums",
+                }}
+              >
+                +23.2%
+              </div>
+              <div style={{ fontSize: 19, fontWeight: 500, color: c.muted, letterSpacing: 1, marginTop: 6 }}>
+                WEEK OVER WEEK
+              </div>
+            </div>
+          </div>
+        </div>
+
+        {/* column chart */}
+        <div style={{ flex: 1, display: "flex", alignItems: "flex-end", marginTop: 30 }}>
+          <div style={{ width: "100%", display: "flex", alignItems: "flex-end", gap: 30 }}>
+            {weeks.map((w, i) => {
+              const g = grow(i)
+              const h = Math.round((w.t / AXIS_MAX) * CHART_H * g)
+              return (
+                <div key={w.label} style={{ flex: 1, display: "flex", flexDirection: "column", alignItems: "center" }}>
+                  {/* value + bar */}
+                  <div style={{ position: "relative", width: "100%", height: CHART_H }}>
+                    {/* dotted track */}
+                    <div
+                      style={{
+                        position: "absolute",
+                        inset: 0,
+                        background: c.dot,
+                        WebkitMaskImage: DOT_MASK,
+                        maskImage: DOT_MASK,
+                        WebkitMaskSize: "12px 12px",
+                        maskSize: "12px 12px",
+                        WebkitMaskRepeat: "repeat",
+                        maskRepeat: "repeat",
+                        WebkitMaskPosition: "left bottom",
+                        maskPosition: "left bottom",
+                      }}
+                    />
+                    {/* fill */}
+                    <div
+                      style={{
+                        position: "absolute",
+                        left: 0,
+                        right: 0,
+                        bottom: 0,
+                        height: h,
+                        background: w.latest ? c.accent : c.accentDim,
+                        borderTop: w.latest ? `3px solid ${c.accentHi}` : "none",
+                      }}
+                    />
+                    {/* value label */}
+                    <div
+                      style={{
+                        position: "absolute",
+                        left: 0,
+                        right: 0,
+                        bottom: h + 10,
+                        textAlign: "center",
+                        fontSize: 26,
+                        fontWeight: w.latest ? 600 : 500,
+                        color: w.latest ? c.accent : c.muted,
+                        fontVariantNumeric: "tabular-nums",
+                        opacity: interpolate(g, [0.5, 1], [0, 1], {
+                          extrapolateLeft: "clamp",
+                          extrapolateRight: "clamp",
+                        }),
+                      }}
+                    >
+                      {w.t.toFixed(2)}T
+                    </div>
+                  </div>
+                  {/* week label */}
+                  <div
+                    style={{
+                      marginTop: 14,
+                      fontSize: 18,
+                      fontWeight: 500,
+                      color: w.latest ? c.ink : c.faint,
+                    }}
+                  >
+                    {w.label}
+                  </div>
+                </div>
+              )
+            })}
+          </div>
+        </div>
+
+        {/* footer */}
+        <div
+          style={{
+            display: "flex",
+            justifyContent: "space-between",
+            alignItems: "center",
+            marginTop: 22,
+            paddingTop: 22,
+            borderTop: `1px solid ${c.line}`,
+            fontSize: 20,
+            fontWeight: 500,
+          }}
+        >
+          <div style={{ display: "inline-flex", alignItems: "center", gap: 9, color: c.muted }}>
+            <span style={{ width: 13, height: 13, background: c.accent, display: "inline-block" }} />
+            2.56T tokens last week · +482.3B added
+          </div>
+          <div style={{ color: c.ink }}>opencode.ai/data</div>
+        </div>
+      </div>
+    </AbsoluteFill>
+  )
+}

artifacts/glm52-rise-video/src/novel.tsx

@@ -0,0 +1,135 @@
+import React from "react"
+import { AbsoluteFill, Easing, Img, interpolate, staticFile, useCurrentFrame } from "remotion"
+
+const c = {
+  white: "#ffffff",
+  dim: "rgba(255,255,255,0.74)",
+}
+const MONO = '"IBM Plex Mono", ui-monospace, SFMono-Regular, Menlo, Monaco, Consolas, monospace'
+
+// verified: OpenCode Go, week of Jun 22-28, 2026 (2026-W26)
+// 19,642,742,937,105 tokens / 173,651,197 requests = 113,116 tokens/request
+const AVG = 113116
+const K = Math.round(AVG / 1000) // 113
+
+const nf = new Intl.NumberFormat("en-US")
+
+function DataWordmark({ height = 30 }: { height?: number }) {
+  return (
+    <svg width={(height * 66) / 20} height={height} viewBox="0 0 66 20" fill="none" style={{ color: c.white }}>
+      <path opacity="0.35" d="M12 16H4V8H12V16Z" fill="currentColor" />
+      <path d="M12 4H4V16H12V4ZM16 20H0V0H16V20Z" fill="currentColor" />
+      <path
+        d="M63.3543 16L62.5119 12.8711H58.6437L57.8013 16H55.7383L59.2454 4H61.9618L65.4689 16H63.3543ZM61.0678 7.851L60.6896 5.94269H60.4489L60.0707 7.851L59.1595 11.1347H61.9962L61.0678 7.851Z"
+        fill="currentColor"
+      />
+      <path d="M52.5951 5.87392V16H50.4461V5.87392H47.4375V4H55.6209V5.87392H52.5951Z" fill="currentColor" />
+      <path
+        d="M45.2059 16L44.3635 12.8711H40.4953L39.6529 16H37.5898L41.097 4H43.8133L47.3205 16H45.2059ZM42.9194 7.851L42.5411 5.94269H42.3004L41.9222 7.851L41.011 11.1347H43.8477L42.9194 7.851Z"
+        fill="currentColor"
+      />
+      <path
+        d="M28 4H32.0917C32.8138 4 33.4556 4.11461 34.0172 4.34384C34.5903 4.5616 35.0716 4.9169 35.4613 5.40974C35.8625 5.89112 36.1662 6.51003 36.3725 7.26648C36.5788 8.02292 36.6819 8.9341 36.6819 10C36.6819 11.0659 36.5788 11.9771 36.3725 12.7335C36.1662 13.49 35.8625 14.1146 35.4613 14.6075C35.0716 15.0888 34.5903 15.4441 34.0172 15.6734C33.4556 15.8911 32.8138 16 32.0917 16H28V4ZM32.0917 14.1261C32.8252 14.1261 33.3926 13.9026 33.7937 13.4556C34.1948 12.9971 34.3954 12.3152 34.3954 11.4097V8.59026C34.3954 7.68481 34.1948 7.0086 33.7937 6.5616C33.3926 6.10315 32.8252 5.87392 32.0917 5.87392H30.149V14.1261H32.0917Z"
+        fill="currentColor"
+      />
+    </svg>
+  )
+}
+
+export function NovelTokens() {
+  const frame = useCurrentFrame()
+
+  const k = Math.round(
+    K *
+      interpolate(frame, [18, 92], [0, 1], {
+        extrapolateLeft: "clamp",
+        extrapolateRight: "clamp",
+        easing: Easing.out(Easing.cubic),
+      }),
+  )
+
+  const zoom = interpolate(frame, [0, 150], [1.06, 1.12], {
+    extrapolateRight: "clamp",
+    easing: Easing.inOut(Easing.quad),
+  })
+
+  return (
+    <AbsoluteFill style={{ background: "#0c0c0c", overflow: "hidden" }}>
+      <Img
+        src={staticFile("book.jpg")}
+        style={{
+          position: "absolute",
+          width: "100%",
+          height: "100%",
+          objectFit: "cover",
+          objectPosition: "center 34%",
+          transform: `scale(${zoom})`,
+          transformOrigin: "center 30%",
+        }}
+      />
+
+      {/* legibility scrims */}
+      <div
+        style={{
+          position: "absolute",
+          inset: 0,
+          background:
+            "linear-gradient(to bottom, rgba(0,0,0,0.55) 0%, rgba(0,0,0,0) 20%, rgba(0,0,0,0.1) 44%, rgba(0,0,0,0.86) 100%)",
+        }}
+      />
+
+      <div
+        style={{
+          position: "absolute",
+          inset: 0,
+          boxSizing: "border-box",
+          padding: 64,
+          color: c.white,
+          fontFamily: MONO,
+          display: "flex",
+          flexDirection: "column",
+          justifyContent: "space-between",
+        }}
+      >
+        {/* header */}
+        <div style={{ display: "flex", justifyContent: "space-between", alignItems: "center" }}>
+          <DataWordmark height={30} />
+          <div style={{ fontSize: 20, fontWeight: 500, color: c.dim, letterSpacing: 1 }}>JUN 22–28, 2026</div>
+        </div>
+
+        {/* bottom block */}
+        <div>
+          <div style={{ fontSize: 23, fontWeight: 600, color: c.dim, letterSpacing: 2, marginBottom: 8 }}>
+            OPENCODE GO · LAST WEEK
+          </div>
+          <div
+            style={{
+              fontSize: 168,
+              fontWeight: 600,
+              lineHeight: 0.92,
+              letterSpacing: -5,
+              fontVariantNumeric: "tabular-nums",
+            }}
+          >
+            {k}K
+          </div>
+          <div style={{ fontSize: 50, fontWeight: 600, letterSpacing: -1, marginTop: 4 }}>tokens per request</div>
+
+          <div
+            style={{
+              display: "flex",
+              justifyContent: "space-between",
+              alignItems: "center",
+              marginTop: 30,
+              fontSize: 20,
+              fontWeight: 500,
+            }}
+          >
+            <div style={{ color: c.dim }}>{nf.format(AVG)} tokens / request · last week</div>
+            <div style={{ color: c.white }}>opencode.ai/data</div>
+          </div>
+        </div>
+      </div>
+    </AbsoluteFill>
+  )
+}

artifacts/glm52-rise-video/src/sheep.tsx

@@ -0,0 +1,139 @@
+import React from "react"
+import { AbsoluteFill, Easing, Img, interpolate, staticFile, useCurrentFrame } from "remotion"
+
+const c = {
+  white: "#ffffff",
+  dim: "rgba(255,255,255,0.72)",
+  faint: "rgba(255,255,255,0.55)",
+}
+const MONO = '"IBM Plex Mono", ui-monospace, SFMono-Regular, Menlo, Monaco, Consolas, monospace'
+
+// verified: NZ OpenCode Go, week of Jun 22-28, 2026 (2026-W26)
+const TOKENS = 40_915_594_381 // 40.9B
+const SHEEP = 23_600_000 // 23.6M
+const PER_SHEEP = Math.round(TOKENS / SHEEP) // 1,734
+const nf = new Intl.NumberFormat("en-US")
+
+// the correct opencode "DATA" wordmark (white, over photo)
+function DataWordmark({ height = 30 }: { height?: number }) {
+  return (
+    <svg width={(height * 66) / 20} height={height} viewBox="0 0 66 20" fill="none" style={{ color: c.white }}>
+      <path opacity="0.35" d="M12 16H4V8H12V16Z" fill="currentColor" />
+      <path d="M12 4H4V16H12V4ZM16 20H0V0H16V20Z" fill="currentColor" />
+      <path
+        d="M63.3543 16L62.5119 12.8711H58.6437L57.8013 16H55.7383L59.2454 4H61.9618L65.4689 16H63.3543ZM61.0678 7.851L60.6896 5.94269H60.4489L60.0707 7.851L59.1595 11.1347H61.9962L61.0678 7.851Z"
+        fill="currentColor"
+      />
+      <path d="M52.5951 5.87392V16H50.4461V5.87392H47.4375V4H55.6209V5.87392H52.5951Z" fill="currentColor" />
+      <path
+        d="M45.2059 16L44.3635 12.8711H40.4953L39.6529 16H37.5898L41.097 4H43.8133L47.3205 16H45.2059ZM42.9194 7.851L42.5411 5.94269H42.3004L41.9222 7.851L41.011 11.1347H43.8477L42.9194 7.851Z"
+        fill="currentColor"
+      />
+      <path
+        d="M28 4H32.0917C32.8138 4 33.4556 4.11461 34.0172 4.34384C34.5903 4.5616 35.0716 4.9169 35.4613 5.40974C35.8625 5.89112 36.1662 6.51003 36.3725 7.26648C36.5788 8.02292 36.6819 8.9341 36.6819 10C36.6819 11.0659 36.5788 11.9771 36.3725 12.7335C36.1662 13.49 35.8625 14.1146 35.4613 14.6075C35.0716 15.0888 34.5903 15.4441 34.0172 15.6734C33.4556 15.8911 32.8138 16 32.0917 16H28V4ZM32.0917 14.1261C32.8252 14.1261 33.3926 13.9026 33.7937 13.4556C34.1948 12.9971 34.3954 12.3152 34.3954 11.4097V8.59026C34.3954 7.68481 34.1948 7.0086 33.7937 6.5616C33.3926 6.10315 32.8252 5.87392 32.0917 5.87392H30.149V14.1261H32.0917Z"
+        fill="currentColor"
+      />
+    </svg>
+  )
+}
+
+export function NZSheep() {
+  const frame = useCurrentFrame()
+
+  const count = Math.round(
+    PER_SHEEP *
+      interpolate(frame, [18, 90], [0, 1], {
+        extrapolateLeft: "clamp",
+        extrapolateRight: "clamp",
+        easing: Easing.out(Easing.cubic),
+      }),
+  )
+
+  // slow Ken Burns push-in (scale up only — never reveals an edge)
+  const zoom = interpolate(frame, [0, 150], [1.06, 1.12], {
+    extrapolateRight: "clamp",
+    easing: Easing.inOut(Easing.quad),
+  })
+
+  return (
+    <AbsoluteFill style={{ background: "#0c0c0c", overflow: "hidden" }}>
+      {/* the sheep, staring */}
+      <Img
+        src={staticFile("sheep.jpg")}
+        style={{
+          position: "absolute",
+          width: "100%",
+          height: "100%",
+          objectFit: "cover",
+          objectPosition: "center 38%",
+          transform: `scale(${zoom})`,
+          transformOrigin: "center 35%",
+        }}
+      />
+
+      {/* legibility scrims */}
+      <div
+        style={{
+          position: "absolute",
+          inset: 0,
+          background:
+            "linear-gradient(to bottom, rgba(0,0,0,0.5) 0%, rgba(0,0,0,0) 22%, rgba(0,0,0,0) 48%, rgba(0,0,0,0.78) 100%)",
+        }}
+      />
+
+      {/* content */}
+      <div
+        style={{
+          position: "absolute",
+          inset: 0,
+          boxSizing: "border-box",
+          padding: 64,
+          color: c.white,
+          fontFamily: MONO,
+          display: "flex",
+          flexDirection: "column",
+          justifyContent: "space-between",
+        }}
+      >
+        {/* header */}
+        <div style={{ display: "flex", justifyContent: "space-between", alignItems: "center" }}>
+          <DataWordmark height={30} />
+          <div style={{ fontSize: 20, fontWeight: 500, color: c.dim, letterSpacing: 1 }}>JUN 22–28, 2026</div>
+        </div>
+
+        {/* bottom block */}
+        <div>
+          <div style={{ fontSize: 23, fontWeight: 600, color: c.dim, letterSpacing: 2, marginBottom: 8 }}>
+            OPENCODE GO · NEW ZEALAND
+          </div>
+          <div
+            style={{
+              fontSize: 168,
+              fontWeight: 600,
+              lineHeight: 0.92,
+              letterSpacing: -5,
+              fontVariantNumeric: "tabular-nums",
+            }}
+          >
+            {nf.format(count)}
+          </div>
+          <div style={{ fontSize: 50, fontWeight: 600, letterSpacing: -1, marginTop: 4 }}>tokens per sheep</div>
+
+          <div
+            style={{
+              display: "flex",
+              justifyContent: "space-between",
+              alignItems: "center",
+              marginTop: 34,
+              fontSize: 20,
+              fontWeight: 500,
+            }}
+          >
+            <div style={{ color: c.dim }}>40.9B tokens ÷ 23.6M sheep · last week</div>
+            <div style={{ color: c.white }}>opencode.ai/data</div>
+          </div>
+        </div>
+      </div>
+    </AbsoluteFill>
+  )
+}

artifacts/glm52-rise-video/src/video.tsx

@@ -0,0 +1,254 @@
+import React from "react"
+import { AbsoluteFill, Easing, interpolate, useCurrentFrame, useVideoConfig } from "remotion"
+import { days, launchIndex, glmWeekTokensT, segments } from "./data"
+
+// stats.opencode.ai design tokens (light theme)
+const c = {
+  bg: "#ffffff",
+  ink: "#161616",
+  muted: "#5c5c5c",
+  faint: "#808080",
+  line: "#e6e6e6",
+  dot: "#ededed",
+  accent: "#3b5cf6",
+  accentHi: "#5b78ff",
+}
+
+const MONO = '"IBM Plex Mono", ui-monospace, SFMono-Regular, Menlo, Monaco, Consolas, monospace'
+const W = 1080
+
+const DOT_MASK =
+  "url(\"data:image/svg+xml,%3Csvg viewBox='0 0 6 6' xmlns='http://www.w3.org/2000/svg'%3E%3Cpath d='M0 0H2V2H0V0Z' fill='black'/%3E%3C/svg%3E\")"
+
+const field = segments.filter((s) => !s.hero)
+const glmColor = segments.find((s) => s.hero)!.color
+
+const clamp = (v: number, lo: number, hi: number) => Math.min(hi, Math.max(lo, v))
+
+// the correct opencode "DATA" wordmark (from stats.opencode.ai header)
+function DataWordmark({ height = 30, color = c.ink }: { height?: number; color?: string }) {
+  return (
+    <svg width={(height * 66) / 20} height={height} viewBox="0 0 66 20" fill="none" style={{ color }}>
+      <path opacity="0.2" d="M12 16H4V8H12V16Z" fill="currentColor" />
+      <path d="M12 4H4V16H12V4ZM16 20H0V0H16V20Z" fill="currentColor" />
+      <path
+        d="M63.3543 16L62.5119 12.8711H58.6437L57.8013 16H55.7383L59.2454 4H61.9618L65.4689 16H63.3543ZM61.0678 7.851L60.6896 5.94269H60.4489L60.0707 7.851L59.1595 11.1347H61.9962L61.0678 7.851Z"
+        fill="currentColor"
+      />
+      <path d="M52.5951 5.87392V16H50.4461V5.87392H47.4375V4H55.6209V5.87392H52.5951Z" fill="currentColor" />
+      <path
+        d="M45.2059 16L44.3635 12.8711H40.4953L39.6529 16H37.5898L41.097 4H43.8133L47.3205 16H45.2059ZM42.9194 7.851L42.5411 5.94269H42.3004L41.9222 7.851L41.011 11.1347H43.8477L42.9194 7.851Z"
+        fill="currentColor"
+      />
+      <path
+        d="M28 4H32.0917C32.8138 4 33.4556 4.11461 34.0172 4.34384C34.5903 4.5616 35.0716 4.9169 35.4613 5.40974C35.8625 5.89112 36.1662 6.51003 36.3725 7.26648C36.5788 8.02292 36.6819 8.9341 36.6819 10C36.6819 11.0659 36.5788 11.9771 36.3725 12.7335C36.1662 13.49 35.8625 14.1146 35.4613 14.6075C35.0716 15.0888 34.5903 15.4441 34.0172 15.6734C33.4556 15.8911 32.8138 16 32.0917 16H28V4ZM32.0917 14.1261C32.8252 14.1261 33.3926 13.9026 33.7937 13.4556C34.1948 12.9971 34.3954 12.3152 34.3954 11.4097V8.59026C34.3954 7.68481 34.1948 7.0086 33.7937 6.5616C33.3926 6.10315 32.8252 5.87392 32.0917 5.87392H30.149V14.1261H32.0917Z"
+        fill="currentColor"
+      />
+    </svg>
+  )
+}
+
+export function GLM52Rise() {
+  const frame = useCurrentFrame()
+  const { fps } = useVideoConfig()
+
+  // ---------- virtual camera ----------
+  // open zoomed-in on the field, pan right while the blue fills, then pull back to reveal.
+  const K = [0, 32, 150, 206, 240]
+  const ease = Easing.inOut(Easing.cubic)
+  const opt = { extrapolateLeft: "clamp" as const, extrapolateRight: "clamp" as const, easing: ease }
+  const s = interpolate(frame, K, [1.82, 1.72, 1.72, 1.0, 1.0], opt)
+  let fx = interpolate(frame, K, [420, 438, 760, 540, 540], opt)
+  let fy = interpolate(frame, K, [664, 664, 664, 540, 540], opt)
+  // keep the framing inside the 1080 canvas so edges never reveal black
+  fx = clamp(fx, 540 / s, W - 540 / s)
+  fy = clamp(fy, 540 / s, W - 540 / s)
+  const camera = `translate(${540 - fx * s}px, ${540 - fy * s}px) scale(${s})`
+
+  // ---------- blue sweep (synced to the pan) ----------
+  const p = interpolate(frame, [32, 150], [0, 1], { extrapolateLeft: "clamp", extrapolateRight: "clamp", easing: ease })
+  const revealAmount = p * (days.length - launchIndex) + 0.35
+  const fillOf = (i: number) => clamp(revealAmount - (i - launchIndex), 0, 1)
+
+  // token number climbs as the camera pulls back and the headline re-enters frame
+  const tokensT =
+    glmWeekTokensT *
+    interpolate(frame, [150, 202], [0, 1], {
+      extrapolateLeft: "clamp",
+      extrapolateRight: "clamp",
+      easing: Easing.out(Easing.cubic),
+    })
+
+  // chart geometry
+  const chartH = 440
+  const chartW = 936
+  const gap = 14
+  const EXAGGERATE = 2.876 // broken y-axis: GLM-5.2 magnified ~2.9x for emphasis
+
+  return (
+    <AbsoluteFill style={{ background: c.bg, overflow: "hidden" }}>
+      <div
+        style={{
+          position: "absolute",
+          width: W,
+          height: W,
+          background: c.bg,
+          transformOrigin: "0 0",
+          transform: camera,
+        }}
+      >
+        <div
+          style={{
+            width: W,
+            height: W,
+            boxSizing: "border-box",
+            padding: 72,
+            color: c.ink,
+            fontFamily: MONO,
+            display: "flex",
+            flexDirection: "column",
+          }}
+        >
+          {/* header */}
+          <div style={{ display: "flex", justifyContent: "space-between", alignItems: "center" }}>
+            <DataWordmark height={30} />
+            <div style={{ fontSize: 20, fontWeight: 500, color: c.faint, letterSpacing: 1 }}>JUN 12–25, 2026</div>
+          </div>
+
+          {/* headline (static) */}
+          <div style={{ marginTop: 52 }}>
+            <div style={{ fontSize: 92, fontWeight: 600, lineHeight: 0.98, letterSpacing: -2 }}>
+              GLM-5.2 <span style={{ color: c.accent }}>broke out</span>
+            </div>
+            <div style={{ marginTop: 22, fontSize: 30, fontWeight: 500, color: c.muted }}>
+              From 0 to <span style={{ color: c.ink }}>{tokensT.toFixed(2)}T tokens</span> in a week.
+            </div>
+          </div>
+
+          {/* stacked chart */}
+          <div style={{ flex: 1, display: "flex", alignItems: "flex-end", marginTop: 40 }}>
+            <div
+              style={{
+                position: "relative",
+                width: chartW,
+                height: chartH,
+                margin: "0 auto",
+                borderBottom: `2px solid ${c.ink}`,
+                boxSizing: "border-box",
+              }}
+            >
+              {/* faint dotted backdrop */}
+              <div
+                style={{
+                  position: "absolute",
+                  left: -8,
+                  right: -8,
+                  top: -8,
+                  bottom: 0,
+                  background: c.dot,
+                  WebkitMaskImage: DOT_MASK,
+                  maskImage: DOT_MASK,
+                  WebkitMaskSize: "12px 12px",
+                  maskSize: "12px 12px",
+                  WebkitMaskRepeat: "repeat",
+                  maskRepeat: "repeat",
+                }}
+              />
+
+              {/* columns */}
+              <div style={{ position: "absolute", inset: 0, display: "flex", gap, alignItems: "flex-end" }}>
+                {days.map((d, i) => {
+                  const glmShare = d.glm / d.total
+                  const blueH = Math.round(glmShare * EXAGGERATE * chartH)
+                  const filled = Math.round(blueH * fillOf(i))
+                  const slotGap = filled > 2 ? 5 : 0
+                  const fieldH = chartH - filled - slotGap
+                  const fieldTotal = d.dsf + d.dsp + d.mm + d.others
+                  return (
+                    <div key={i} style={{ position: "relative", flex: 1, height: chartH }}>
+                      {/* gray field of other models (already in place) */}
+                      <div
+                        style={{
+                          position: "absolute",
+                          top: 0,
+                          left: 0,
+                          right: 0,
+                          height: fieldH,
+                          display: "flex",
+                          flexDirection: "column-reverse",
+                        }}
+                      >
+                        {field.map((seg) => (
+                          <div
+                            key={seg.key}
+                            style={{
+                              height: Math.round(((d[seg.key as keyof typeof d] as number) / fieldTotal) * fieldH),
+                              background: seg.color,
+                              borderTop: `2px solid ${c.bg}`,
+                            }}
+                          />
+                        ))}
+                      </div>
+                      {/* GLM-5.2, animates in */}
+                      {filled > 2 && (
+                        <div
+                          style={{
+                            position: "absolute",
+                            left: 0,
+                            right: 0,
+                            bottom: 0,
+                            height: filled,
+                            background: glmColor,
+                            borderTop: `2px solid ${c.accentHi}`,
+                          }}
+                        />
+                      )}
+                    </div>
+                  )
+                })}
+              </div>
+            </div>
+          </div>
+
+          {/* day axis */}
+          <div style={{ display: "flex", gap, width: chartW, margin: "14px auto 0" }}>
+            {days.map((d, i) => (
+              <div
+                key={i}
+                style={{
+                  flex: 1,
+                  textAlign: "center",
+                  fontSize: 15,
+                  fontWeight: 500,
+                  color: i === days.length - 1 ? c.ink : c.faint,
+                }}
+              >
+                {i === 0 || i === launchIndex || i === days.length - 1 ? d.date : ""}
+              </div>
+            ))}
+          </div>
+
+          {/* footer */}
+          <div
+            style={{
+              display: "flex",
+              justifyContent: "space-between",
+              alignItems: "center",
+              marginTop: 28,
+              paddingTop: 22,
+              borderTop: `1px solid ${c.line}`,
+              fontSize: 20,
+              fontWeight: 500,
+            }}
+          >
+            <div style={{ display: "inline-flex", alignItems: "center", gap: 9, color: c.muted }}>
+              <span style={{ width: 13, height: 13, background: c.accent, display: "inline-block" }} />
+              GLM-5.2
+            </div>
+            <div style={{ color: c.ink }}>opencode.ai/data</div>
+          </div>
+        </div>
+      </div>
+    </AbsoluteFill>
+  )
+}

bunfig.toml

@@ -2,7 +2,7 @@
 exact = true
 # Only install newly resolved package versions published at least 3 days ago.
 minimumReleaseAge = 259200
-minimumReleaseAgeExcludes = ["@opentui/core", "@opentui/core-darwin-arm64", "@opentui/core-darwin-x64", "@opentui/core-linux-arm64", "@opentui/core-linux-x64", "@opentui/core-win32-arm64", "@opentui/core-win32-x64", "@opentui/keymap", "@opentui/solid", "gitlab-ai-provider"]
+minimumReleaseAgeExcludes = ["@ai-sdk/amazon-bedrock", "@ai-sdk/anthropic", "@opentui/core", "@opentui/core-darwin-arm64", "@opentui/core-darwin-x64", "@opentui/core-linux-arm64", "@opentui/core-linux-arm64-musl", "@opentui/core-linux-x64", "@opentui/core-linux-x64-musl", "@opentui/core-win32-arm64", "@opentui/core-win32-x64", "@opentui/keymap", "@opentui/solid", "opentui-spinner", "gitlab-ai-provider", "opencode-gitlab-auth", "@ff-labs/fff-node", "@ff-labs/fff-bun", "@ff-labs/fff-bin-darwin-arm64", "@ff-labs/fff-bin-darwin-x64", "@ff-labs/fff-bin-linux-arm64-gnu", "@ff-labs/fff-bin-linux-arm64-musl", "@ff-labs/fff-bin-linux-x64-gnu", "@ff-labs/fff-bin-linux-x64-musl", "@ff-labs/fff-bin-win32-arm64", "@ff-labs/fff-bin-win32-x64", "@pierre/diffs", "@pierre/theming", "app-builder-lib", "dmg-builder", "electron-builder", "electron-publish"]
 
 [test]
 root = "./do-not-run-tests-from-root"

docs/design/service-lifecycle.md

@@ -0,0 +1,685 @@
+# Service Lifecycle: Election, Restart, and Reconnect
+
+Status: in progress
+
+Incident: [#36688](https://github.com/anomalyco/opencode/issues/36688)
+
+## Summary
+
+The managed V2 service keeps its current update policy: the background updater
+may install a new package, but only a freshly launched TUI activates that update
+after finding an older running service. Existing TUIs never replace a service;
+they only reconnect.
+
+The restart path changes in three places:
+
+1. A process-held OS lock, not the HTTP port or registration file, elects
+   exactly one server owner for its lifetime.
+2. The elected process binds and registers a minimal lifecycle surface before
+   it initializes the application, so clients can distinguish a slow winner
+   from an absent server.
+3. TUIs rediscover and reconnect indefinitely. Transport loss is never a
+   terminal error by itself.
+
+Several clients may spawn small contenders during a restart. This is safe and
+intentional: one contender acquires the lock and initializes, while every loser
+exits before expensive server boot. The design does not require clients to
+agree on a single initiator.
+
+This proposal does not introduce a supervisor process, warm candidate server,
+protocol negotiation, idle background restart, or general execution-recovery
+framework.
+
+## Architecture at a Glance
+
+```text
+                       ╭───────────────────╮
+                       │ CLI ServiceConfig │
+                       ╰─────────┬─────────╯
+                                 │
+                                 ▼
+                     ╭──────────────────────╮
+                     │ CLI ServerConnection │
+                     ╰───────────┬──────────╯
+              ╭──────────────────╰───────────────────╮
+              ▼                                      ▼
+╭──────────────────────────╮            ╭─────────────────────────╮
+│ Client Service lifecycle │            │ CLI runPromiseWith seam │
+╰─────────────┬────────────╯            ╰─────────────┬───────────╯
+              ╰─────╮                                 │
+                    ▼                                 ▼
+     ╭────────────────────────────╮            ╭─────────────╮
+     │ Background service process │            │ TUI / Solid │
+     ╰──────────────┬─────────────╯            ╰──────┬──────╯
+                    │                                 │
+                    ╰────────────◀────────────────────╯
+                     ╭───────────────────────╮
+                     │ Server HTTP transport │
+                     ╰───────────┬───────────╯
+                                 │
+                                 ▼
+                       ╭──────────────────╮
+                       │ Core application │
+                       ╰──────────────────╯
+```
+
+| Owner                                            | Responsibility                                                                                      |
+| ------------------------------------------------ | --------------------------------------------------------------------------------------------------- |
+| `packages/client/src/effect/service.ts`          | Effect-native discovery, start, and stop lifecycle operations                                       |
+| `packages/cli/src/services/service-config.ts`    | CLI registration path, installed version, and daemon command                                        |
+| `packages/cli/src/services/server-connection.ts` | Resolve an endpoint and, only for the shared service, grouped reconnect and restart Effects         |
+| `packages/cli/src/server-process.ts`             | Daemon election, registration, and server process boot                                              |
+| `packages/server/src/process.ts`                 | HTTP lifecycle shell and application transport                                                      |
+| `packages/core`                                  | Application behavior behind the transport                                                           |
+| CLI default handler                              | Convert lifecycle Effects with the outer `FileSystem` context and pass grouped Promise capabilities |
+| `packages/tui` Solid client context              | Own event-stream reconnect, endpoint replacement, status, and user-triggered restart UI             |
+
+## Implementation Status
+
+| Area                      | State                                                                 |
+| ------------------------- | --------------------------------------------------------------------- |
+| Lifetime ownership        | Implemented on this branch with a scoped OS lock                      |
+| Contender behavior        | Implemented; losers exit before the server module is imported         |
+| Registration repair       | Implemented; the owner reasserts deleted or corrupt discovery         |
+| Channel isolation         | Implemented with no-clobber migration for legacy preview discovery    |
+| Client startup waiting    | Implemented; slow winners are not killed and waiting is indefinite    |
+| Lifecycle shell           | Implemented; the owner binds and registers before application boot    |
+| Failed-state latching     | Implemented; deterministic boot failure stays bound and actionable    |
+| Recovery diagnostics      | Implemented; the TUI shows status instead of transport internals      |
+| Cross-platform validation | macOS runtime verified; Linux and Windows run in the unit-test matrix |
+
+## Context
+
+The V2 CLI runs a shared managed service that owns Sessions, location graphs,
+plugins, permissions, and tool execution. The service updater can replace the
+installed package while the current process continues running the old image.
+A later TUI launch then detects the version mismatch and replaces the service.
+
+Incident #36688 showed four failures in that replacement path:
+
+- Multiple TUIs spawned heavyweight server contenders.
+- A winner remained unobservable while it cold-booted, so another wave treated
+  it as absent and displaced it.
+- A fresh TUI exhausted its reconnect budget and crashed with an unhandled
+  transport defect.
+- A losing contender remained alive and consumed about 1 GB of RSS.
+
+The `origin/v2` baseline serializes service startup with `EffectFlock`. A
+contender acquires a three-second heartbeat lease, checks whether another
+service became discoverable, and only the winner crosses the application-boot
+boundary. This already prevents simultaneous heavy boots and makes startup
+losers exit.
+
+The lease is released immediately after registration, however, so it is not
+lifetime ownership. Registration then reverts to last-writer-wins authority: a
+deleted or corrupt registration can admit a second boot, a displaced server
+terminates itself through its 10-second registration self-check, and a stalled
+lease holder can be displaced after the three-second service staleness timeout.
+
+`Flock` and `EffectFlock` live in `packages/core/src/util` and are also used for
+config writes, MCP auth, npm installs, and repository caching. Despite the
+name, the primitive is an atomic-mkdir lease with heartbeat and staleness
+takeover, not an OS-held lock. It remains appropriate for bounded critical
+sections, including today's startup fence, but is not lifetime service
+ownership.
+
+The current implementation also mixes three different concepts:
+
+- **Ownership:** which process is allowed to be the managed server.
+- **Discovery:** where clients can reach that process.
+- **Lifecycle:** whether that process is starting, ready, stopping, or failed.
+
+This design gives each concept one authority.
+
+```definitions
+[
+  {
+    "term": "Owner",
+    "definition": "The one process holding the process-held OS service lock."
+  },
+  {
+    "term": "Contender",
+    "definition": "A small serve process attempting to acquire the service lock. It must not initialize the application before winning."
+  },
+  {
+    "term": "Registration",
+    "definition": "An atomic discovery record containing the elected owner's identity and endpoint. Registration never grants ownership."
+  },
+  {
+    "term": "Lifecycle shell",
+    "definition": "The minimal HTTP surface bound by the elected process before application initialization. It serves health and retryable startup responses."
+  },
+  {
+    "term": "Application",
+    "definition": "The full server routes and global or location-scoped modules used for normal OpenCode work."
+  }
+]
+```
+
+## Goals
+
+- At most one process initializes and serves the managed application.
+- Losing contenders exit before database, route, plugin, MCP, or location boot.
+- A slow winner becomes observable before expensive initialization.
+- Existing and freshly launched TUIs survive retryable service unavailability.
+- Reconnect follows service state instead of displaying retry counts or raw
+  transport failures.
+- Version-mismatch replacement remains triggered by a fresh TUI launch.
+- A stale or malformed registration cannot create a second owner.
+- An unresponsive owner is never killed automatically by an arbitrary TUI.
+- Every spawned contender has a bounded path to ownership or exit.
+
+## Non-goals
+
+- Restarting automatically when a background update finds an idle window.
+- Running old and candidate application servers concurrently.
+- Adding a permanent steward, proxy, or supervisor process.
+- Zero-downtime worker handoff or automatic rollback.
+- Application protocol negotiation or automatic TUI self-restart.
+- General hard-crash recovery for active Sessions.
+- Defining recovery semantics for provider attempts, tools, shells, sub-agents,
+  permissions, questions, or background jobs.
+- Automatically killing a frozen owner.
+- Bounding concurrent location cold boots after clients reconnect.
+- Multi-machine or clustered service placement.
+
+## Invariants
+
+1. **The service lock is ownership.** Exactly one process may hold the OS lock
+   for one installation channel and service profile.
+2. **Ownership precedes boot.** A contender performs no expensive application
+   initialization before it acquires the lock.
+3. **Ownership lasts for the process lifetime.** The owner holds an open lock
+   handle until the managed server exits. The OS releases it on process death
+   without a cleanup callback.
+4. **The port is transport, not election.** The owner may select a dynamic port
+   after acquiring the lock.
+5. **Registration is discovery, not election.** Deleting, corrupting, or
+   replacing registration does not invalidate a live owner's lock.
+6. **Only a fresh launch enforces package version.** Existing TUIs reconnect to
+   the current owner without initiating version replacement.
+7. **Transport loss is retryable.** It never terminates a TUI without a separate
+   diagnosed, non-retryable cause.
+8. **Clients do not kill an unresponsive owner automatically.** Destructive
+   recovery requires the explicit `service restart` command.
+9. **Lifecycle does not promise execution semantics.** Graceful replacement
+   invokes Session suspension and resumption hooks, but tool-level continuity
+   belongs to a separate design.
+
+## System Model
+
+```text
+╭───────────────────────╮                              ╭──────────────────────────────╮
+│ Fresh or existing TUI │                              │ Process-held OS service lock │
+╰───────────┬───────────╯                              ╰───────────────┬──────────────╯
+            ╰─────┬ normal requests  observe ───────────────────────╮  │
+                  │ discover               │                        ├──╯ authorizes one owner
+                  ▼                        │                        ▼
+        ╭───────────────────╮              │               ╭─────────────────╮
+        │ Registration file │              │               │ Lifecycle shell │
+        ╰───────────────────╯              │               ╰────────┬────────╯
+                                           │                        │
+                                           ├────────────────────────╯
+                                           ▼
+                               ╭──────────────────────╮
+                               │ OpenCode application │
+                               ╰──────────────────────╯
+```
+
+The lifecycle shell and application run in the same process. The distinction is
+initialization order and responsibility, not process topology.
+
+## Service Status
+
+The server reports one small status value:
+
+```typescript
+type ServiceStatus =
+  | {
+      type: "starting"
+    }
+  | {
+      type: "ready"
+    }
+  | {
+      type: "stopping"
+      targetVersion?: string
+    }
+  | {
+      type: "failed"
+      message: string
+      action: string
+    }
+```
+
+The client adds only the discovery states needed by callers:
+
+```typescript
+type Status = { type: "missing" } | { type: "unreachable" } | { type: "unresponsive" } | ServiceStatus
+```
+
+The health response retains the existing fields for old clients and adds the
+status discriminant:
+
+```typescript
+type ServiceHealth = {
+  healthy: true
+  version: string
+  pid: number
+  instanceID: string
+  status: ServiceStatus
+}
+```
+
+`healthy: true` means the registered lifecycle shell is responding and its
+identity matches registration. New clients use `status.type === "ready"` as
+the application-readiness signal.
+
+During `starting` or `stopping`, application requests are not held in memory.
+They receive an immediate retryable response:
+
+```http
+HTTP/1.1 503 Service Unavailable
+Retry-After: 1
+Content-Type: application/json
+
+{"code":"service_starting"}
+```
+
+`stopping` uses `service_stopping`. A failed application boot uses
+`service_failed` and includes a safe diagnostic message.
+
+A failed owner remains bound and keeps holding the service lock. Exiting on
+failure would let every waiting client's `ensureRunning` loop elect a new
+contender that repeats the same heavy failing boot, so staying bound turns a
+deterministic boot failure into one observable `failed` state instead of a
+client-driven respawn loop. Recovery still works: a fresh launch observes the
+failed instance through the stop path, and explicit `service restart` replaces
+it.
+
+## Registration Contract
+
+Registration contains only discovery identity:
+
+```typescript
+type ServiceRegistration = {
+  schema: 1
+  instanceID: string
+  version: string
+  url: string
+  pid: number
+}
+```
+
+Authentication continues to use the existing private service credential
+storage. The registration schema does not change that policy.
+
+The owner writes registration only after the lifecycle shell has bound:
+
+1. Bind the lifecycle shell.
+2. Write a temporary registration file with mode `0600`.
+3. Atomically rename it over the old registration.
+4. Serve lifecycle health as `starting`.
+
+On shutdown, the owner removes registration only if the current file still has
+its `instanceID`. An old finalizer can never remove a successor's registration.
+
+While running, the owner periodically asserts its registration. Because the
+lock guarantees exactly one live owner, any registration that does not name the
+owner is stale or corrupt, and the owner rewrites it. A deleted or clobbered
+registration therefore heals within one assertion interval instead of leaving
+clients waiting on absent discovery. This inverts today's self-check loop,
+which terminates the displaced process instead of repairing discovery.
+
+Legacy registration shapes are decoded by a compatibility adapter. The new
+domain type does not make fields optional to represent old formats.
+
+## Election
+
+This design promotes today's startup fence into lifetime ownership.
+Last-writer-wins registration is replaced by a process-held OS lock that is
+acquired before any expensive boot work and held for the entire service
+lifetime.
+
+A heartbeat-and-staleness lease, including the existing `Flock` utility, is not
+sufficient for service ownership: the service configures a three-second stale
+timeout, after which its lock can be broken and recreated. An event-loop stall,
+a suspended machine, or a debugger pause can therefore make a live owner appear
+stale and allow a contender to displace it. Service ownership requires a
+process-held OS lock: `flock` on Unix and an exclusively bound named pipe on
+Windows. It cannot be broken because a heartbeat exceeded a timeout. Process
+death releases the lock through the OS.
+
+Neither Bun nor Node exposes `flock` directly, the existing `Flock` utility is
+an mkdir-plus-heartbeat lease rather than an OS-held lock, and the common
+lockfile packages are staleness-based leases as well. The platform layer uses
+`bun:ffi` to call `flock` on POSIX and Node's named-pipe server support on
+Windows, where Bun FFI is not available on every shipped architecture. It lives
+alongside the existing utility in `packages/core/src/util`. This primitive is
+the foundation of the design, so the delivery sequence spikes it first.
+
+```text
+Contender           Lock            Lifecycle              Application
+    │                 │                 │                       │
+    ├─ try acquire ───▶                 │                       │
+    │                 │                 │                       │
+ ╭─ alt: lock held ────────────────────────────────────────────────╮
+ │  │                 │                 │                       │  │
+ │  ◀─ busy ──────────┤                 │                       │  │
+ │  │                 │                 │                       │  │
+ │  ├─────────╮       │                 │                       │  │
+ │  │ exit    │       │                 │                       │  │
+ │  ◀─────────╯       │                 │                       │  │
+ │  │                 │                 │                       │  │
+ ├─ else: lock acquired ───────────────────────────────────────────┤
+ │  │                 │                 │                       │  │
+ │  ◀─ owner ─────────┤                 │                       │  │
+ │  │                 │                 │                       │  │
+ │  ├─ bind, register, starting ────────▶                       │  │
+ │  │                 │                 │                       │  │
+ │  ├─ initialize ──────────────────────────────────────────────▶  │
+ │  │                 │                 │                       │  │
+ │╭─ alt: boot succeeds ──────────────────────────────────────────╮│
+ ││ │                 │                 │                       │ ││
+ ││ │                 │                 ◀─ ready ───────────────┤ ││
+ ││ │                 │                 │                       │ ││
+ │├─ else: boot fails ────────────────────────────────────────────┤│
+ ││ │                 │                 │                       │ ││
+ ││ │                 │                 ◀─ failed, stay bound ──┤ ││
+ ││ │                 │                 │                       │ ││
+ │╰───────────────────────────────────────────────────────────────╯│
+ │  │                 │                 │                       │  │
+ ╰─────────────────────────────────────────────────────────────────╯
+    │                 │                 │                       │
+```
+
+Lock acquisition by a contender is nonblocking or tightly bounded. A loser
+must exit before constructing application routes or importing startup-heavy
+modules.
+
+Several clients may spawn contenders concurrently. The design guarantees one
+heavy winner, not one process spawn. If the winner crashes during startup, the
+OS releases the lock and a later client retry starts another election.
+
+The lock is scoped by installation channel and service profile. Local, preview,
+and stable installations cannot displace one another.
+
+## Update Activation
+
+Background update behavior remains unchanged:
+
+1. The running service checks for an update.
+2. The updater installs the package in the background.
+3. The running process continues using its existing process image.
+4. No idle check or automatic restart occurs.
+
+A fresh TUI launch activates the installed update:
+
+1. Read registration and authenticate the responding service.
+2. If its package version matches the fresh client, attach normally.
+3. If the version differs, request graceful stop of that exact registered
+   instance using the existing authenticated stop path.
+4. Re-check instance identity before every signal or escalation in that path.
+5. Wait for the old process to exit and release the service lock.
+6. Call `ensureRunning` until a compatible service becomes ready.
+
+Concurrent fresh launchers may all observe the same old instance. Stopping that
+exact instance must be idempotent. Once registration names a different instance,
+a stale launcher stops signaling and returns to discovery.
+
+No durable restart-transition record is introduced. The initiating fresh TUI
+already knows the source and target versions and can display its update
+preflight. Existing TUIs may display `Updating...` if they observed `stopping`;
+otherwise `Waiting for background service...` is the honest fallback.
+
+## Fresh Launch Versus Reconnect
+
+Fresh launch and reconnect deliberately have different version policies:
+
+```typescript
+type ManagedConnection =
+  | {
+      type: "launch"
+      requiredVersion: string
+    }
+  | {
+      type: "reconnect"
+    }
+```
+
+- `launch` requires the installed package version and may activate replacement.
+- `reconnect` accepts the current owner and never activates replacement.
+
+This preserves today's permissive reconnect behavior. Explicit application
+protocol negotiation and automatic TUI re-exec remain follow-ups.
+
+## Client Reconnect
+
+Fresh and existing TUIs use the same status loop after startup:
+
+1. Read registration on every attempt. Do not retry a stale URL indefinitely.
+2. If registration is absent, call `ensureRunning` and continue waiting.
+3. If registration is unreachable, call `ensureRunning`. A live owner prevents
+   contenders from acquiring the lock; a dead owner does not.
+4. If status is `starting` or `stopping`, wait.
+5. If status is `failed`, show its actionable message.
+6. If status is `ready`, rebuild HTTP and event-stream clients for the new
+   endpoint and perform authoritative state reconciliation.
+
+Retry cadence is internal policy. Retry counts are telemetry, not user-facing
+state. The TUI waits until the service is ready or the user exits.
+
+Transport failures are handled at the TUI run boundary. A raw client transport
+error or Effect defect must not escape to the terminal. Hard exit is reserved
+for diagnosed causes such as invalid local configuration, failed authentication,
+or a foreign process occupying an explicitly configured port.
+
+The UI derives text from status:
+
+| Status                   | User-facing state                   |
+| ------------------------ | ----------------------------------- |
+| No registration          | `Starting background service...`    |
+| Registration unreachable | `Waiting for background service...` |
+| `starting`               | `Starting OpenCode vX...`           |
+| `stopping`               | `Updating to vX...`                 |
+| `failed`                 | Actionable failure message          |
+| `ready`                  | Normal TUI                          |
+
+## Graceful Session Continuity
+
+Version-mismatch replacement uses the existing graceful Session suspension and
+resumption hooks:
+
+1. The old server snapshots active Session IDs during graceful teardown.
+2. The successor schedules those Sessions for continuation.
+3. The runner reloads durable Session history before continuing.
+
+This lifecycle design does not define what an interrupted physical provider
+attempt or tool invocation means. It does not promise that external side effects
+did not occur, replay the exact interrupted tool, preserve an in-memory form, or
+recover process-local background work.
+
+Those concerns require a separate execution-continuity design covering tools,
+shells, sub-agents, permissions, questions, provider attempts, and hard-crash
+recovery.
+
+## Unresponsive Owner
+
+An unreachable registration does not prove that the owner is dead. A contender
+attempts the service lock:
+
+- If the lock is free, the contender starts a replacement.
+- If the lock is held, the contender exits and the client keeps waiting.
+
+After a bounded diagnostic threshold, the client may show:
+
+```text
+The background service owns the service lock but is not responding.
+Run `opencode service restart` to recover it.
+```
+
+Only explicit `service restart` may perform destructive recovery. It verifies
+the complete registration and process instance before signaling, waits for
+graceful exit, re-checks identity before escalation, and refuses to kill a
+process it cannot positively identify.
+
+Automatic frozen-owner recovery is deferred.
+
+## Failure Walkthroughs
+
+### Update with open TUIs
+
+1. The old service installs vNext but keeps running.
+2. A fresh vNext TUI finds the healthy vOld service and requests graceful stop.
+3. The old service reports `stopping`, suspends active Sessions, and exits.
+4. Open TUIs enter their indefinite status loops.
+5. One or more clients spawn contenders.
+6. One contender acquires the service lock. Losers exit before heavy boot.
+7. The winner binds and registers the lifecycle shell as `starting`.
+8. Clients stop spawning and wait on the observable winner.
+9. The winner initializes the application and reports `ready`.
+10. TUIs rebuild clients, reconcile state, and resume.
+
+### Server crashes while ready
+
+1. The endpoint becomes unreachable and registration may remain stale.
+2. Clients call `ensureRunning`.
+3. Process death has released the service lock.
+4. One contender wins, replaces registration, and starts normally.
+5. Detailed active-execution recovery is outside this design.
+
+### Winner crashes during startup
+
+1. Clients observed `starting` and remain alive.
+2. Process death releases the service lock.
+3. A later reconnect attempt starts another election.
+4. One new contender wins; all other contenders exit.
+
+### Registration is deleted while the owner is healthy
+
+1. Clients may call `ensureRunning` because discovery is absent.
+2. Every contender fails to acquire the owner's lock and exits.
+3. No second application initializes.
+4. The owner's next registration assertion republishes discovery.
+
+### Owner is alive but unresponsive
+
+1. Health fails, but the process still holds the service lock.
+2. Contenders fail lock acquisition and exit.
+3. Clients wait and eventually show explicit recovery guidance.
+4. No TUI kills the owner automatically.
+
+## TDD Verification
+
+Implementation should proceed test-first with real subprocesses and real locks.
+Mocks cannot establish process death, lock release, loser cleanup, or port
+behavior.
+
+### Election tests
+
+| Scenario                                              | Required result                                         |
+| ----------------------------------------------------- | ------------------------------------------------------- |
+| Ten contenders start simultaneously                   | Exactly one crosses the application-boot boundary       |
+| Winner pauses after lock acquisition                  | No loser initializes or remains alive                   |
+| Winner event loop pauses beyond the old stale timeout | Ownership is not displaced                              |
+| Winner crashes before bind                            | Lock releases; a later attempt wins                     |
+| Winner crashes after bind but before registration     | Lock releases; a later attempt replaces stale discovery |
+| Registration is deleted while owner runs              | No second owner initializes                             |
+| Registration is malformed                             | Lock still prevents a second owner                      |
+| Registration names a dead PID                         | New contender can acquire the released lock             |
+| Two installation channels start                       | Each elects an independent owner                        |
+| Explicit configured port is foreign-owned             | Fail diagnostically; do not kill the foreign process    |
+
+The fixture records a marker immediately before application initialization. The
+tests assert that only one process writes that marker and that every loser exits
+within a bounded interval. The harness should also assert that a loser's peak
+RSS stays an order of magnitude below an application boot, since import weight
+was the observed incident cost.
+
+### Lifecycle tests
+
+| Scenario                                        | Required result                                                  |
+| ----------------------------------------------- | ---------------------------------------------------------------- |
+| Winner owns lock but application boot is paused | Health reports `starting`                                        |
+| Application request arrives during startup      | Immediate retryable `503`                                        |
+| Application becomes ready                       | Status changes once from `starting` to `ready`                   |
+| Graceful replacement begins                     | Status reports `stopping` before disconnect                      |
+| Application initialization fails                | Actionable `failed` status; owner stays bound and holds the lock |
+| Registration is deleted while owner runs        | Owner republishes it within one assertion interval               |
+| Owner exits                                     | Registration is removed only if it still names that owner        |
+
+### Update tests
+
+| Scenario                               | Required result                                          |
+| -------------------------------------- | -------------------------------------------------------- |
+| Background update installs vNext       | Running vOld service does not restart                    |
+| Fresh vNext launch finds vOld          | Exact old instance stops; vNext eventually becomes ready |
+| Two fresh vNext launches race          | One heavy successor; both clients attach                 |
+| Existing vOld TUI reconnects to vNext  | It never requests replacement                            |
+| Stale launcher observes a new instance | It does not signal the new instance                      |
+
+### Reconnect tests
+
+| Scenario                                            | Required result                                    |
+| --------------------------------------------------- | -------------------------------------------------- |
+| Endpoint disappears and changes port                | TUI rediscovers and rebuilds clients               |
+| Service remains unavailable beyond old retry budget | TUI remains alive                                  |
+| Event stream reconnects                             | Client performs authoritative state reconciliation |
+| Transport returns an unexpected defect              | TUI formats it; no raw stack escapes               |
+| Owner remains unresponsive                          | TUI waits and shows explicit restart guidance      |
+
+## Delivery Sequence
+
+1. **Spike the lock primitive.** Prove a nonblocking, process-held OS lock
+   under Bun on macOS, Linux, and Windows (`bun:ffi` to `flock` on POSIX and a
+   named pipe on Windows), including release on hard kill and behavior across
+   containers and network filesystems used in CI.
+2. **Expand the subprocess test harness.** Begin from the baseline
+   two-contender test and cover ten contenders, lock release on crash, a paused
+   winner, deleted or corrupt registration, and bounded loser exit before
+   changing ownership.
+3. **Contain client failure.** Make transport loss nonterminal, rediscover on
+   every cycle, and format unexpected failures at the TUI boundary.
+4. **Promote the startup fence to process-held ownership.** Preserve the
+   existing pre-boot acquisition seam, replace its lease with the OS lock, hold
+   it until process exit, and invert the registration self-check from
+   self-termination to reassertion.
+5. **Bind the lifecycle shell first.** Publish registration and `starting`,
+   return retryable `503` for application requests, then initialize the app.
+   The health contract change is public API: regenerate clients from
+   `packages/client` with `bun run generate`.
+6. **Codify launch versus reconnect.** Fresh launch enforces installed version;
+   reconnect never activates replacement.
+7. **Integrate graceful replacement.** Preserve current background-install and
+   fresh-launch activation behavior while invoking Session continuity hooks.
+8. **Harden explicit recovery.** Verify exact process identity during explicit
+   `service restart`; never automatically kill an unresponsive owner.
+9. **Run the full multi-process suite.** Include repeated restart cycles and
+   assert that no contender or child process remains afterward.
+
+## Acceptance Criteria
+
+- Ten concurrent restart observers produce one application initialization.
+- No losing contender survives or builds a location graph.
+- A 30-second application boot remains continuously observable as `starting`.
+- A TUI remains alive through a service outage longer than the previous retry
+  budget.
+- A service endpoint change does not require restarting an existing TUI.
+- Background installation alone does not restart the service.
+- A fresh mismatched TUI eventually attaches to the installed service version.
+- Existing reconnecting TUIs never replace the current owner.
+- Registration corruption cannot produce two owners.
+- A deleted registration heals without restarting the owner or any client.
+- An unresponsive owner is not killed without an explicit recovery command.
+- Raw transport defects never escape to the terminal.
+
+## Follow-ups
+
+- Idle background update activation with an admission fence.
+- Application protocol compatibility and automatic local TUI re-exec.
+- Durable execution recovery for provider attempts and tools.
+- Shell, sub-agent, permission, question, and background-job continuity.
+- Automatic recovery for a positively identified frozen owner.
+- Cold-boot concurrency limits and interaction-prioritized location loading.
+- A steward or socket-handoff architecture if zero-downtime replacement becomes
+  a real requirement.

github/index.ts

@@ -495,7 +495,6 @@ async function subscribeSessionEvents() {
   console.log("Subscribing to session events...")
 
   const TOOL: Record<string, [string, string]> = {
-    todowrite: ["Todo", "\x1b[33m\x1b[1m"],
     bash: ["Bash", "\x1b[31m\x1b[1m"],
     edit: ["Edit", "\x1b[32m\x1b[1m"],
     glob: ["Glob", "\x1b[34m\x1b[1m"],

infra/console.ts

@@ -256,6 +256,7 @@ new sst.cloudflare.x.SolidStart("Console", {
     SECRET.UpstashRedisRestToken,
     AUTH_API_URL,
     STRIPE_WEBHOOK_SECRET,
+    SECRET.SupportApiKey,
     DISCORD_INCIDENT_WEBHOOK_URL,
     SECRET.HoneycombWebhookSecret,
     STRIPE_SECRET_KEY,

infra/enterprise.ts

@@ -7,6 +7,7 @@ new sst.cloudflare.x.SolidStart("Teams", {
   domain: shortDomain,
   path: "packages/enterprise",
   buildCommand: "bun run build:cloudflare",
+  link: [SECRET.SupportApiKey],
   environment: {
     OPENCODE_STORAGE_ADAPTER: "r2",
     OPENCODE_STORAGE_ACCOUNT_ID: sst.cloudflare.DEFAULT_ACCOUNT_ID,

infra/lake.ts

@@ -67,6 +67,10 @@ const athenaWorkgroup = new aws.athena.Workgroup("LakeAthenaWorkgroup", {
   configuration: {
     enforceWorkgroupConfiguration: true,
     publishCloudwatchMetricsEnabled: true,
+    // Athena bills $5/TB scanned; kill any query that would scan more than 2 TB
+    // so a regression cannot silently burn money. Stats sync full passes scan
+    // ~250 GB as of 2026-07.
+    bytesScannedCutoffPerQuery: 2 * 1024 ** 4,
     resultConfiguration: {
       outputLocation: $interpolate`s3://${athenaResultsBucket.bucket}/`,
     },

infra/secret.ts

@@ -9,6 +9,7 @@ export const SECRET = {
   R2SecretKey: new sst.Secret("R2SecretKey", "unknown"),
   HoneycombApiKey: new sst.Secret("HONEYCOMB_API_KEY"),
   HoneycombWebhookSecret: new random.RandomPassword("HoneycombWebhookSecret", { length: 24 }),
+  SupportApiKey: new sst.Secret("SUPPORT_API_KEY"),
   UpstashRedisRestUrl: new sst.Secret("UpstashRedisRestUrl"),
   UpstashRedisRestToken: new sst.Secret("UpstashRedisRestToken"),
 }

infra/stats.ts

@@ -42,11 +42,12 @@ const inferenceEventTable = new aws.s3tables.Table(
             { name: "request", type: "string", required: false },
             { name: "client", type: "string", required: false },
             { name: "user_agent", type: "string", required: false },
+            { name: "model", type: "string", required: false },
+            { name: "model_tier", type: "string", required: false },
             { name: "model_variant", type: "string", required: false },
             { name: "source", type: "string", required: false },
             { name: "provider", type: "string", required: false },
             { name: "provider_model", type: "string", required: false },
-            { name: "model", type: "string", required: false },
             { name: "llm_error_code", type: "int", required: false },
             { name: "llm_error_message", type: "string", required: false },
             { name: "error_response", type: "string", required: false },
@@ -56,6 +57,7 @@ const inferenceEventTable = new aws.s3tables.Table(
             { name: "error_cause2", type: "string", required: false },
             { name: "api_key", type: "string", required: false },
             { name: "workspace", type: "string", required: false },
+            { name: "user_id", type: "string", required: false },
             { name: "is_subscription", type: "boolean", required: false },
             { name: "subscription", type: "string", required: false },
             { name: "response_length", type: "long", required: false },
@@ -84,7 +86,7 @@ const inferenceEventTable = new aws.s3tables.Table(
       },
     },
   },
-  { deleteBeforeReplace: $app.stage !== "production" },
+  { deleteBeforeReplace: $app.stage !== "production", ignoreChanges: ["metadata"] },
 )
 
 export const inferenceEvent = new sst.Linkable("InferenceEvent", {
@@ -165,7 +167,7 @@ export const app = new sst.cloudflare.x.SolidStart("Stats", {
   domain: `stats.${domain}`,
   link: [database, EMAILOCTOPUS_API_KEY],
   environment: {
-    PUBLIC_URL: `https://stats.${domain}/stats`,
+    PUBLIC_URL: `https://${domain}/data`,
   },
 })
 
@@ -183,7 +185,9 @@ export const statSync = new sst.aws.Service("StatsSyncService", {
   cluster: lakeCluster,
   architecture: "arm64",
   cpu: "0.25 vCPU",
-  memory: "0.5 GB",
+  // 0.5 GB caused an OOM crash loop: every restart immediately re-ran the 4 Athena
+  // stats queries (~$5/pass) every ~5 minutes instead of hourly.
+  memory: "2 GB",
   image: {
     context: ".",
     dockerfile: "packages/stats/server/Dockerfile",

nix/hashes.json

@@ -1,8 +1,8 @@
 {
   "nodeModules": {
-    "x86_64-linux": "sha256-fzplLKjzYefVCRhAgfCWWIa3me2JiI2d9kDBACnz4fA=",
-    "aarch64-linux": "sha256-gccipj2CAau/lZ7KTQhdeU8n6fcXDuUt4X4XbNufCko=",
-    "aarch64-darwin": "sha256-r0QEetxKUf6HrtMOozyvb4jjEJjVtp+DE8aiKKhRrVI=",
-    "x86_64-darwin": "sha256-bU+5WudkiIflFgoqgLSf30iqeNNLuEbScI5oMFPu9eM="
+    "x86_64-linux": "sha256-F1luclnqCPQk9yxfmeSYGaM/nScf28yBu9K3Fv+Xd24=",
+    "aarch64-linux": "sha256-XW0XZnsCRkU3MFJH9TjMRYZHffzVy3cQyiNCkec2gl4=",
+    "aarch64-darwin": "sha256-bf8kvORs3Fs2UYLp3PekF+AJR7NKOcHb+fIQA79RtMk=",
+    "x86_64-darwin": "sha256-sBdQPkzd7JXNW6Lbi9JHiAsfHwdLwTKWY+uPeXAv2Nw="
   }
 }

nix/opencode.nix

@@ -27,6 +27,13 @@ stdenvNoCC.mkDerivation (finalAttrs: {
     writableTmpDirAsHomeHook
   ];
 
+  postPatch = ''
+    # NOTE: Relax Bun version check to be a warning instead of an error
+    substituteInPlace packages/script/src/index.ts \
+      --replace-fail 'throw new Error(`This script requires bun@''${expectedBunVersionRange}' \
+                     'console.warn(`Warning: This script requires bun@''${expectedBunVersionRange}'
+  '';
+
   configurePhase = ''
     runHook preConfigure
 

package.json

@@ -2,23 +2,30 @@
   "$schema": "https://json.schemastore.org/package.json",
   "name": "opencode",
   "description": "AI-powered development tool",
+  "version": "0.0.0",
   "private": true,
   "type": "module",
   "packageManager": "bun@1.3.14",
   "scripts": {
-    "dev": "bun run --cwd packages/opencode --conditions=browser src/index.ts",
+    "dev": "bun run --cwd packages/cli --conditions=browser src/index.ts",
     "dev:desktop": "bun --cwd packages/desktop dev",
     "dev:web": "bun --cwd packages/app dev",
     "dev:console": "ulimit -n 10240 2>/dev/null; bun run --cwd packages/console/app dev",
     "dev:stats": "bun sst shell --stage=production -- bun run --cwd packages/stats/app dev",
+    "dev:www": "bun run --cwd packages/www dev",
     "dev:storybook": "bun --cwd packages/storybook storybook",
     "lint": "oxlint",
-    "typecheck": "bun turbo typecheck",
+    "lint:effect-patterns": "ast-grep scan -c script/ast-grep/sgconfig.yml packages/core/src packages/server/src packages/protocol/src packages/cli/src",
+    "test:lint-rules": "ast-grep test -c script/ast-grep/sgconfig.yml",
+    "typecheck": "bun turbo typecheck --concurrency=3",
+    "typecheck:profile": "bun script/profile-typecheck.ts",
+    "typecheck:profile:packages": "bun script/profile-typecheck-packages.ts",
     "upgrade-opentui": "bun run script/upgrade-opentui.ts",
-    "postinstall": "bun run --cwd packages/opencode fix-node-pty",
+    "postinstall": "bun run --cwd packages/core fix-node-pty",
     "prepare": "husky",
     "random": "echo 'Random script'",
     "sso": "aws sso login --sso-session=opencode --no-browser",
+    "translate:app": "bun run script/translate-app.ts",
     "test": "echo 'do not run tests from root' && exit 1"
   },
   "workspaces": {
@@ -30,19 +37,23 @@
       "packages/slack"
     ],
     "catalog": {
-      "@effect/opentelemetry": "4.0.0-beta.74",
-      "@effect/platform-node": "4.0.0-beta.74",
-      "@effect/sql-sqlite-bun": "4.0.0-beta.74",
+      "@effect/opentelemetry": "4.0.0-beta.98",
+      "@effect/platform-node": "4.0.0-beta.98",
+      "@effect/sql-sqlite-bun": "4.0.0-beta.98",
       "@npmcli/arborist": "9.4.0",
       "@types/bun": "1.3.13",
       "@types/cross-spawn": "6.0.6",
       "@octokit/rest": "22.0.0",
+      "@hono/standard-validator": "0.2.0",
       "@hono/zod-validator": "0.4.2",
-      "@opentui/core": "0.3.1",
-      "@opentui/keymap": "0.3.1",
-      "@opentui/solid": "0.3.1",
+      "@opentui/core": "0.4.5",
+      "@opentui/keymap": "0.4.5",
+      "@opentui/solid": "0.4.5",
+      "@tanstack/solid-virtual": "3.13.32",
+      "@shikijs/stream": "4.2.0",
       "ulid": "3.0.1",
       "@kobalte/core": "0.13.11",
+      "@corvu/drawer": "0.2.4",
       "@types/luxon": "3.7.1",
       "@types/node": "24.12.2",
       "@types/semver": "7.7.1",
@@ -50,22 +61,23 @@
       "@tsconfig/bun": "1.0.9",
       "@cloudflare/workers-types": "4.20251008.0",
       "@openauthjs/openauth": "0.0.0-20250322224806",
-      "@pierre/diffs": "1.1.0-beta.18",
-      "opentui-spinner": "0.0.6",
+      "@pierre/diffs": "1.2.10",
+      "opentui-spinner": "0.0.7",
       "@solid-primitives/storage": "4.3.3",
       "@tailwindcss/vite": "4.1.11",
       "diff": "8.0.2",
       "dompurify": "3.3.1",
       "drizzle-kit": "1.0.0-rc.2",
       "drizzle-orm": "1.0.0-rc.2",
-      "effect": "4.0.0-beta.74",
+      "effect": "4.0.0-beta.98",
       "ai": "6.0.168",
       "cross-spawn": "7.0.6",
       "hono": "4.10.7",
       "hono-openapi": "1.1.2",
       "fuzzysort": "3.1.0",
+      "get-east-asian-width": "1.6.0",
       "luxon": "3.6.1",
-      "marked": "17.0.1",
+      "marked": "17.0.6",
       "marked-shiki": "1.2.1",
       "remend": "1.3.0",
       "@playwright/test": "1.59.1",
@@ -74,11 +86,12 @@
       "@typescript/native-preview": "7.0.0-dev.20251207.1",
       "zod": "4.1.8",
       "remeda": "2.26.0",
+      "resolve.exports": "2.0.3",
       "sst": "4.13.1",
-      "shiki": "3.20.0",
+      "shiki": "4.2.0",
       "solid-list": "0.3.0",
+      "string-width": "7.2.0",
       "tailwindcss": "4.1.11",
-      "virtua": "0.49.1",
       "vite": "7.1.4",
       "@solidjs/meta": "0.29.4",
       "@solidjs/router": "0.15.4",
@@ -92,6 +105,9 @@
   },
   "devDependencies": {
     "@actions/artifact": "5.0.1",
+    "@ast-grep/cli": "0.44.0",
+    "@types/react": "19.2.17",
+    "@types/react-dom": "19.2.3",
     "@tsconfig/bun": "catalog:",
     "@types/mime-types": "3.0.1",
     "@typescript/native-preview": "catalog:",
@@ -102,7 +118,7 @@
     "prettier": "3.6.2",
     "semver": "^7.6.0",
     "sst": "catalog:",
-    "turbo": "2.8.13"
+    "turbo": "2.10.2"
   },
   "dependencies": {
     "@aws-sdk/client-s3": "3.933.0",
@@ -139,14 +155,18 @@
     "@types/node": "catalog:"
   },
   "patchedDependencies": {
-    "@npmcli/agent@4.0.0": "patches/@npmcli%2Fagent@4.0.0.patch",
+    "@ff-labs/fff-bun@0.9.3": "patches/@ff-labs%2Ffff-bun@0.9.3.patch",
+    "@npmcli/agent@4.0.2": "patches/@npmcli%2Fagent@4.0.2.patch",
     "@silvia-odwyer/photon-node@0.3.4": "patches/@silvia-odwyer%2Fphoton-node@0.3.4.patch",
     "@standard-community/standard-openapi@0.2.9": "patches/@standard-community%2Fstandard-openapi@0.2.9.patch",
     "solid-js@1.9.10": "patches/solid-js@1.9.10.patch",
-    "virtua@0.49.1": "patches/virtua@0.49.1.patch",
-    "@ai-sdk/xai@3.0.82": "patches/@ai-sdk%2Fxai@3.0.82.patch",
+    "@ai-sdk/xai@3.0.102": "patches/@ai-sdk%2Fxai@3.0.102.patch",
     "gcp-metadata@8.1.2": "patches/gcp-metadata@8.1.2.patch",
     "pacote@21.5.0": "patches/pacote@21.5.0.patch",
-    "@ai-sdk/google@3.0.73": "patches/@ai-sdk%2Fgoogle@3.0.73.patch"
+    "@ai-sdk/google@3.0.73": "patches/@ai-sdk%2Fgoogle@3.0.73.patch",
+    "@pierre/trees@1.0.0-beta.4": "patches/@pierre%2Ftrees@1.0.0-beta.4.patch",
+    "@modelcontextprotocol/sdk@1.29.0": "patches/@modelcontextprotocol%2Fsdk@1.29.0.patch",
+    "effect@4.0.0-beta.98": "patches/effect@4.0.0-beta.98.patch",
+    "@tanstack/virtual-core@3.17.3": "patches/@tanstack%2Fvirtual-core@3.17.3.patch"
   }
 }

packages/ai/AGENTS.md

@@ -1,4 +1,4 @@
-# LLM Package Guide
+# AI Package Guide
 
 ## Effect
 
@@ -10,7 +10,7 @@
 
 ## Conventions
 
-Per-type constructors live on the type, not as top-level re-exports. Use `Message.user(...)`, `Message.assistant(...)`, `Message.tool(...)`, `Model.make(...)`, `ToolDefinition.make(...)`, `ToolCallPart.make(...)`, `ToolResultPart.make(...)`, `ToolChoice.make(...)`, `ToolChoice.named(...)`, `SystemPart.make(...)`, and `GenerationOptions.make(...)` directly. The top-level `LLM` namespace is reserved for request-shaped call APIs: `LLM.request`, `LLM.generate`, `LLM.stream`, `LLM.updateRequest`, and `LLM.generateObject`. Two ways to construct the same thing is one too many.
+Per-type constructors live on the type, not as top-level re-exports. Use `Message.system(...)`, `Message.user(...)`, `Message.assistant(...)`, `Message.tool(...)`, `Model.make(...)`, `ToolDefinition.make(...)`, `ToolCallPart.make(...)`, `ToolResultPart.make(...)`, `ToolChoice.make(...)`, `ToolChoice.named(...)`, `SystemPart.make(...)`, and `GenerationOptions.make(...)` directly. The top-level `LLM` namespace is reserved for request-shaped call APIs: `LLM.request`, `LLM.generate`, `LLM.stream`, `LLM.updateRequest`, and `LLM.generateObject`. Two ways to construct the same thing is one too many.
 
 ## Tests
 
@@ -25,7 +25,7 @@ Primary in-repo integration point:
 
 - `packages/opencode/src/session/llm.ts` is the session-owned orchestration layer that decides whether a request uses AI SDK or this package's native route runtime.
 - `packages/opencode/src/session/llm/native-request.ts` is the lowering adapter from opencode's session/AI SDK-shaped data into this package's `LLMRequest` model.
-- `packages/opencode/src/session/llm/native-runtime.ts` is the execution adapter that calls `LLMClient.stream(...)` and bridges opencode tools into this package's tool runtime.
+- `packages/opencode/src/session/llm/native-runtime.ts` is the execution adapter that calls raw `LLMClient.stream(request)` and bridges one provider turn of opencode tool calls through this package's typed dispatcher.
 - `packages/opencode/src/session/llm/ai-sdk.ts` keeps the default AI SDK path compatible by converting AI SDK stream parts into this package's shared `LLMEvent`s.
 
 Keep this package independent of session concerns. Session auth, permissions, plugins, telemetry headers, and runtime selection belong in `packages/opencode/src/session/llm.ts` and its local adapters.
@@ -113,10 +113,27 @@ Keep provider facades small and explicit:
 
 `Provider.make(...)` remains available for simple static provider definitions, but new built-in providers should prefer plain configured facades unless a helper removes real duplication without adding runtime behavior.
 
+### Provider Package Entrypoints
+
+Catalog-selected native providers use package-like export paths from `@opencode-ai/ai`. They are internal entrypoints in one npm package, not separately published provider packages. Every entrypoint implements `ProviderPackage.Definition` and exposes `model(modelID, settings)`, where settings are serializable provider configuration plus common `headers`, `body`, and `limits` overlays.
+
+```ts
+import { model } from "@opencode-ai/ai/providers/openai/responses"
+
+const selected = model("gpt-5", {
+  apiKey,
+  transport: "websocket",
+})
+```
+
+Keep semantic APIs as separate entrypoints, such as OpenAI `chat` and `responses`. Keep transport choices inside the semantic entrypoint settings, so OpenAI Responses HTTP and WebSocket share one entrypoint. Provider facades may still expose named selectors such as `responsesWebSocket` for direct typed call sites; the package-like contract maps its settings to those selectors before returning an executable `Model`.
+
+Do not expose `Route` in provider package settings. Route composition stays an implementation detail behind `model(...)`.
+
 ### Folder layout
 
 ```
-packages/llm/src/
+packages/ai/src/
   schema/                   canonical Schema model, split by concern
     ids.ts                  branded IDs, literal types, ProviderMetadata
     options.ts              Generation/Provider/Http options, Limits, Model, cache policy
@@ -126,7 +143,7 @@ packages/llm/src/
     index.ts                barrel
   llm.ts                    request constructors and convenience helpers
   route/
-    index.ts                @opencode-ai/llm/route advanced barrel
+    index.ts                @opencode-ai/ai/route advanced barrel
     client.ts               Route.make + LLMClient.prepare/stream/generate
     executor.ts             RequestExecutor service + transport error mapping
     protocol.ts             Protocol type + Protocol.make
@@ -147,13 +164,15 @@ packages/llm/src/
     bedrock-converse.ts
     bedrock-event-stream.ts framing for AWS event-stream binary frames
     openai-compatible-chat.ts route that reuses OpenAIChat.protocol, no canonical URL
+    openai-compatible-responses.ts route that reuses OpenAIResponses.protocol, no canonical URL
     utils/                  per-protocol helpers (auth, cache, media, tool-stream, ...)
   providers/
-    openai-compatible.ts    generic compatible helper + family model helpers
+    openai-compatible.ts    generic Chat helper + family model helpers
+    openai-compatible-responses.ts generic Responses helper
     openai-compatible-profile.ts family defaults (deepseek, togetherai, ...)
     azure.ts / amazon-bedrock.ts / cloudflare.ts / github-copilot.ts / google.ts / xai.ts / openai.ts / anthropic.ts / openrouter.ts
   tool.ts                   typed tool() helper
-  tool-runtime.ts           implementation helpers for LLMClient tool execution
+  tool-runtime.ts           narrow one-call typed tool dispatcher
 ```
 
 The dependency arrow points down: `providers/*.ts` files import protocol routes and auth-option utilities; protocol modules import `endpoint`, `auth`, `framing`, and transport pieces. Protocols do not import provider facades. Lower-level modules know nothing about provider catalog metadata.
@@ -171,6 +190,20 @@ The dependency arrow points down: `providers/*.ts` files import protocol routes
 
 If you find yourself copying a 3-to-5-line snippet between two protocols, lift it into `ProviderShared` next to these helpers rather than duplicating.
 
+### Chronological System Updates
+
+`LLMRequest.system` is the initial privileged prompt that applies ahead of the conversation. `Message.system(...)` is a separate, provider-neutral chronological operator update inside `LLMRequest.messages`; it applies only from its position in history onward and accepts text content only.
+
+Native chronological system messages are route/model-specific. Anthropic Messages lowers them natively for Claude Opus 4.8 (`claude-opus-4-8`). Other routes and models intentionally lower the update in place into ordinary user-compatible text using this stable escaped representation:
+
+```text
+<system-update>
+...
+</system-update>
+```
+
+The wrapped-user fallback preserves ordering while visibly lowering authority. Never silently pass a raw chronological `role: "system"` through a route that might reject it. Do not insert raw retrieved documents, tool output, or web content into privileged chronological system updates; keep untrusted content in ordinary user/tool channels.
+
 ### Tools
 
 Tool loops are represented in common messages and events:
@@ -187,9 +220,9 @@ const followUp = LLM.request({
 
 Routes lower these into provider-native assistant tool-call messages and tool-result messages. Streaming providers should emit `tool-input-delta` events while arguments arrive, then a final `tool-call` event with parsed input.
 
-### Tool runtime
+### Tool dispatch
 
-`LLM.stream({ request, tools })` executes model-requested tools with full type safety. Plain `LLM.stream(request)` only streams the model; if `request.tools` contains schemas, tool calls are returned for the caller to handle. Use `toolExecution: "none"` to pass executable tool definitions as schemas without invoking handlers. Add `stopWhen` to opt into follow-up model rounds after tool results.
+`LLM.stream(request)` and `LLM.generate(request)` each run exactly one provider turn. Add tool schemas to `request.tools` with `Tool.toDefinitions(tools)`. When a caller wants the package's typed one-call execution behavior, pass each canonical local `tool-call` event to `ToolRuntime.dispatch(tools, call)`.
 
 ```ts
 const get_weather = tool({
@@ -205,22 +238,25 @@ const get_weather = tool({
     }),
 })
 
-const events = yield* LLM.stream({
-  request,
-  tools: { get_weather, get_time, ... },
-  stopWhen: LLM.stepCountIs(10),
-}).pipe(Stream.runCollect)
+const tools = { get_weather, get_time, ... }
+const events = yield* LLM.stream(
+  LLM.updateRequest(request, { tools: Tool.toDefinitions(tools) }),
+).pipe(Stream.runCollect)
+
+const call = Array.from(events).find(LLMEvent.is.toolCall)
+if (call && !call.providerExecuted) {
+  const dispatched = yield* ToolRuntime.dispatch(tools, call)
+  // Persist call + dispatched.result, then construct the next request explicitly.
+}
 ```
 
-The runtime:
+The dispatcher:
 
-- Adds tool definitions (derived from each tool's `parameters` Schema via `Schema.toJsonSchemaDocument`) onto `request.tools`.
-- Streams the model.
-- On `tool-call`: looks up the named tool, decodes input against `parameters` Schema, dispatches to the typed `execute`, encodes the result against `success` Schema, emits `tool-result`.
-- Emits local `tool-result` events in the same step by default.
-- Loops only when `stopWhen` is provided and the step finishes with `tool-calls`, appending the assistant + tool messages.
+- On `tool-call`: looks up the named tool, decodes input against `parameters` Schema, dispatches to the typed `execute`, encodes the result against `success` Schema, and returns canonical `tool-result` events.
+- Does not stream providers, construct Session events, schedule fibers, append history, count steps, or continue model rounds.
+- Leaves persistence and continuation to the enclosing product flow.
 
-Handler dependencies (services, permissions, plugin hooks, abort handling) are closed over by the consumer at tool-construction time. The runtime's only environment requirement is `RequestExecutor.Service`. Build the tools record inside an `Effect.gen` once and reuse it across many runs.
+Handler dependencies (services, permissions, plugin hooks, abort handling) are closed over by the consumer at tool-construction time. Build the tools record inside an `Effect.gen` once and reuse it across many dispatches.
 
 Errors must be expressed as `ToolFailure`. The runtime catches it and emits a `tool-error` event, then a `tool-result` of `type: "error"`, so the model can self-correct on the next step. Anything that is not a `ToolFailure` is treated as a defect and fails the stream. Three recoverable error paths produce `tool-error` events:
 
@@ -231,8 +267,8 @@ Errors must be expressed as `ToolFailure`. The runtime catches it and emits a `t
 Provider-defined / hosted tools (Anthropic `web_search` / `code_execution` / `web_fetch`, OpenAI Responses `web_search_call` / `file_search_call` / `code_interpreter_call` / `mcp_call` / `local_shell_call` / `image_generation_call` / `computer_use_call`) pass through the runtime untouched:
 
 - Routes surface the model's call as a `tool-call` event with `providerExecuted: true`, and the provider's result as a matching `tool-result` event with `providerExecuted: true`.
-- The runtime detects `providerExecuted` on `tool-call` and **skips client dispatch** — no handler is invoked and no `tool-error` is raised for "unknown tool". The provider already executed it.
-- Both events are appended to the assistant message in `assistantContent` so the next round's history carries the call + result for context. Anthropic encodes them back as `server_tool_use` + `web_search_tool_result` (or `code_execution_tool_result` / `web_fetch_tool_result`) blocks; OpenAI Responses callers typically use `previous_response_id` instead of resending hosted-tool items.
+- Callers detect `providerExecuted` on `tool-call` and **skip local dispatch** — no handler is invoked and no `tool-error` is raised for "unknown tool". The provider already executed it.
+- Callers that continue should retain both events in explicit history when the protocol requires it. Anthropic encodes them back as `server_tool_use` + `web_search_tool_result` (or `code_execution_tool_result` / `web_fetch_tool_result`) blocks; OpenAI Responses callers typically use `previous_response_id` instead of resending hosted-tool items.
 
 Add provider-defined tools to `request.tools` (no runtime entry needed). The matching route must know how to lower the tool definition into the provider-native shape; right now Anthropic accepts `web_search` / `code_execution` / `web_fetch` and OpenAI Responses accepts the hosted tool names listed above.
 
@@ -286,7 +322,7 @@ recorded.effect("streams text", () =>
 )
 ```
 
-Replay is the default. `RECORD=true` records fresh cassettes and requires the listed env vars. Cassettes are written as pretty-printed JSON so multi-interaction diffs stay reviewable.
+Replay is the default. `RECORD=true` records fresh cassettes locally and requires the listed env vars; unset `CI` before recording because CI always forces replay. Cassettes are written as pretty-printed JSON so multi-interaction diffs stay reviewable.
 
 Pass `provider`, `protocol`, and optional `tags` to `recordedTests(...)` / `recorded.effect.with(...)` so cassettes carry searchable metadata. Use recorded-test filters to replay or record a narrow subset without rewriting a whole file:
 
@@ -297,8 +333,8 @@ Pass `provider`, `protocol`, and optional `tags` to `recordedTests(...)` / `reco
 
 Filters apply in replay and record mode. Combine them with `RECORD=true` when refreshing only one provider or scenario.
 
-**Binary response bodies.** Most providers stream text (SSE, JSON). AWS Bedrock streams binary AWS event-stream frames whose CRC32 fields would be mangled by a UTF-8 round-trip — those bodies are stored as base64 with `bodyEncoding: "base64"` on the response snapshot. Detection is by `Content-Type` in `@opencode-ai/http-recorder` (currently `application/vnd.amazon.eventstream` and `application/octet-stream`); cassettes for SSE/JSON routes omit the field and decode as text.
+**Binary response bodies.** Most providers stream text (SSE, JSON). The recorder treats known textual media types (`text/*`, JSON/XML structured types, JavaScript, forms, YAML, and SVG) as text and stores every other response as base64 with `bodyEncoding: "base64"`. This preserves binary formats such as AWS event-stream frames without a lossy UTF-8 round trip.
 
-**Matching strategy.** Replay walks the cassette in record order via an internal cursor: the Nth runtime request is served by the Nth recorded interaction, and each one is validated by comparing method, URL, allow-listed headers, and the canonical JSON body. This handles tool loops (each round's request differs as history grows) and retry/polling scenarios (successive byte-identical requests with different responses) uniformly. If a test reorders its requests, re-record the cassette. `scriptedResponses` (in `test/lib/http.ts`) is the deterministic counterpart for tests that don't need a live provider; it scripts response bodies in order without reading from disk.
+**Matching strategy.** A runtime request atomically claims the first unused recorded interaction that matches its method, URL, allow-listed headers, and canonical JSON body. Distinct requests may replay in any order or concurrently. Repeated identical requests consume their matching responses in cassette order, preserving deterministic retry and polling behavior. `scriptedResponses` (in `test/lib/http.ts`) is the deterministic counterpart for tests that don't need a live provider; it scripts response bodies in order without reading from disk.
 
 Do not blanket re-record an entire test file when adding one cassette. `RECORD=true` rewrites every recorded case that runs, and provider streams contain volatile IDs, timestamps, fingerprints, and obfuscation fields. Prefer deleting the one cassette you intend to refresh, or run a focused test pattern that only registers the scenario you want to record. Keep stable existing cassettes unchanged unless their request shape or expected behavior changed.

packages/ai/README.md

@@ -0,0 +1,233 @@
+# @opencode-ai/ai
+
+Schema-first AI primitives for opencode. Provider quirks live in adapters, not in calling code.
+
+```ts
+import { Effect } from "effect"
+import { LLM, LLMClient } from "@opencode-ai/ai"
+import { OpenAI } from "@opencode-ai/ai/providers"
+
+const model = OpenAI.configure({ apiKey: process.env.OPENAI_API_KEY }).responses("gpt-4o-mini")
+
+const request = LLM.request({
+  model,
+  system: "You are concise.",
+  prompt: "Say hello in one short sentence.",
+  generation: { maxTokens: 40 },
+})
+
+const program = Effect.gen(function* () {
+  const response = yield* LLMClient.generate(request)
+  console.log(response.text)
+})
+```
+
+Run `LLMClient.stream(request)` instead of `generate` when you want incremental `LLMEvent`s. The event stream is provider-neutral — same shape across OpenAI Chat, OpenAI Responses, Anthropic Messages, Gemini, Bedrock Converse, and any OpenAI-compatible deployment.
+
+## Image generation
+
+Use `Image.generate` with an image model for direct asset generation:
+
+```ts
+import { Image } from "@opencode-ai/ai"
+import { OpenAI } from "@opencode-ai/ai/providers"
+
+const program = Effect.gen(function* () {
+  const response = yield* Image.generate({
+    model: OpenAI.configure({ apiKey: process.env.OPENAI_API_KEY }).image("gpt-image-2"),
+    prompt: "A robot tending a rooftop garden",
+    count: 2,
+    size: { width: 1024, height: 1024 },
+    providerOptions: { openai: { quality: "high", outputFormat: "webp" } },
+  })
+
+  return response.images // GeneratedImage[] with owned bytes or a provider URL
+})
+```
+
+Conversational image generation remains part of the LLM interaction. OpenAI Responses exposes it through its hosted image tool:
+
+```ts
+const program = Effect.gen(function* () {
+  const response = yield* LLM.generate(
+    LLM.request({
+      model: OpenAI.configure({ apiKey }).responses("gpt-5"),
+      prompt: "Design a solarpunk rooftop garden, then show me.",
+      tools: [OpenAI.imageGeneration({ quality: "high" })],
+    }),
+  )
+
+  return response.message
+})
+```
+
+The hosted result is represented as a provider-executed tool call and tool result. Its image is a `file` content item with a data URI, so retaining `response.message` preserves the generated image for continuation.
+
+## Public API
+
+- **`LLM.request({...})`** — build a provider-neutral `LLMRequest`. Accepts ergonomic inputs (`system: string`, `prompt: string`) that normalize into the canonical Schema classes.
+- **`LLM.generate` / `LLM.stream`** — re-exported from `LLMClient` for one-import use.
+- **`Message.user(...)` / `Message.assistant(...)` / `Message.tool(...)`** — message constructors from the canonical schema model.
+- **`Model.make(...)` / `ToolCallPart.make(...)` / `ToolResultPart.make(...)` / `ToolDefinition.make(...)`** — model and tool-related constructors from the canonical schema model.
+- **`LLMClient.prepare(request)`** — compile a request through protocol body construction, validation, and HTTP preparation without sending. Useful for inspection and testing.
+- **`LLMEvent.is.*`** — typed guards (`is.textDelta`, `is.toolCall`, `is.finish`, …) for filtering streams.
+- **`Image.generate({...})`** — generate images through a provider-neutral image request and response model.
+- **`ImageClient`** — Effect service and layer for image execution, parallel to `LLMClient`.
+
+## Caching
+
+Prompt caching is **on by default**. Every `LLMRequest` resolves to `cache: "auto"` unless the caller opts out with `cache: "none"`. Each protocol translates `CacheHint`s to its wire format (`cache_control` on Anthropic, `cachePoint` on Bedrock; OpenAI and Gemini do implicit caching server-side and don't need inline markers — auto is a no-op there).
+
+### Auto placement
+
+`"auto"` places three breakpoints — last tool definition, last system part, latest user message. The last-user-message boundary is the load-bearing detail: in a tool-use loop, a single user turn expands into many assistant/tool round-trips, all sharing that prefix. Caching at that boundary lets every intra-turn API call hit.
+
+The math justifies the default: Anthropic's 5-minute cache write is 1.25× base, read is 0.1×, so a single reuse within 5 minutes already wins. One-shot completions below the per-model minimum-cacheable-token threshold silently no-op on the wire, so the worst case is harmless.
+
+### Opting out
+
+```ts
+LLM.request({
+  model,
+  system,
+  prompt: "one-off question",
+  cache: "none",
+})
+```
+
+### Granular policy
+
+```ts
+cache: {
+  tools?: boolean,
+  system?: boolean,
+  messages?: "latest-user-message" | "latest-assistant" | { tail: number },
+  ttlSeconds?: number,         // ≥ 3600 → 1h on Anthropic/Bedrock; else 5m
+}
+```
+
+### Manual hints
+
+Inline `CacheHint` on any text / system / tool / tool-result part overrides automatic placement. The auto policy preserves manual hints; it only fills gaps.
+
+```ts
+LLM.request({
+  model,
+  system: [
+    { type: "text", text: "stable system prompt", cache: { type: "ephemeral" } },
+  ],
+  ...
+})
+```
+
+### Provider behavior table
+
+| Protocol                | `cache: "auto"`                                                           |
+| ----------------------- | ------------------------------------------------------------------------- |
+| Anthropic Messages      | emits up to 3 `cache_control` markers (4-breakpoint cap enforced)         |
+| Bedrock Converse        | emits up to 3 `cachePoint` blocks (4-breakpoint cap enforced)             |
+| OpenAI Chat / Responses | no-op (implicit caching above 1024 tokens)                                |
+| Gemini                  | no-op (implicit caching on 2.5+; explicit `CachedContent` is out-of-band) |
+
+Normalized cache usage is read back into `response.usage.cacheReadInputTokens` and `cacheWriteInputTokens` across every provider.
+
+## Providers
+
+Provider facades configure endpoint/auth/deployment details first, then expose model selectors that take only a model or deployment id. The selected model carries the executable route value used at runtime.
+
+```ts
+import { OpenAI, CloudflareAIGateway } from "@opencode-ai/ai/providers"
+
+const openai = OpenAI.configure({ apiKey: process.env.OPENAI_API_KEY }).responses("gpt-4o-mini")
+const gateway = CloudflareAIGateway.configure({
+  accountId: process.env.CLOUDFLARE_ACCOUNT_ID,
+  gatewayApiKey: process.env.CLOUDFLARE_API_TOKEN,
+}).model("workers-ai/@cf/meta/llama-3.1-8b-instruct")
+```
+
+Included providers: OpenAI, Anthropic, Google (Gemini), Google Vertex Gemini and Anthropic, Amazon Bedrock, Azure OpenAI, Cloudflare AI Gateway, Cloudflare Workers AI, GitHub Copilot, OpenRouter, xAI, plus generic OpenAI-compatible Chat and Responses entrypoints and an Anthropic Messages-compatible entrypoint.
+
+### Package-like entrypoints
+
+Native catalog integrations load provider behavior through package-like entrypoints. These are export paths from the same `@opencode-ai/ai` npm package, not independently published packages. Each entrypoint exports the same `model(modelID, settings)` contract, and `settings` contains serializable provider configuration plus common `headers`, `body`, and `limits` overlays.
+
+```ts
+import { model } from "@opencode-ai/ai/providers/openai/responses"
+
+const selected = model("gpt-5", {
+  apiKey: process.env.OPENAI_API_KEY,
+  transport: "websocket",
+  headers: { "x-application": "opencode" },
+  limits: { context: 200_000, output: 64_000 },
+})
+```
+
+OpenAI Chat and OpenAI Responses are separate semantic entrypoints:
+
+- `@opencode-ai/ai/providers/openai/chat`
+- `@opencode-ai/ai/providers/openai/responses`
+- `@opencode-ai/ai/providers/openai-compatible/responses`
+- `@opencode-ai/ai/providers/anthropic-compatible`
+- `@opencode-ai/ai/providers/google-vertex/gemini`
+- `@opencode-ai/ai/providers/google-vertex/chat`
+- `@opencode-ai/ai/providers/google-vertex/responses`
+- `@opencode-ai/ai/providers/google-vertex/messages`
+
+Responses HTTP versus WebSocket is a scoped `transport` setting on the OpenAI Responses entrypoint, not another entrypoint. Azure follows the same Chat/Responses split at `providers/azure/chat` and `providers/azure/responses`. Generic OpenAI-compatible Chat remains at `providers/openai-compatible`; compatible Responses is separate at `providers/openai-compatible/responses`. Generic Anthropic Messages-compatible providers use `providers/anthropic-compatible`, which the named Anthropic provider composes. Google Gemini and Amazon Bedrock expose their single native API through their existing provider paths.
+
+Vertex Gemini, Vertex Chat, Vertex Responses, and Vertex Messages are separate API entrypoints. All accept `project`, `location`, and an optional `accessToken`; when no explicit token or auth override is supplied they lazily use Google Application Default Credentials. Vertex Gemini instead selects express mode when `apiKey` or `GOOGLE_VERTEX_API_KEY` is present. Vertex Chat targets MaaS models through the OpenAI-compatible Chat Completions endpoint, while Vertex Responses targets Grok models and defaults `store` to `false` as required by Vertex. `providers/google-vertex` remains the default alias for `providers/google-vertex/gemini`.
+
+Tuned Vertex Gemini deployments use model ids shaped like `endpoints/1234567890` and require OAuth or ADC; Vertex express-mode API keys support publisher models only.
+
+```ts
+import { model } from "@opencode-ai/ai/providers/google-vertex/gemini"
+
+model("gemini-3.5-flash", { project: "my-project", location: "global" })
+```
+
+```ts
+import { model } from "@opencode-ai/ai/providers/google-vertex/chat"
+
+model("deepseek-ai/deepseek-v3.2-maas", { project: "my-project", location: "global" })
+```
+
+```ts
+import { model } from "@opencode-ai/ai/providers/google-vertex/responses"
+
+model("xai/grok-4.20-reasoning", { project: "my-project", location: "global" })
+```
+
+```ts
+import { model } from "@opencode-ai/ai/providers/google-vertex/messages"
+
+model("claude-sonnet-4-6", { project: "my-project", location: "global" })
+```
+
+Provider facades such as `OpenAI.configure(...).responses(...)` remain the direct application API. Package-like entrypoints are the self-similar loading contract used when a catalog selects behavior by export path.
+
+Other provider exports listed above remain direct facades until they explicitly implement the package-like contract. Exporting a provider facade does not implicitly make it a catalog-loadable provider package.
+
+## Provider options & HTTP overlays
+
+Three escape hatches in order of stability:
+
+1. **`generation`** — portable knobs (`maxTokens`, `temperature`, `topP`, `topK`, penalties, seed, stop).
+2. **`providerOptions: { <provider>: {...} }`** — typed-at-the-facade provider-specific knobs (OpenAI `promptCacheKey`, Anthropic `thinking`, Gemini `thinkingConfig`, OpenRouter routing).
+3. **`http: { body, headers, query }`** — last-resort serializable overlays merged into the final HTTP request. Reach for this only when a stable typed path doesn't yet exist.
+
+Route/provider defaults are overridden by request-level values for each axis.
+
+## Routes
+
+Adding a new model or deployment is usually 5-15 lines using `Route.make({ protocol, endpoint, auth, framing, ... })`. The route owns endpoint/auth/framing and the protocol owns body construction plus stream parsing. Transports are reusable IO templates that receive route endpoint/auth at compile time. Capability/catalog metadata lives outside this low-level package; unsupported request shapes fail during protocol lowering. See `AGENTS.md` for the architectural detail.
+
+## Effect
+
+This package is built on Effect. Public methods return `Effect` or `Stream`; provide `LLMClient.layer` for LLM dispatch and `ImageClient.layer` for image dispatch, then import the provider/protocol modules for the routes you use. The example at `example/tutorial.ts` is a runnable walkthrough.
+
+## See also
+
+- `AGENTS.md` — architecture, route construction, contributor guide
+- `STATUS.md` — native provider parity status and AI SDK migration gaps
+- `example/tutorial.ts` — runnable end-to-end walkthrough
+- `test/provider/*.test.ts` — fixture-first protocol tests; `*.recorded.test.ts` files cover live cassettes

packages/ai/STATUS.md

@@ -0,0 +1,108 @@
+# LLM Provider Parity Status
+
+Last reviewed: 2026-07-17
+
+This file tracks the gap between the native `@opencode-ai/ai` package and the AI SDK provider packages that opencode still depends on for many catalog/runtime paths.
+
+## Existing Status Sources
+
+| File                                | What it tracks                                                          | Limitation                                              |
+| ----------------------------------- | ----------------------------------------------------------------------- | ------------------------------------------------------- |
+| `packages/ai/DESIGN.md`             | Future clean-break API proposal for `@opencode-ai/ai`.                  | Not a provider parity tracker.                          |
+| `packages/ai/example/call-sites.md` | Route/value/provider-facade migration checklist and call-site sketches. | Architecture migration only; not AI SDK package parity. |
+
+## Current Implementation Snapshot
+
+| Native slice                       | Source                                                                                         | Current state                                                                                                                                                            | Main gaps                                                                                                                                                                                                                                                 |
+| ---------------------------------- | ---------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
+| OpenAI Chat                        | `src/protocols/openai-chat.ts`, `src/providers/openai.ts`                                      | Usable. Streams text, reasoning deltas, tool calls, usage, images, and common generation controls.                                                                       | No typed structured-output / `response_format` path. Limited typed OpenAI option surface compared with SDK escape hatches.                                                                                                                                |
+| OpenAI Responses HTTP              | `src/protocols/openai-responses.ts`, `src/providers/openai.ts`                                 | Usable. Supports hosted-tool event surfacing, reasoning replay metadata, GPT-5 defaults, and cache usage.                                                                | No explicit `previous_response_id` path. Typed options cover only a subset of Responses fields. Structured output is still mostly synthetic-tool based.                                                                                                   |
+| OpenAI Responses WebSocket         | `src/protocols/openai-responses.ts`, `src/route/transport/websocket.ts`                        | Present as `OpenAI.responsesWebSocket(...)`.                                                                                                                             | Runner/catalog support explicitly must not downgrade WebSocket routes; broader runtime selection is not complete.                                                                                                                                         |
+| OpenAI-compatible Chat             | `src/protocols/openai-compatible-chat.ts`, `src/providers/openai-compatible.ts`                | Usable for generic Chat and several profiles: Baseten, Cerebras, DeepInfra, DeepSeek, Fireworks, Groq, TogetherAI.                                                       | Family quirks are mostly endpoint defaults, not full typed behavior.                                                                                                                                                                                      |
+| OpenAI-compatible Responses        | `src/protocols/openai-compatible-responses.ts`, `src/providers/openai-compatible-responses.ts` | Usable for deployments that implement the OpenAI Responses wire protocol.                                                                                                | No named family profiles or recorded deployment coverage yet.                                                                                                                                                                                             |
+| Anthropic-compatible Messages      | `src/protocols/anthropic-messages.ts`, `src/providers/anthropic-compatible.ts`                 | Usable for deployments that implement the Anthropic Messages wire protocol. Named Anthropic composes this base; MiniMax M3 has recorded text and tool-loop coverage.       | No named compatible family profiles yet.                                                                                                                                                                                                                  |
+| Anthropic Messages                 | `src/protocols/anthropic-messages.ts`, `src/providers/anthropic.ts`                            | Usable. Supports tools, thinking, cache control, images, server-hosted tool events, and usage.                                                                           | Provider option surface is small. Beta/header handling, metadata, and newer Messages fields need a typed parity pass.                                                                                                                                     |
+| Gemini Developer API               | `src/protocols/gemini.ts`, `src/providers/google.ts`                                           | Usable for Google API key flow. Supports text, images, tools, thinking signatures, and cache usage.                                                                      | This is not Vertex. Typed provider options are narrow; many Gemini request fields currently require raw `http.body` overlays.                                                                                                                             |
+| Vertex Gemini                      | `src/protocols/gemini.ts`, `src/providers/google-vertex.ts`                                    | Usable through API-key express mode, explicit OAuth tokens, or ADC with project/location endpoint derivation, including tuned `endpoints/...` deployments.               | Core runner/catalog mapping and recorded provider coverage are missing.                                                                                                                                                                                   |
+| Vertex Chat                        | `src/protocols/openai-chat.ts`, `src/providers/google-vertex-chat.ts`                          | Usable for MaaS models through OpenAI-compatible Chat Completions with explicit OAuth tokens or ADC and project/location endpoint derivation.                            | Core runner/catalog mapping and recorded provider coverage are missing; MaaS family-specific request parity needs review.                                                                                                                                 |
+| Vertex Responses                   | `src/protocols/openai-responses.ts`, `src/providers/google-vertex-responses.ts`                | Usable for Grok models through OpenAI-compatible Responses with explicit OAuth tokens or ADC, project/location endpoint derivation, and storage disabled by default.     | Core runner/catalog mapping and recorded provider coverage are missing; stateful continuation is not supported by Vertex.                                                                                                                                 |
+| Vertex Messages                    | `src/protocols/anthropic-messages.ts`, `src/providers/google-vertex-messages.ts`               | Usable through explicit OAuth tokens or ADC, including global, regional, and `eu`/`us` multi-region endpoints.                                                           | Core runner/catalog mapping and recorded provider coverage are missing; Vertex-specific hosted-tool parity needs review.                                                                                                                                  |
+| Bedrock Converse                   | `src/protocols/bedrock-converse.ts`, `src/providers/amazon-bedrock.ts`                         | Partial but real. Supports AWS event-stream framing, SigV4 with supplied credentials, bearer auth, tools, reasoning signatures, media, cache points, and recorded tests. | Native facade does not mirror the AI SDK plugin's default AWS credential chain/profile behavior. Runner/catalog mapping is missing. Guardrails, inference profiles, region-specific model ID fixes, and model-specific request fields need a parity pass. |
+| Azure OpenAI                       | `src/providers/azure.ts` using OpenAI Chat/Responses protocols                                 | Partial. Supports resource/base URL setup, API key auth, API version query, Chat, and Responses selectors.                                                               | Core runner does not map `@ai-sdk/azure` to this native facade. AAD/token auth and Azure-specific endpoint variants need review.                                                                                                                          |
+| Cloudflare AI Gateway / Workers AI | `src/providers/cloudflare.ts`                                                                  | Present via OpenAI-compatible Chat routes.                                                                                                                               | Useful but not part of the critical AI SDK replacement set yet. Needs per-product recorded coverage before relying on it broadly.                                                                                                                         |
+| OpenRouter                         | `src/providers/openrouter.ts`                                                                  | Present with OpenRouter-specific usage/reasoning/prompt-cache options over Chat.                                                                                         | Responses-style OpenRouter support is absent.                                                                                                                                                                                                             |
+| xAI                                | `src/providers/xai.ts`                                                                         | Present with Responses and Chat selectors.                                                                                                                               | Needs package-parity review against the AI SDK xAI provider.                                                                                                                                                                                              |
+| GitHub Copilot                     | `src/providers/github-copilot.ts`                                                              | Present as explicit-base-URL OpenAI Chat/Responses facade.                                                                                                               | Runtime/catalog integration remains specialized and should stay separate from public OpenAI-compatible defaults.                                                                                                                                          |
+
+## V2 Runner Status
+
+`packages/core/src/session/runner/model.ts` currently resolves only this native subset from catalog `aisdk` metadata:
+
+| Catalog API                                         | Native route used today      |
+| --------------------------------------------------- | ---------------------------- |
+| `aisdk:@ai-sdk/openai`                              | `OpenAIResponses.route`      |
+| `aisdk:@ai-sdk/anthropic`                           | `AnthropicMessages.route`    |
+| `aisdk:@ai-sdk/openai-compatible` with explicit URL | `OpenAICompatibleChat.route` |
+
+Other `aisdk:` packages, including Google Vertex, Azure, and Bedrock, currently fall back through the AI SDK loader in the production runner. The dependency-free resolver seam rejects them with `SessionRunnerModel.UnsupportedPackageError`; they are not native route mappings yet.
+
+## AI SDK Package Parity Matrix
+
+| AI SDK package                    | Intended native target                                         | Status           | Biggest gaps                                                                                                                                                                                                        |
+| --------------------------------- | -------------------------------------------------------------- | ---------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
+| `@ai-sdk/openai`                  | `OpenAI.chat`, `OpenAI.responses`, `OpenAI.responsesWebSocket` | Partial / usable | Add complete typed option coverage, structured output strategy, explicit Responses continuation support, and runner route selection between Chat/Responses/WebSocket.                                               |
+| `@ai-sdk/openai-compatible`       | Generic OpenAI-compatible Chat and Responses                   | Partial / usable | Decide per-family namespace/profile behavior and runner API selection for providers that support Responses versus Chat only.                                                                                        |
+| `@ai-sdk/anthropic`               | `AnthropicMessages`                                            | Partial / usable | Finish Messages API parity for headers/betas/metadata/newer fields and document hosted-tool continuation expectations.                                                                                              |
+| `@ai-sdk/google`                  | Gemini Developer API                                           | Partial / usable | Add typed options for safety, response schema/modalities, cached content, grounding/search/code execution, and non-text output modes where supported.                                                               |
+| `@ai-sdk/google-vertex`           | Vertex Gemini namespace/facade                                 | Partial / usable | Add runner/catalog mapping, recorded coverage, and broader provider-option parity.                                                                                                                                  |
+| `@ai-sdk/google-vertex/anthropic` | Anthropic Messages over Vertex namespace/facade                | Partial / usable | Add runner/catalog mapping, recorded coverage, and Vertex-specific hosted-tool parity.                                                                                                                              |
+| `@ai-sdk/google-vertex/maas`      | Vertex Chat                                                    | Partial / usable | Add runner/catalog mapping, recorded coverage, and MaaS family-specific request parity.                                                                                                                             |
+| `@ai-sdk/google-vertex/xai`       | Vertex Chat / Responses                                        | Partial / usable | Decide Chat/Responses selection for catalog models, add runner mapping and recorded coverage, and review xAI-specific request options.                                                                              |
+| `@ai-sdk/azure`                   | Azure OpenAI Chat/Responses facade                             | Partial          | Map runner/catalog metadata to native Azure, handle resourceName/baseURL/apiVersion variants, add AAD/token auth story, and verify Chat vs Responses deployment selection.                                          |
+| `@ai-sdk/amazon-bedrock`          | Bedrock Converse                                               | Partial          | Add default AWS credential chain/profile support, region/inference-profile model ID handling, provider option parity via `additionalModelRequestFields`, guardrails/performance config, and runner/catalog mapping. |
+| `@ai-sdk/amazon-bedrock/mantle`   | Bedrock Mantle OpenAI-compatible Chat/Responses namespace      | Missing          | Decide native Mantle shape, likely separate from Converse because it uses OpenAI-compatible Chat/Responses semantics over Bedrock. Add package mapping and tests.                                                   |
+
+## Highest-Risk Gaps
+
+1. Runner support is narrower than the LLM package. The package has native provider facades for Google, Azure, and Bedrock, but the V2 Session runner only maps OpenAI, Anthropic, and explicit OpenAI-compatible Chat from `aisdk` catalog metadata.
+2. OpenAI-compatible Responses is available as a separate package entrypoint, but the V2 runner still maps `@ai-sdk/openai-compatible` to Chat only. Catalog selection must become API-aware before Responses deployments can use it.
+3. Bedrock native auth is not AI SDK parity. The AI SDK plugin uses the default AWS provider chain, profile, container credentials, and Bedrock bearer token env behavior. Native Bedrock currently expects explicit credentials or bearer auth on the facade.
+4. Vertex Gemini, Vertex Chat, Vertex Responses, and Vertex Messages now have native package entrypoints, but the core runner does not map catalog metadata to them yet and recorded provider coverage is still missing.
+5. Azure is only a provider facade, not a full runtime replacement. Native Azure exists, but the catalog runner does not select it, and token auth/resource variants need review.
+6. Provider option typing is uneven. OpenAI, Anthropic, Gemini, Bedrock, and OpenRouter each expose a small typed subset plus raw HTTP overlays; this is useful but not equivalent to AI SDK provider option coverage.
+7. Structured output is not provider-native yet. `LLM.generateObject` still uses a synthetic tool strategy, while the future design expects native structured output where reliable and tool fallback where needed.
+8. Package/namespace boundaries for the current native loading set are explicit in docs and exports. Other exported provider facades are not catalog package entrypoints until they implement the contract. Vertex xAI still needs catalog API selection; the missing native boundary is Bedrock Mantle.
+9. Recorded coverage is uneven. OpenAI, Anthropic, Gemini, Bedrock Converse, Cloudflare, OpenRouter, and several OpenAI-compatible Chat providers have cassettes. Azure, Vertex, and Mantle need first-class recorded scenarios before switching defaults.
+
+## Native Namespace Shape
+
+These are implementation/API slices, not separate npm packages.
+
+| API slice                     | Package-like entrypoint                                 | Purpose                                                                      |
+| ----------------------------- | ------------------------------------------------------- | ---------------------------------------------------------------------------- |
+| OpenAI Chat                   | `@opencode-ai/ai/providers/openai/chat`                 | OpenAI `/chat/completions` semantics.                                        |
+| OpenAI Responses              | `@opencode-ai/ai/providers/openai/responses`            | OpenAI `/responses` semantics with HTTP/WebSocket selected through settings. |
+| OpenAI-compatible Chat        | `@opencode-ai/ai/providers/openai-compatible`           | Generic OpenAI-compatible `/chat/completions`.                               |
+| OpenAI-compatible Responses   | `@opencode-ai/ai/providers/openai-compatible/responses` | Generic OpenAI-compatible `/responses`.                                      |
+| Anthropic-compatible Messages | `@opencode-ai/ai/providers/anthropic-compatible`        | Generic Anthropic-compatible `/messages`.                                    |
+| Anthropic Messages            | `@opencode-ai/ai/providers/anthropic`                   | Anthropic Messages API.                                                      |
+| Gemini Developer API          | `@opencode-ai/ai/providers/google`                      | Google AI Studio Gemini API.                                                 |
+| Vertex Gemini                 | `@opencode-ai/ai/providers/google-vertex/gemini`        | Vertex Gemini API; `providers/google-vertex` is the default alias.           |
+| Vertex Chat                   | `@opencode-ai/ai/providers/google-vertex/chat`          | Vertex OpenAI-compatible Chat Completions for MaaS models.                   |
+| Vertex Responses              | `@opencode-ai/ai/providers/google-vertex/responses`     | Vertex OpenAI-compatible Responses for Grok models.                          |
+| Vertex Messages               | `@opencode-ai/ai/providers/google-vertex/messages`      | Vertex-hosted Anthropic Messages API.                                        |
+| Bedrock Converse              | `@opencode-ai/ai/providers/amazon-bedrock`              | AWS Bedrock Converse API.                                                    |
+| Bedrock Mantle                | Missing                                                 | AWS Bedrock Mantle OpenAI-compatible APIs.                                   |
+| Azure OpenAI Chat             | `@opencode-ai/ai/providers/azure/chat`                  | Azure specialization of OpenAI Chat.                                         |
+| Azure OpenAI Responses        | `@opencode-ai/ai/providers/azure/responses`             | Azure specialization of OpenAI Responses.                                    |
+
+## Suggested Next Work Slices
+
+1. Add native runner/catalog mappings for `@ai-sdk/azure`, `@ai-sdk/google`, and `@ai-sdk/amazon-bedrock` where the existing native facades are already close.
+2. Add API-aware runner/catalog selection between OpenAI-compatible Chat and Responses.
+3. Bring Bedrock native auth/config to AI SDK parity: region, profile, default AWS credential chain, bearer token env, endpoint override, and cross-region inference profile handling.
+4. Add runner/catalog mappings and recorded scenarios for the native Vertex Gemini, Chat, Responses, and Messages entrypoints.
+5. Decide Chat/Responses selection for `@ai-sdk/google-vertex/xai` catalog models.
+6. Add Bedrock Mantle as a separate OpenAI-compatible Bedrock namespace after deciding whether it uses Chat, Responses, or both by model.
+7. Expand typed provider options from the existing V1 lowerer knowledge in `packages/core/src/v1/config/provider-options.ts` before adding more raw overlay examples.
+8. Add recorded provider tests for Azure, Vertex Gemini, Vertex Chat, Vertex Responses, Vertex Messages, Bedrock credential-chain behavior, and Mantle before making native runtime the default for those packages.

packages/ai/example/call-sites.md

@@ -7,7 +7,7 @@ values directly.
 ## Conversation Summary
 
 Kit and Aidan want provider-specific LLM behavior to move out of opencode's AI
-SDK transform path and into `packages/llm` where possible. The goal is not a big
+SDK transform path and into `packages/ai` where possible. The goal is not a big
 generic transform layer; the goal is small composable route definitions backed by
 recorded golden tests.
 
@@ -342,14 +342,51 @@ const response =
   )
 ```
 
-HTTP versus WebSocket is represented as named route selectors, not as model or
-request overrides. Same protocol, different transport, different route:
+For direct provider-facade calls, HTTP versus WebSocket is represented as named
+route selectors, not as model or request overrides. Same protocol, different
+transport, different route:
 
 ```ts
 OpenAI.responses("gpt-4o")
 OpenAI.responsesWebSocket("gpt-4o")
 ```
 
+The package-like OpenAI Responses entrypoint instead keeps transport scoped to
+Responses settings while preserving the same `model(...)` contract:
+
+```ts
+import { model } from "@opencode-ai/ai/providers/openai/responses"
+
+model("gpt-4o", { apiKey, transport: "websocket" })
+```
+
+Vertex keeps Gemini, Chat, Responses, and Messages as separate package-like entrypoints,
+while sharing project/location resolution and ADC authentication internally:
+
+```ts
+import { model } from "@opencode-ai/ai/providers/google-vertex/gemini"
+
+model("gemini-3.5-flash", { project, location: "global" })
+```
+
+```ts
+import { model } from "@opencode-ai/ai/providers/google-vertex/chat"
+
+model("deepseek-ai/deepseek-v3.2-maas", { project, location: "global" })
+```
+
+```ts
+import { model } from "@opencode-ai/ai/providers/google-vertex/responses"
+
+model("xai/grok-4.20-reasoning", { project, location: "global" })
+```
+
+```ts
+import { model } from "@opencode-ai/ai/providers/google-vertex/messages"
+
+model("claude-sonnet-4-6", { project, location: "global" })
+```
+
 The client should not require a different public layer just because a selected
 route uses WebSocket. Use one `LLMClient.layer` with HTTP and WebSocket runtime
 capabilities available; routes that do not need WebSocket simply never touch it.
@@ -468,10 +505,10 @@ const model =
 ```
 
 That boundary can branch on durable config/catalog metadata and call typed
-provider APIs directly. Transport selection belongs there too: map metadata like
-`endpoint.websocket` to `OpenAI.responsesWebSocket(apiModelID)`; otherwise use
-the normal `OpenAI.responses(apiModelID)` route. The client runtime only executes
-the route carried by the model.
+provider APIs directly. A direct provider-facade boundary maps metadata like
+`endpoint.websocket` to `OpenAI.responsesWebSocket(apiModelID)`. A package-loading
+boundary passes `transport: "websocket"` to the OpenAI Responses entrypoint.
+The client runtime only executes the route carried by the resulting model.
 
 ## Competitive Shape
 
@@ -507,8 +544,9 @@ App boundary = explicit durable-config -> typed-provider call
   id.
 - No `model(id, overrides)` escape hatch. Model selection takes the model id;
   endpoint/auth/deployment customization happens by configuring the route first.
-- No transport override on model/request. HTTP SSE versus WebSocket is a named
-  route selector such as `responses` versus `responsesWebSocket`.
+- No transport override on an executable model or request. Direct provider
+  facades use `responses` versus `responsesWebSocket`; the package-like Responses
+  entrypoint maps its scoped `transport` setting before constructing the model.
 - No separate public `LLMClient.layerWithWebSocket`. The runtime should expose one
   client layer with the available transport capabilities.
 - No executable `ModelRef`. The executable handle is `Model`; durable model

packages/ai/example/tutorial.ts

@@ -1,12 +1,12 @@
 import { Config, Effect, Formatter, Layer, Schema, Stream } from "effect"
-import { LLM, LLMClient, ProviderID, Tool } from "@opencode-ai/llm"
-import { Route, Auth, Endpoint, Framing, Protocol, RequestExecutor, WebSocketExecutor } from "@opencode-ai/llm/route"
-import { OpenAI } from "@opencode-ai/llm/providers"
+import { LLM, LLMClient, Message, ProviderID, Tool, ToolRuntime } from "@opencode-ai/ai"
+import { Route, Auth, Endpoint, Framing, Protocol, RequestExecutor, WebSocketExecutor } from "@opencode-ai/ai/route"
+import { OpenAI } from "@opencode-ai/ai/providers"
 
 /**
  * A runnable walkthrough of the LLM package use-site API.
  *
- * Run from `packages/llm` with an OpenAI key in the environment:
+ * Run from `packages/ai` with an OpenAI key in the environment:
  *
  *   OPENAI_API_KEY=... bun example/tutorial.ts
  *
@@ -84,9 +84,9 @@ const streamText = LLM.stream(request).pipe(
   Stream.runDrain,
 )
 
-// 5. Tools are typed with Effect Schema. Passing tools to `LLMClient.stream`
-// adds their definitions to the request and dispatches matching tool calls.
-// Add `stopWhen` to opt into follow-up model rounds after tool results.
+// 5. Tools are typed with Effect Schema. Provider turns remain explicit:
+// advertise definitions on the request, stream one turn, dispatch local calls,
+// then persist/build follow-up history in the enclosing product flow.
 const tools = {
   get_weather: Tool.make({
     description: "Get current weather for a city.",
@@ -96,24 +96,33 @@ const tools = {
   }),
 }
 
-const streamWithTools = LLM.stream({
-  request: LLM.request({
+const streamWithTools = Effect.gen(function* () {
+  const request = LLM.request({
     model,
     prompt: "Use get_weather for San Francisco, then answer in one sentence.",
     generation: { maxTokens: 80, temperature: 0 },
-  }),
-  tools,
-  stopWhen: LLM.stepCountIs(3),
-}).pipe(
-  Stream.tap((event) =>
-    Effect.sync(() => {
-      if (event.type === "tool-call") console.log("tool call", event.name, event.input)
-      if (event.type === "tool-result") console.log("tool result", event.name, event.result)
-      if (event.type === "text-delta") process.stdout.write(event.text)
-    }),
-  ),
-  Stream.runDrain,
-)
+    tools: Tool.toDefinitions(tools),
+  })
+  const events = Array.from(yield* LLM.stream(request).pipe(Stream.runCollect))
+  for (const event of events) {
+    if (event.type === "tool-call") console.log("tool call", event.name, event.input)
+    if (event.type === "text-delta") process.stdout.write(event.text)
+    if (event.type !== "tool-call" || event.providerExecuted) continue
+    const dispatched = yield* ToolRuntime.dispatch(tools, event)
+    console.log("tool result", event.name, dispatched.result)
+
+    // A durable agent would persist these messages before starting another
+    // raw model turn. This tutorial keeps the boundary visible instead.
+    const followUp = LLM.updateRequest(request, {
+      messages: [
+        ...request.messages,
+        Message.assistant([event]),
+        Message.tool({ ...event, result: dispatched.result }),
+      ],
+    })
+    console.log("follow-up history messages:", followUp.messages.length)
+  }
+})
 
 // 6. `generateObject` is the structured-output helper. It forces a synthetic
 // tool call internally, so the same call site works across providers instead of
@@ -229,7 +238,7 @@ const inspectFakeProvider = Effect.gen(function* () {
 // Provide the LLM runtime and the HTTP request executor once. Keep one path
 // enabled at a time so the tutorial can demonstrate generate, prepare, stream,
 // or tool-loop behavior without spending tokens on every example.
-const requestExecutorLayer = RequestExecutor.defaultLayer
+const requestExecutorLayer = RequestExecutor.fetchLayer
 const llmDeps = Layer.mergeAll(requestExecutorLayer, WebSocketExecutor.layer)
 const llmClientLayer = LLMClient.layer.pipe(Layer.provide(llmDeps))
 

packages/ai/package.json

@@ -0,0 +1,37 @@
+{
+  "$schema": "https://json.schemastore.org/package.json",
+  "version": "1.17.20",
+  "name": "@opencode-ai/ai",
+  "type": "module",
+  "license": "MIT",
+  "scripts": {
+    "setup:recording-env": "bun run script/setup-recording-env.ts",
+    "test": "bun test --timeout 30000 --only-failures",
+    "typecheck": "tsgo --noEmit",
+    "build": "tsc -p tsconfig.build.json"
+  },
+  "files": [
+    "dist"
+  ],
+  "exports": {
+    ".": "./src/index.ts",
+    "./*": "./src/*.ts"
+  },
+  "devDependencies": {
+    "@clack/prompts": "1.0.0-alpha.1",
+    "@effect/platform-node": "catalog:",
+    "@opencode-ai/http-recorder": "workspace:*",
+    "@tsconfig/bun": "catalog:",
+    "@types/bun": "catalog:",
+    "@typescript/native-preview": "catalog:",
+    "typescript": "catalog:"
+  },
+  "dependencies": {
+    "@smithy/eventstream-codec": "4.2.14",
+    "@smithy/util-utf8": "4.2.2",
+    "@opencode-ai/schema": "workspace:*",
+    "aws4fetch": "1.0.20",
+    "effect": "catalog:",
+    "google-auth-library": "10.5.0"
+  }
+}

packages/ai/script/publish.ts

@@ -0,0 +1,38 @@
+#!/usr/bin/env bun
+import { Script } from "@opencode-ai/script"
+import { $ } from "bun"
+import { fileURLToPath } from "url"
+
+const dir = fileURLToPath(new URL("..", import.meta.url))
+process.chdir(dir)
+
+async function published(name: string, version: string) {
+  return (await $`npm view ${name}@${version} version`.nothrow()).exitCode === 0
+}
+
+await $`bun run build`
+const originalText = await Bun.file("package.json").text()
+const pkg = JSON.parse(originalText) as {
+  name: string
+  version: string
+  exports: Record<string, string>
+}
+if (await published(pkg.name, pkg.version)) {
+  console.log(`already published ${pkg.name}@${pkg.version}`)
+} else {
+  for (const [key, value] of Object.entries(pkg.exports)) {
+    const file = value.replace("./src/", "./dist/").replace(".ts", "")
+    // @ts-ignore
+    pkg.exports[key] = {
+      import: file + ".js",
+      types: file + ".d.ts",
+    }
+  }
+  await Bun.write("package.json", JSON.stringify(pkg, null, 2))
+  try {
+    await $`bun pm pack`
+    await $`npm publish *.tgz --tag ${Script.channel} --access public`
+  } finally {
+    await Bun.write("package.json", originalText)
+  }
+}

packages/ai/script/setup-recording-env.ts

@@ -161,6 +161,18 @@ const PROVIDERS: ReadonlyArray<Provider> = [
     vars: [{ name: "TOGETHER_AI_API_KEY" }],
     validate: (env) => validateBearer("https://api.together.xyz/v1/models", Redacted.make(env.TOGETHER_AI_API_KEY)),
   },
+  {
+    id: "minimax",
+    label: "MiniMax",
+    tier: "compatible",
+    note: "Anthropic-compatible Messages text/tool recorded tests",
+    vars: [{ name: "MINIMAX_API_KEY" }],
+    validate: (env) =>
+      HttpClientRequest.get("https://api.minimax.io/anthropic/v1/models").pipe(
+        HttpClientRequest.setHeader("x-api-key", Redacted.value(Redacted.make(env.MINIMAX_API_KEY))),
+        executeRequest,
+      ),
+  },
   {
     id: "mistral",
     label: "Mistral",

packages/ai/src/image-client.ts

@@ -0,0 +1,34 @@
+import { Context, Effect, Layer } from "effect"
+import { RequestExecutor } from "./route/executor"
+import type { ImageRequest, ImageResponse } from "./image"
+import type { LLMError } from "./schema"
+
+export type Execute = RequestExecutor.Interface["execute"]
+
+export interface Interface {
+  readonly generate: (request: ImageRequest) => Effect.Effect<ImageResponse, LLMError>
+}
+
+export class Service extends Context.Service<Service, Interface>()("@opencode/ImageClient") {}
+
+export const generate = (request: ImageRequest): Effect.Effect<ImageResponse, LLMError> =>
+  Effect.gen(function* () {
+    const client = yield* Service
+    return yield* client.generate(request)
+  }) as Effect.Effect<ImageResponse, LLMError>
+
+export const layer: Layer.Layer<Service, never, RequestExecutor.Service> = Layer.effect(
+  Service,
+  Effect.gen(function* () {
+    const executor = yield* RequestExecutor.Service
+    return Service.of({
+      generate: (request) => request.model.route.generate(request, executor.execute),
+    })
+  }),
+)
+
+export const ImageClient = {
+  Service,
+  layer,
+  generate,
+} as const

packages/ai/src/image.ts

@@ -0,0 +1,116 @@
+import { Effect, Schema } from "effect"
+import { HttpOptions, InvalidRequestReason, LLMError, ModelID, ProviderID, ProviderMetadata, Usage } from "./schema"
+import { ImageClient, type Execute as ImageExecute } from "./image-client"
+
+export interface ImageRoute {
+  readonly id: string
+  readonly generate: (request: ImageRequest, execute: ImageExecute) => Effect.Effect<ImageResponse, LLMError>
+}
+
+export class ImageModel {
+  readonly id: ModelID
+  readonly provider: ProviderID
+  readonly route: ImageRoute
+  readonly defaults?: ImageModelDefaults
+
+  constructor(input: ImageModel.Input) {
+    this.id = input.id
+    this.provider = input.provider
+    this.route = input.route
+    this.defaults = input.defaults
+  }
+
+  static make(input: ImageModel.MakeInput) {
+    return new ImageModel({
+      id: ModelID.make(input.id),
+      provider: ProviderID.make(input.provider),
+      route: input.route,
+      defaults: input.defaults,
+    })
+  }
+}
+
+export namespace ImageModel {
+  export interface Input {
+    readonly id: ModelID
+    readonly provider: ProviderID
+    readonly route: ImageRoute
+    readonly defaults?: ImageModelDefaults
+  }
+
+  export interface MakeInput extends Omit<Input, "id" | "provider"> {
+    readonly id: string | ModelID
+    readonly provider: string | ProviderID
+  }
+}
+
+export interface ImageModelDefaults {
+  readonly providerOptions?: Record<string, Record<string, unknown>>
+  readonly http?: HttpOptions
+}
+
+export const ImageModelSchema = Schema.declare((value): value is ImageModel => value instanceof ImageModel, {
+  expected: "Image.Model",
+})
+
+export const ImageSize = Schema.Struct({
+  width: Schema.Int.check(Schema.isGreaterThanOrEqualTo(1)),
+  height: Schema.Int.check(Schema.isGreaterThanOrEqualTo(1)),
+}).annotate({ identifier: "Image.Size" })
+export type ImageSize = Schema.Schema.Type<typeof ImageSize>
+
+export class ImageRequest extends Schema.Class<ImageRequest>("Image.Request")({
+  model: ImageModelSchema,
+  prompt: Schema.String,
+  count: Schema.optional(Schema.Int.check(Schema.isGreaterThanOrEqualTo(1))),
+  size: Schema.optional(ImageSize),
+  aspectRatio: Schema.optional(Schema.String),
+  seed: Schema.optional(Schema.Number),
+  providerOptions: Schema.optional(Schema.Record(Schema.String, Schema.Record(Schema.String, Schema.Unknown))),
+  http: Schema.optional(HttpOptions),
+  metadata: Schema.optional(Schema.Record(Schema.String, Schema.Unknown)),
+}) {}
+
+export type ImageRequestInput = Omit<ConstructorParameters<typeof ImageRequest>[0], "http"> & {
+  readonly http?: HttpOptions.Input
+}
+
+export class GeneratedImage extends Schema.Class<GeneratedImage>("Image.Generated")({
+  mediaType: Schema.String,
+  data: Schema.Union([Schema.String, Schema.Uint8Array]),
+  providerMetadata: Schema.optional(ProviderMetadata),
+}) {}
+
+export class ImageResponse extends Schema.Class<ImageResponse>("Image.Response")({
+  images: Schema.Array(GeneratedImage),
+  usage: Schema.optional(Usage),
+  providerMetadata: Schema.optional(ProviderMetadata),
+}) {
+  get image() {
+    return this.images[0]
+  }
+}
+
+export const request = (input: ImageRequest | ImageRequestInput) => {
+  if (input instanceof ImageRequest) return input
+  return new ImageRequest({
+    ...input,
+    http: input.http === undefined ? undefined : HttpOptions.make(input.http),
+  })
+}
+
+export const generate = (input: ImageRequest | ImageRequestInput) =>
+  Effect.try({
+    try: () => request(input),
+    catch: (error) =>
+      new LLMError({
+        module: "Image",
+        method: "generate",
+        reason: new InvalidRequestReason({ message: error instanceof Error ? error.message : String(error) }),
+      }),
+  }).pipe(Effect.flatMap(ImageClient.generate))
+
+export const Image = {
+  request,
+  generate,
+} as const

packages/ai/src/index.ts

@@ -0,0 +1,39 @@
+export { LLMClient } from "./route/client"
+export { ImageClient } from "./image-client"
+export { Auth } from "./route/auth"
+export { Provider } from "./provider"
+export { ProviderPackage } from "./provider-package"
+export { isContextOverflow, isContextOverflowFailure } from "./provider-error"
+export type {
+  RouteModelInput,
+  RouteRoutedModelInput,
+  Interface as LLMClientShape,
+  Service as LLMClientService,
+} from "./route/client"
+export * from "./schema"
+export { GeneratedImage, ImageModel, ImageRequest, ImageResponse, ImageSize } from "./image"
+export type { ImageModelDefaults, ImageRequestInput, ImageRoute } from "./image"
+export { Image } from "./image"
+export { Tool, ToolFailure, toDefinitions } from "./tool"
+export { ToolRuntime } from "./tool-runtime"
+export type { DispatchResult as ToolDispatchResult, ToolSettlement } from "./tool-runtime"
+export type {
+  AnyExecutableTool,
+  AnyTool,
+  ExecutableTool,
+  ExecutableTools,
+  Definition as ToolShape,
+  ToolExecute,
+  ToolExecuteContext,
+  ToolModelOutputInput,
+  Tools,
+  ToolSchema,
+  ToolToModelOutput,
+} from "./tool"
+export * as LLM from "./llm"
+export type {
+  Definition as ProviderDefinition,
+  ModelFactory as ProviderModelFactory,
+  ModelOptions as ProviderModelOptions,
+} from "./provider"
+export type { Definition as ProviderPackageDefinition, Settings as ProviderPackageSettings } from "./provider-package"

packages/ai/src/llm.ts

@@ -16,7 +16,7 @@ import {
   type ContentPart,
   ToolResultPart,
 } from "./schema"
-import { make as makeTool, type ToolSchema } from "./tool"
+import { make as makeTool, toDefinitions, type ToolSchema } from "./tool"
 
 export type ModelInput = SchemaModelInput
 
@@ -46,8 +46,6 @@ export const generate = LLMClient.generate
 
 export const stream = LLMClient.stream
 
-export const stepCountIs = LLMClient.stepCountIs
-
 export const requestInput = (input: LLMRequest): RequestInput => ({
   ...LLMRequest.input(input),
 })
@@ -115,13 +113,10 @@ const runGenerateObject = Effect.fn("LLM.generateObject")(function* (
 ) {
   const baseRequest = request(options)
   const generateRequest = LLMRequest.update(baseRequest, {
+    tools: toDefinitions({ [GENERATE_OBJECT_TOOL_NAME]: tool }),
     toolChoice: ToolChoice.named(GENERATE_OBJECT_TOOL_NAME),
   })
-  const response = yield* LLMClient.generate({
-    request: generateRequest,
-    tools: { [GENERATE_OBJECT_TOOL_NAME]: tool },
-    toolExecution: "none",
-  })
+  const response = yield* LLMClient.generate(generateRequest)
   const call = response.toolCalls.find(
     (event) => LLMEvent.is.toolCall(event) && event.name === GENERATE_OBJECT_TOOL_NAME,
   )

packages/ai/src/protocols.ts

@@ -0,0 +1 @@
+export * from "./protocols/index"

packages/ai/src/protocols/anthropic-messages.ts

@@ -5,21 +5,25 @@ import { Endpoint } from "../route/endpoint"
 import { Framing } from "../route/framing"
 import { Protocol } from "../route/protocol"
 import {
+  LLMError,
   LLMEvent,
   Usage,
   type CacheHint,
   type FinishReason,
+  type JsonSchema,
   type LLMRequest,
   type MediaPart,
   type ProviderMetadata,
   type ToolCallPart,
   type ToolDefinition,
-  type ToolResultContentPart,
+  type ToolContent,
   type ToolResultPart,
 } from "../schema"
 import { JsonObject, optionalArray, optionalNull, ProviderShared } from "./shared"
+import { classifyProviderFailure } from "../provider-error"
 import * as Cache from "./utils/cache"
 import { Lifecycle } from "./utils/lifecycle"
+import { ToolSchemaProjection } from "./utils/tool-schema"
 import { ToolStream } from "./utils/tool-stream"
 
 const ADAPTER = "anthropic-messages"
@@ -128,6 +132,7 @@ type AnthropicToolResultBlock = Schema.Schema.Type<typeof AnthropicToolResultBlo
 const AnthropicMessage = Schema.Union([
   Schema.Struct({ role: Schema.Literal("user"), content: Schema.Array(AnthropicUserBlock) }),
   Schema.Struct({ role: Schema.Literal("assistant"), content: Schema.Array(AnthropicAssistantBlock) }),
+  Schema.Struct({ role: Schema.Literal("system"), content: Schema.Array(AnthropicTextBlock) }),
 ]).pipe(Schema.toTaggedUnion("role"))
 type AnthropicMessage = Schema.Schema.Type<typeof AnthropicMessage>
 
@@ -144,9 +149,22 @@ const AnthropicToolChoice = Schema.Union([
   Schema.Struct({ type: Schema.tag("tool"), name: Schema.String }),
 ])
 
-const AnthropicThinking = Schema.Struct({
-  type: Schema.tag("enabled"),
-  budget_tokens: Schema.Number,
+const AnthropicThinking = Schema.Union([
+  Schema.Struct({
+    type: Schema.tag("enabled"),
+    budget_tokens: Schema.Number,
+  }),
+  Schema.Struct({
+    type: Schema.tag("adaptive"),
+    display: Schema.optional(Schema.Literals(["summarized", "omitted"])),
+  }),
+  Schema.Struct({
+    type: Schema.tag("disabled"),
+  }),
+])
+
+const AnthropicOutputConfig = Schema.Struct({
+  effort: Schema.optional(Schema.String),
 })
 
 const AnthropicBodyFields = {
@@ -162,8 +180,9 @@ const AnthropicBodyFields = {
   top_k: Schema.optional(Schema.Number),
   stop_sequences: optionalArray(Schema.String),
   thinking: Schema.optional(AnthropicThinking),
+  output_config: Schema.optional(AnthropicOutputConfig),
 }
-const AnthropicMessagesBody = Schema.Struct(AnthropicBodyFields)
+export const AnthropicMessagesBody = Schema.Struct(AnthropicBodyFields)
 export type AnthropicMessagesBody = Schema.Schema.Type<typeof AnthropicMessagesBody>
 
 const AnthropicUsage = Schema.Struct({
@@ -254,10 +273,10 @@ const signatureFromMetadata = (metadata: ProviderMetadata | undefined): string |
   return typeof anthropic.signature === "string" ? anthropic.signature : undefined
 }
 
-const lowerTool = (breakpoints: Cache.Breakpoints, tool: ToolDefinition): AnthropicTool => ({
+const lowerTool = (breakpoints: Cache.Breakpoints, tool: ToolDefinition, inputSchema: JsonSchema): AnthropicTool => ({
   name: tool.name,
   description: tool.description,
-  input_schema: tool.inputSchema,
+  input_schema: inputSchema,
   cache_control: cacheControl(breakpoints, tool.cache),
 })
 
@@ -301,14 +320,17 @@ const lowerServerToolResult = Effect.fn("AnthropicMessages.lowerServerToolResult
 })
 
 const lowerImage = Effect.fn("AnthropicMessages.lowerImage")(function* (part: MediaPart) {
-  if (!part.mediaType.startsWith("image/"))
-    return yield* invalid(`Anthropic Messages user media content only supports images`)
+  const media = yield* ProviderShared.validateMedia(
+    "Anthropic Messages",
+    part,
+    new Set<string>(ProviderShared.IMAGE_MIMES),
+  )
   return {
     type: "image" as const,
     source: {
       type: "base64" as const,
-      media_type: part.mediaType,
-      data: ProviderShared.mediaBase64(part),
+      media_type: media.mime,
+      data: media.base64,
     },
   } satisfies AnthropicImageBlock
 })
@@ -316,19 +338,22 @@ const lowerImage = Effect.fn("AnthropicMessages.lowerImage")(function* (part: Me
 // Tool results may carry structured text/images. Keep media as provider-native
 // content instead of JSON-stringifying base64 into a prompt string.
 const lowerToolResultContentItem = Effect.fn("AnthropicMessages.lowerToolResultContentItem")(function* (
-  item: ToolResultContentPart,
+  item: ToolContent,
 ) {
   if (item.type === "text") return { type: "text" as const, text: item.text } satisfies AnthropicTextBlock
-  if (item.mediaType.startsWith("image/"))
-    return {
-      type: "image" as const,
-      source: {
-        type: "base64" as const,
-        media_type: item.mediaType,
-        data: ProviderShared.mediaBase64(item),
-      },
-    } satisfies AnthropicImageBlock
-  return yield* invalid(`Anthropic Messages tool-result media content only supports images, got ${item.mediaType}`)
+  const media = yield* ProviderShared.validateToolFile(
+    "Anthropic Messages",
+    item,
+    new Set<string>(ProviderShared.IMAGE_MIMES),
+  )
+  return {
+    type: "image" as const,
+    source: {
+      type: "base64" as const,
+      media_type: media.mime,
+      data: media.base64,
+    },
+  } satisfies AnthropicImageBlock
 })
 
 const lowerToolResultContent = Effect.fn("AnthropicMessages.lowerToolResultContent")(function* (part: ToolResultPart) {
@@ -336,17 +361,82 @@ const lowerToolResultContent = Effect.fn("AnthropicMessages.lowerToolResultConte
   // with existing cassettes and provider expectations.
   if (part.result.type !== "content") return ProviderShared.toolResultText(part)
   // Preserve the narrowed array element type when compiled through a consumer package.
-  const content: ReadonlyArray<ToolResultContentPart> = part.result.value
+  const content: ReadonlyArray<ToolContent> = part.result.value
   return yield* Effect.forEach(content, lowerToolResultContentItem)
 })
 
+// Mid-conversation system messages are a native Claude API feature only for
+// Opus 4.8. Other Anthropic models intentionally use the same visible wrapped-
+// user fallback as non-Anthropic routes rather than sending a role they reject.
+const supportsNativeSystemUpdates = (request: LLMRequest) => String(request.model.id) === "claude-opus-4-8"
+
+const endsInServerToolUse = (message: LLMRequest["messages"][number]) => {
+  const last = message.content.at(-1)
+  return message.role === "assistant" && last?.type === "tool-call" && last.providerExecuted === true
+}
+
+const canUseNativeSystemUpdate = (messages: LLMRequest["messages"], index: number) => {
+  const previous = messages[index - 1]
+  const next = messages[index + 1]
+  return (
+    previous !== undefined &&
+    previous.role !== "system" &&
+    (previous.role === "user" || previous.role === "tool" || endsInServerToolUse(previous)) &&
+    next?.role !== "system" &&
+    (next === undefined || next.role === "assistant")
+  )
+}
+
+const splitsLocalToolResults = (messages: LLMRequest["messages"], index: number) => {
+  const pending = new Set<string>()
+  for (const message of messages.slice(0, index)) {
+    for (const part of message.content) {
+      if (message.role === "assistant" && part.type === "tool-call" && part.providerExecuted !== true)
+        pending.add(part.id)
+      if (message.role === "tool" && part.type === "tool-result") pending.delete(part.id)
+    }
+  }
+  return pending.size > 0
+}
+
+const lowerNativeSystemUpdate = Effect.fn("AnthropicMessages.lowerNativeSystemUpdate")(function* (
+  message: LLMRequest["messages"][number],
+  breakpoints: Cache.Breakpoints,
+) {
+  const content = yield* ProviderShared.systemUpdateText("Anthropic Messages", message)
+  return {
+    role: "system" as const,
+    content: content.map((part) => ({
+      type: "text" as const,
+      text: part.text,
+      cache_control: cacheControl(breakpoints, part.cache),
+    })),
+  }
+})
+
 const lowerMessages = Effect.fn("AnthropicMessages.lowerMessages")(function* (
   request: LLMRequest,
   breakpoints: Cache.Breakpoints,
 ) {
   const messages: AnthropicMessage[] = []
 
-  for (const message of request.messages) {
+  for (const [index, message] of request.messages.entries()) {
+    if (message.role === "system") {
+      if (splitsLocalToolResults(request.messages, index))
+        return yield* invalid("Anthropic Messages system updates cannot split a local tool call from its tool result")
+      if (supportsNativeSystemUpdates(request) && canUseNativeSystemUpdate(request.messages, index)) {
+        messages.push(yield* lowerNativeSystemUpdate(message, breakpoints))
+        continue
+      }
+      const part = yield* ProviderShared.wrappedSystemUpdate("Anthropic Messages", message)
+      const block = { type: "text" as const, text: part.text, cache_control: cacheControl(breakpoints, part.cache) }
+      const previous = messages.at(-1)
+      if (previous?.role === "user")
+        messages[messages.length - 1] = { role: "user", content: [...previous.content, block] }
+      else messages.push({ role: "user", content: [block] })
+      continue
+    }
+
     if (message.role === "user") {
       const content: AnthropicUserBlock[] = []
       for (const part of message.content) {
@@ -417,7 +507,18 @@ const anthropicOptions = (request: LLMRequest) => request.providerOptions?.anthr
 
 const lowerThinking = Effect.fn("AnthropicMessages.lowerThinking")(function* (request: LLMRequest) {
   const thinking = anthropicOptions(request)?.thinking
-  if (!ProviderShared.isRecord(thinking) || thinking.type !== "enabled") return undefined
+  if (!ProviderShared.isRecord(thinking)) return undefined
+  if (thinking.type === "adaptive") {
+    const display =
+      thinking.display === "summarized"
+        ? ("summarized" as const)
+        : thinking.display === "omitted"
+          ? ("omitted" as const)
+          : undefined
+    return { type: "adaptive" as const, ...(display === undefined ? {} : { display }) }
+  }
+  if (thinking.type === "disabled") return { type: "disabled" as const }
+  if (thinking.type !== "enabled") return undefined
   const budget =
     typeof thinking.budgetTokens === "number"
       ? thinking.budgetTokens
@@ -428,9 +529,16 @@ const lowerThinking = Effect.fn("AnthropicMessages.lowerThinking")(function* (re
   return { type: "enabled" as const, budget_tokens: budget }
 })
 
+const outputConfig = (request: LLMRequest) => {
+  const effort = anthropicOptions(request)?.effort
+  return typeof effort === "string" ? { effort } : undefined
+}
+
 const fromRequest = Effect.fn("AnthropicMessages.fromRequest")(function* (request: LLMRequest) {
   const toolChoice = request.toolChoice ? yield* lowerToolChoice(request.toolChoice) : undefined
   const generation = request.generation
+  const toolSchemaCompatibility = request.model.compatibility?.toolSchema
+  const outputLimit = request.model.defaults?.limits?.output ?? request.model.route.defaults.limits?.output ?? 4096
   // Allocate the 4-breakpoint budget in invalidation order: tools → system →
   // messages. Tools live highest in the cache hierarchy, so when callers
   // over-mark we keep their tool hints and shed the message-tail ones first.
@@ -438,7 +546,13 @@ const fromRequest = Effect.fn("AnthropicMessages.fromRequest")(function* (reques
   const tools =
     request.tools.length === 0 || request.toolChoice?.type === "none"
       ? undefined
-      : request.tools.map((tool) => lowerTool(breakpoints, tool))
+      : request.tools.map((tool) =>
+          lowerTool(
+            breakpoints,
+            tool,
+            ToolSchemaProjection.modelCompatibility(tool.inputSchema, toolSchemaCompatibility),
+          ),
+        )
   const system =
     request.system.length === 0
       ? undefined
@@ -460,12 +574,13 @@ const fromRequest = Effect.fn("AnthropicMessages.fromRequest")(function* (reques
     tools,
     tool_choice: toolChoice,
     stream: true as const,
-    max_tokens: generation?.maxTokens ?? request.model.route.defaults.limits?.output ?? 4096,
+    max_tokens: generation?.maxTokens ?? outputLimit,
     temperature: generation?.temperature,
     top_p: generation?.topP,
     top_k: generation?.topK,
     stop_sequences: generation?.stop,
     thinking: yield* lowerThinking(request),
+    output_config: outputConfig(request),
   }
 })
 
@@ -588,7 +703,14 @@ const onContentBlockStart = (state: ParserState, event: AnthropicEvent): StepRes
           providerExecuted: block.type === "server_tool_use",
         }),
       },
-      [...events, LLMEvent.toolInputStart({ id: block.id ?? String(event.index), name: block.name ?? "" })],
+      [
+        ...events,
+        LLMEvent.toolInputStart({
+          id: block.id ?? String(event.index),
+          name: block.name ?? "",
+          providerExecuted: block.type === "server_tool_use" ? true : undefined,
+        }),
+      ],
     ]
   }
 
@@ -718,10 +840,12 @@ const providerErrorMessage = (event: AnthropicEvent): string => {
   return message || type || "Anthropic Messages stream error"
 }
 
-const onError = (state: ParserState, event: AnthropicEvent): StepResult => [
-  state,
-  [LLMEvent.providerError({ message: providerErrorMessage(event) })],
-]
+const onError = (event: AnthropicEvent) =>
+  new LLMError({
+    module: ADAPTER,
+    method: "stream",
+    reason: classifyProviderFailure({ message: providerErrorMessage(event), code: event.error?.type }),
+  })
 
 const step = (state: ParserState, event: AnthropicEvent) => {
   if (event.type === "message_start") return Effect.succeed(onMessageStart(state, event))
@@ -729,7 +853,7 @@ const step = (state: ParserState, event: AnthropicEvent) => {
   if (event.type === "content_block_delta") return onContentBlockDelta(state, event)
   if (event.type === "content_block_stop") return onContentBlockStop(state, event)
   if (event.type === "message_delta") return Effect.succeed(onMessageDelta(state, event))
-  if (event.type === "error") return Effect.succeed(onError(state, event))
+  if (event.type === "error") return onError(event)
   return Effect.succeed<StepResult>([state, NO_EVENTS])
 }
 
@@ -757,6 +881,7 @@ export const protocol = Protocol.make({
 export const route = Route.make({
   id: ADAPTER,
   provider: "anthropic",
+  providerMetadataKey: "anthropic",
   protocol,
   endpoint: Endpoint.path(PATH, { baseURL: DEFAULT_BASE_URL }),
   auth: Auth.none,

packages/ai/src/protocols/bedrock-converse.ts

@@ -3,21 +3,28 @@ import { Route } from "../route/client"
 import { Endpoint } from "../route/endpoint"
 import { Protocol } from "../route/protocol"
 import {
+  LLMError,
   LLMEvent,
   Usage,
   type CacheHint,
   type FinishReason,
+  type JsonSchema,
   type LLMRequest,
+  type ModelToolSchemaCompatibility,
+  type ProviderMetadata,
+  type ReasoningPart,
   type ToolCallPart,
   type ToolDefinition,
   type ToolResultPart,
 } from "../schema"
 import { BedrockEventStream } from "./bedrock-event-stream"
+import { classifyProviderFailure } from "../provider-error"
 import { JsonObject, optionalArray, ProviderShared } from "./shared"
 import { BedrockAuth } from "./utils/bedrock-auth"
 import { BedrockCache } from "./utils/bedrock-cache"
 import { BedrockMedia } from "./utils/bedrock-media"
 import { Lifecycle } from "./utils/lifecycle"
+import { ToolSchemaProjection } from "./utils/tool-schema"
 import { ToolStream } from "./utils/tool-stream"
 
 const ADAPTER = "bedrock-converse"
@@ -202,18 +209,22 @@ type BedrockEvent = Schema.Schema.Type<typeof BedrockEvent>
 // =============================================================================
 // Request Lowering
 // =============================================================================
-const lowerToolSpec = (tool: ToolDefinition): BedrockToolSpec => ({
+const lowerToolSpec = (tool: ToolDefinition, inputSchema: JsonSchema): BedrockToolSpec => ({
   toolSpec: {
     name: tool.name,
     description: tool.description,
-    inputSchema: { json: tool.inputSchema },
+    inputSchema: { json: inputSchema },
   },
 })
 
-const lowerTools = (breakpoints: BedrockCache.Breakpoints, tools: ReadonlyArray<ToolDefinition>): BedrockTool[] => {
+const lowerTools = (
+  compatibility: ModelToolSchemaCompatibility | undefined,
+  breakpoints: BedrockCache.Breakpoints,
+  tools: ReadonlyArray<ToolDefinition>,
+): BedrockTool[] => {
   const result: BedrockTool[] = []
   for (const tool of tools) {
-    result.push(lowerToolSpec(tool))
+    result.push(lowerToolSpec(tool, ToolSchemaProjection.modelCompatibility(tool.inputSchema, compatibility)))
     const cachePoint = BedrockCache.block(breakpoints, tool.cache)
     if (cachePoint) result.push(cachePoint)
   }
@@ -237,6 +248,16 @@ const lowerToolChoice = (toolChoice: NonNullable<LLMRequest["toolChoice"]>) =>
     tool: (name) => ({ tool: { name } }) as const,
   })
 
+const bedrockMetadata = (metadata: Record<string, unknown>): ProviderMetadata => ({ bedrock: metadata })
+
+const reasoningSignature = (part: ReasoningPart) => {
+  const bedrock = part.providerMetadata?.bedrock
+  return (
+    part.encrypted ??
+    (ProviderShared.isRecord(bedrock) && typeof bedrock.signature === "string" ? bedrock.signature : undefined)
+  )
+}
+
 const lowerToolCall = (part: ToolCallPart): BedrockToolUseBlock => ({
   toolUse: {
     toolUseId: part.id,
@@ -256,7 +277,12 @@ const lowerToolResultContent = Effect.fn("BedrockConverse.lowerToolResultContent
       content.push({ text: item.text })
       continue
     }
-    const media = yield* BedrockMedia.lower(item)
+    const media = yield* BedrockMedia.lower({
+      type: "media",
+      mediaType: item.mime,
+      data: item.uri,
+      filename: item.name,
+    })
     if (!("image" in media))
       return yield* ProviderShared.invalidRequest("Bedrock Converse only supports image media in tool results")
     content.push(media)
@@ -281,6 +307,16 @@ const lowerMessages = Effect.fn("BedrockConverse.lowerMessages")(function* (
   const messages: BedrockMessage[] = []
 
   for (const message of request.messages) {
+    if (message.role === "system") {
+      const part = yield* ProviderShared.wrappedSystemUpdate("Bedrock Converse", message)
+      const content = textWithCache(breakpoints, part.text, part.cache)
+      const previous = messages.at(-1)
+      if (previous?.role === "user")
+        messages[messages.length - 1] = { role: "user", content: [...previous.content, ...content] }
+      else messages.push({ role: "user", content })
+      continue
+    }
+
     if (message.role === "user") {
       const content: BedrockUserBlock[] = []
       for (const part of message.content) {
@@ -315,7 +351,7 @@ const lowerMessages = Effect.fn("BedrockConverse.lowerMessages")(function* (
         if (part.type === "reasoning") {
           content.push({
             reasoningContent: {
-              reasoningText: { text: part.text, signature: part.encrypted },
+              reasoningText: { text: part.text, signature: reasoningSignature(part) },
             },
           })
           continue
@@ -358,7 +394,7 @@ const fromRequest = Effect.fn("BedrockConverse.fromRequest")(function* (request:
   const breakpoints = BedrockCache.breakpoints()
   const toolConfig =
     request.tools.length > 0 && request.toolChoice?.type !== "none"
-      ? { tools: lowerTools(breakpoints, request.tools), toolChoice }
+      ? { tools: lowerTools(request.model.compatibility?.toolSchema, breakpoints, request.tools), toolChoice }
       : undefined
   const system = request.system.length === 0 ? undefined : lowerSystem(breakpoints, request.system)
   const messages = yield* lowerMessages(request, breakpoints)
@@ -384,6 +420,9 @@ const fromRequest = Effect.fn("BedrockConverse.fromRequest")(function* (request:
             stopSequences: generation?.stop,
           },
     toolConfig,
+    // Converse's base inferenceConfig has no topK; Anthropic/Nova accept it
+    // as a model-specific field, so it goes through additionalModelRequestFields.
+    additionalModelRequestFields: generation?.topK === undefined ? undefined : { top_k: generation.topK },
   }
 })
 
@@ -425,6 +464,7 @@ interface ParserState {
   readonly pendingFinish: { readonly reason: FinishReason; readonly usage?: Usage } | undefined
   readonly hasToolCalls: boolean
   readonly lifecycle: Lifecycle.State
+  readonly reasoningSignatures: Readonly<Record<number, string>>
 }
 
 const step = (state: ParserState, event: BedrockEvent) =>
@@ -468,17 +508,19 @@ const step = (state: ParserState, event: BedrockEvent) =>
       ] as const
     }
 
-    if (event.contentBlockDelta?.delta?.reasoningContent?.text) {
+    if (event.contentBlockDelta?.delta?.reasoningContent) {
+      const index = event.contentBlockDelta.contentBlockIndex
+      const reasoning = event.contentBlockDelta.delta.reasoningContent
       const events: LLMEvent[] = []
       return [
         {
           ...state,
-          lifecycle: Lifecycle.reasoningDelta(
-            state.lifecycle,
-            events,
-            `reasoning-${event.contentBlockDelta.contentBlockIndex}`,
-            event.contentBlockDelta.delta.reasoningContent.text,
-          ),
+          lifecycle: reasoning.text
+            ? Lifecycle.reasoningDelta(state.lifecycle, events, `reasoning-${index}`, reasoning.text)
+            : state.lifecycle,
+          reasoningSignatures: reasoning.signature
+            ? { ...state.reasoningSignatures, [index]: reasoning.signature }
+            : state.reasoningSignatures,
         },
         events,
       ] as const
@@ -501,23 +543,32 @@ const step = (state: ParserState, event: BedrockEvent) =>
     }
 
     if (event.contentBlockStop) {
-      const result = yield* ToolStream.finish(ADAPTER, state.tools, event.contentBlockStop.contentBlockIndex)
+      const index = event.contentBlockStop.contentBlockIndex
+      const result = yield* ToolStream.finish(ADAPTER, state.tools, index)
       const events: LLMEvent[] = []
       const resultEvents = result.events ?? []
       const lifecycle = resultEvents.length
         ? Lifecycle.stepStart(state.lifecycle, events)
         : Lifecycle.reasoningEnd(
-            Lifecycle.textEnd(state.lifecycle, events, `text-${event.contentBlockStop.contentBlockIndex}`),
+            Lifecycle.textEnd(state.lifecycle, events, `text-${index}`),
             events,
-            `reasoning-${event.contentBlockStop.contentBlockIndex}`,
+            `reasoning-${index}`,
+            state.reasoningSignatures[index]
+              ? bedrockMetadata({ signature: state.reasoningSignatures[index] })
+              : undefined,
           )
       events.push(...resultEvents)
       return [
         {
           ...state,
-          hasToolCalls: resultEvents.some(LLMEvent.is.toolCall) ? true : state.hasToolCalls,
+          hasToolCalls:
+            resultEvents.some((event) => LLMEvent.is.toolCall(event) || LLMEvent.is.toolInputError(event)) ||
+            state.hasToolCalls,
           lifecycle,
           tools: result.tools,
+          reasoningSignatures: Object.fromEntries(
+            Object.entries(state.reasoningSignatures).filter(([key]) => key !== String(index)),
+          ),
         },
         events,
       ] as const
@@ -538,19 +589,24 @@ const step = (state: ParserState, event: BedrockEvent) =>
       return [{ ...state, pendingFinish: { reason: state.pendingFinish?.reason ?? "stop", usage } }, []] as const
     }
 
-    if (event.internalServerException || event.modelStreamErrorException || event.serviceUnavailableException) {
-      const message =
-        event.internalServerException?.message ??
-        event.modelStreamErrorException?.message ??
-        event.serviceUnavailableException?.message ??
-        "Bedrock Converse stream error"
-      return [state, [LLMEvent.providerError({ message, retryable: true })]] as const
-    }
-
-    if (event.validationException || event.throttlingException) {
-      const message =
-        event.validationException?.message ?? event.throttlingException?.message ?? "Bedrock Converse error"
-      return [state, [LLMEvent.providerError({ message, retryable: event.throttlingException !== undefined })]] as const
+    const exception = (
+      [
+        ["internalServerException", event.internalServerException],
+        ["modelStreamErrorException", event.modelStreamErrorException],
+        ["serviceUnavailableException", event.serviceUnavailableException],
+        ["throttlingException", event.throttlingException],
+        ["validationException", event.validationException],
+      ] as const
+    ).find((entry) => entry[1] !== undefined)
+    if (exception) {
+      return yield* new LLMError({
+        module: ADAPTER,
+        method: "stream",
+        reason: classifyProviderFailure({
+          message: exception[1]?.message ?? "Bedrock Converse stream error",
+          code: exception[0],
+        }),
+      })
     }
 
     return [state, []] as const
@@ -591,6 +647,7 @@ export const protocol = Protocol.make({
       pendingFinish: undefined,
       hasToolCalls: false,
       lifecycle: Lifecycle.initial(),
+      reasoningSignatures: {},
     }),
     step,
     onHalt,
@@ -600,6 +657,7 @@ export const protocol = Protocol.make({
 export const route = Route.make({
   id: ADAPTER,
   provider: "bedrock",
+  providerMetadataKey: "bedrock",
   protocol,
   // Bedrock's URL embeds the region in the route endpoint host and the
   // validated modelId in the path. We read the validated body so the URL

packages/ai/src/protocols/bedrock-event-stream.ts

@@ -1,7 +1,7 @@
 import { EventStreamCodec } from "@smithy/eventstream-codec"
 import { fromUtf8, toUtf8 } from "@smithy/util-utf8"
 import { Effect, Stream } from "effect"
-import type { Framing } from "../route/framing"
+import { Framing } from "../route/framing"
 import { ProviderShared } from "./shared"
 
 // Bedrock streams responses using the AWS event stream binary protocol — each
@@ -79,7 +79,7 @@ const consumeFrames = (route: string) => (state: FrameBufferState, chunk: Uint8A
  * under its `:event-type` header so the chunk schema can match the JSON
  * payload directly.
  */
-export const framing = (route: string): Framing<object> => ({
+export const framing = (route: string): Framing.Definition<object> => ({
   id: "aws-event-stream",
   frame: (bytes) => bytes.pipe(Stream.mapAccumEffect(() => initialFrameBuffer, consumeFrames(route))),
 })

packages/ai/src/protocols/gemini.ts

@@ -8,17 +8,22 @@ import {
   LLMEvent,
   Usage,
   type FinishReason,
+  type JsonSchema,
   type LLMRequest,
   type MediaPart,
+  type ProviderMetadata,
   type TextPart,
   type ToolCallPart,
   type ToolDefinition,
+  type ToolContent,
 } from "../schema"
 import { JsonObject, optionalArray, ProviderShared } from "./shared"
 import { GeminiToolSchema } from "./utils/gemini-tool-schema"
 import { Lifecycle } from "./utils/lifecycle"
+import { ToolSchemaProjection } from "./utils/tool-schema"
 
 const ADAPTER = "gemini"
+const MEDIA_MIMES = new Set<string>(ProviderShared.MEDIA_MIMES)
 export const DEFAULT_BASE_URL = "https://generativelanguage.googleapis.com/v1beta"
 
 // =============================================================================
@@ -136,10 +141,9 @@ interface ParserState {
   readonly nextToolCallId: number
   readonly usage?: Usage
   readonly lifecycle: Lifecycle.State
+  readonly reasoningSignature?: string
 }
 
-const mediaData = ProviderShared.mediaBytes
-
 // =============================================================================
 // Tool Schema Conversion
 // =============================================================================
@@ -164,10 +168,10 @@ const mediaData = ProviderShared.mediaBytes
 // =============================================================================
 // Request Lowering
 // =============================================================================
-const lowerTool = (tool: ToolDefinition) => ({
+const lowerTool = (tool: ToolDefinition, inputSchema: JsonSchema) => ({
   name: tool.name,
   description: tool.description,
-  parameters: GeminiToolSchema.convert(tool.inputSchema),
+  parameters: GeminiToolSchema.convert(inputSchema),
 })
 
 const lowerToolConfig = (toolChoice: NonNullable<LLMRequest["toolChoice"]>) =>
@@ -178,23 +182,45 @@ const lowerToolConfig = (toolChoice: NonNullable<LLMRequest["toolChoice"]>) =>
     tool: (name) => ({ functionCallingConfig: { mode: "ANY" as const, allowedFunctionNames: [name] } }),
   })
 
-const lowerUserPart = (part: TextPart | MediaPart) =>
-  part.type === "text" ? { text: part.text } : { inlineData: { mimeType: part.mediaType, data: mediaData(part) } }
+const lowerUserPart = Effect.fn("Gemini.lowerUserPart")(function* (part: TextPart | MediaPart) {
+  if (part.type === "text") return { text: part.text }
+  const media = yield* ProviderShared.validateMedia("Gemini", part, MEDIA_MIMES)
+  return { inlineData: { mimeType: media.mime, data: media.base64 } }
+})
+
+const googleMetadata = (metadata: Record<string, unknown>): ProviderMetadata => ({ google: metadata })
+
+const thoughtSignature = (providerMetadata: ProviderMetadata | undefined) => {
+  const google = providerMetadata?.google
+  return ProviderShared.isRecord(google) && typeof google.thoughtSignature === "string"
+    ? google.thoughtSignature
+    : undefined
+}
 
 const lowerToolCall = (part: ToolCallPart) => ({
   functionCall: { name: part.name, args: part.input },
+  thoughtSignature: thoughtSignature(part.providerMetadata),
 })
 
 const lowerMessages = Effect.fn("Gemini.lowerMessages")(function* (request: LLMRequest) {
   const contents: GeminiContent[] = []
 
   for (const message of request.messages) {
+    if (message.role === "system") {
+      const part = yield* ProviderShared.wrappedSystemUpdate("Gemini", message)
+      const previous = contents.at(-1)
+      if (previous?.role === "user")
+        contents[contents.length - 1] = { role: "user", parts: [...previous.parts, { text: part.text }] }
+      else contents.push({ role: "user", parts: [{ text: part.text }] })
+      continue
+    }
+
     if (message.role === "user") {
       const parts: Array<Schema.Schema.Type<typeof GeminiContentPart>> = []
       for (const part of message.content) {
         if (!ProviderShared.supportsContent(part, ["text", "media"]))
           return yield* ProviderShared.unsupportedContent("Gemini", "user", ["text", "media"])
-        parts.push(lowerUserPart(part))
+        parts.push(yield* lowerUserPart(part))
       }
       contents.push({ role: "user", parts })
       continue
@@ -210,7 +236,7 @@ const lowerMessages = Effect.fn("Gemini.lowerMessages")(function* (request: LLMR
           continue
         }
         if (part.type === "reasoning") {
-          parts.push({ text: part.text, thought: true })
+          parts.push({ text: part.text, thought: true, thoughtSignature: thoughtSignature(part.providerMetadata) })
           continue
         }
         if (part.type === "tool-call") {
@@ -226,15 +252,34 @@ const lowerMessages = Effect.fn("Gemini.lowerMessages")(function* (request: LLMR
     for (const part of message.content) {
       if (!ProviderShared.supportsContent(part, ["tool-result"]))
         return yield* ProviderShared.unsupportedContent("Gemini", "tool", ["tool-result"])
+      if (part.result.type !== "content") {
+        parts.push({
+          functionResponse: {
+            name: part.name,
+            response: {
+              name: part.name,
+              content: ProviderShared.toolResultText(part),
+            },
+          },
+        })
+        continue
+      }
+      const content: ReadonlyArray<ToolContent> = part.result.value
+      const text = content.filter((item) => item.type === "text").map((item) => item.text)
       parts.push({
         functionResponse: {
           name: part.name,
           response: {
             name: part.name,
-            content: ProviderShared.toolResultText(part),
+            content: text.join("\n"),
           },
         },
       })
+      for (const item of content) {
+        if (item.type === "text") continue
+        const media = yield* ProviderShared.validateToolFile("Gemini", item, MEDIA_MIMES)
+        parts.push({ inlineData: { mimeType: media.mime, data: media.base64 } })
+      }
     }
     contents.push({ role: "user", parts })
   }
@@ -257,6 +302,7 @@ const thinkingConfig = (request: LLMRequest) => {
 const fromRequest = Effect.fn("Gemini.fromRequest")(function* (request: LLMRequest) {
   const toolsEnabled = request.tools.length > 0 && request.toolChoice?.type !== "none"
   const generation = request.generation
+  const toolSchemaCompatibility = request.model.compatibility?.toolSchema
   const generationConfig = {
     maxOutputTokens: generation?.maxTokens,
     temperature: generation?.temperature,
@@ -270,7 +316,15 @@ const fromRequest = Effect.fn("Gemini.fromRequest")(function* (request: LLMReque
     contents: yield* lowerMessages(request),
     systemInstruction:
       request.system.length === 0 ? undefined : { parts: [{ text: ProviderShared.joinText(request.system) }] },
-    tools: toolsEnabled ? [{ functionDeclarations: request.tools.map(lowerTool) }] : undefined,
+    tools: toolsEnabled
+      ? [
+          {
+            functionDeclarations: request.tools.map((tool) =>
+              lowerTool(tool, ToolSchemaProjection.modelCompatibility(tool.inputSchema, toolSchemaCompatibility)),
+            ),
+          },
+        ]
+      : undefined,
     toolConfig: toolsEnabled && request.toolChoice ? yield* lowerToolConfig(request.toolChoice) : undefined,
     generationConfig: Object.values(generationConfig).some((value) => value !== undefined)
       ? generationConfig
@@ -326,7 +380,15 @@ const finish = (state: ParserState): ReadonlyArray<LLMEvent> =>
   state.finishReason || state.usage
     ? (() => {
         const events: LLMEvent[] = []
-        Lifecycle.finish(state.lifecycle, events, {
+        const lifecycle = state.reasoningSignature
+          ? Lifecycle.reasoningEnd(
+              state.lifecycle,
+              events,
+              "reasoning-0",
+              googleMetadata({ thoughtSignature: state.reasoningSignature }),
+            )
+          : state.lifecycle
+        Lifecycle.finish(lifecycle, events, {
           reason: mapFinishReason(state.finishReason, state.hasToolCalls),
           usage: state.usage,
         })
@@ -350,20 +412,52 @@ const step = (state: ParserState, event: GeminiEvent) => {
   let hasToolCalls = nextState.hasToolCalls
   let lifecycle = nextState.lifecycle
   let nextToolCallId = nextState.nextToolCallId
+  let reasoningSignature = nextState.reasoningSignature
 
   for (const part of candidate.content.parts) {
+    if ("thoughtSignature" in part && part.thoughtSignature && "thought" in part && part.thought)
+      reasoningSignature = part.thoughtSignature
     if ("text" in part && part.text.length > 0) {
-      lifecycle = part.thought
-        ? Lifecycle.reasoningDelta(lifecycle, events, "reasoning-0", part.text)
-        : Lifecycle.textDelta(lifecycle, events, "text-0", part.text)
+      if (part.thought) {
+        lifecycle = Lifecycle.reasoningDelta(
+          lifecycle,
+          events,
+          "reasoning-0",
+          part.text,
+          part.thoughtSignature ? googleMetadata({ thoughtSignature: part.thoughtSignature }) : undefined,
+        )
+        continue
+      }
+      lifecycle = Lifecycle.reasoningEnd(
+        lifecycle,
+        events,
+        "reasoning-0",
+        reasoningSignature ? googleMetadata({ thoughtSignature: reasoningSignature }) : undefined,
+      )
+      lifecycle = Lifecycle.textDelta(lifecycle, events, "text-0", part.text)
       continue
     }
 
     if ("functionCall" in part) {
       const input = part.functionCall.args
       const id = `tool_${nextToolCallId++}`
+      lifecycle = Lifecycle.reasoningEnd(
+        lifecycle,
+        events,
+        "reasoning-0",
+        reasoningSignature ? googleMetadata({ thoughtSignature: reasoningSignature }) : undefined,
+      )
       lifecycle = Lifecycle.stepStart(lifecycle, events)
-      events.push(LLMEvent.toolCall({ id, name: part.functionCall.name, input }))
+      events.push(
+        LLMEvent.toolCall({
+          id,
+          name: part.functionCall.name,
+          input,
+          providerMetadata: part.thoughtSignature
+            ? googleMetadata({ thoughtSignature: part.thoughtSignature })
+            : undefined,
+        }),
+      )
       hasToolCalls = true
     }
   }
@@ -374,6 +468,7 @@ const step = (state: ParserState, event: GeminiEvent) => {
       hasToolCalls,
       lifecycle,
       nextToolCallId,
+      reasoningSignature,
       finishReason: candidate.finishReason ?? nextState.finishReason,
     },
     events,
@@ -405,6 +500,7 @@ export const protocol = Protocol.make({
 export const route = Route.make({
   id: ADAPTER,
   provider: "google",
+  providerMetadataKey: "google",
   protocol,
   // Gemini's path embeds the model id and pins SSE framing at the URL level.
   endpoint: Endpoint.path(({ request }) => `/models/${request.model.id}:streamGenerateContent?alt=sse`, {

packages/ai/src/protocols/index.ts

@@ -2,5 +2,7 @@ export * as AnthropicMessages from "./anthropic-messages"
 export * as BedrockConverse from "./bedrock-converse"
 export * as Gemini from "./gemini"
 export * as OpenAIChat from "./openai-chat"
+export * as OpenAIImages from "./openai-images"
 export * as OpenAICompatibleChat from "./openai-compatible-chat"
+export * as OpenAICompatibleResponses from "./openai-compatible-responses"
 export * as OpenAIResponses from "./openai-responses"

packages/ai/src/protocols/openai-chat.ts

@@ -1,4 +1,4 @@
-import { Array as Arr, Effect, Schema } from "effect"
+import { Effect, Schema } from "effect"
 import { Route } from "../route/client"
 import { Auth } from "../route/auth"
 import { Endpoint } from "../route/endpoint"
@@ -8,17 +8,23 @@ import {
   LLMEvent,
   Usage,
   type FinishReason,
+  type JsonSchema,
   type LLMRequest,
+  type MediaPart,
+  type ReasoningPart,
   type TextPart,
   type ToolCallPart,
   type ToolDefinition,
+  type ToolContent,
 } from "../schema"
 import { isRecord, JsonObject, optionalArray, optionalNull, ProviderShared } from "./shared"
 import { OpenAIOptions } from "./utils/openai-options"
 import { Lifecycle } from "./utils/lifecycle"
+import { ToolSchemaProjection } from "./utils/tool-schema"
 import { ToolStream } from "./utils/tool-stream"
 
 const ADAPTER = "openai-chat"
+const IMAGE_MIMES = new Set<string>(ProviderShared.IMAGE_MIMES)
 export const DEFAULT_BASE_URL = "https://api.openai.com/v1"
 export const PATH = "/chat/completions"
 
@@ -50,14 +56,28 @@ const OpenAIChatAssistantToolCall = Schema.Struct({
 })
 type OpenAIChatAssistantToolCall = Schema.Schema.Type<typeof OpenAIChatAssistantToolCall>
 
+const OpenAIChatUserContent = Schema.Union([
+  Schema.Struct({ type: Schema.Literal("text"), text: Schema.String }),
+  Schema.Struct({
+    type: Schema.Literal("image_url"),
+    image_url: Schema.Struct({ url: Schema.String }),
+  }),
+])
+
 const OpenAIChatMessage = Schema.Union([
   Schema.Struct({ role: Schema.Literal("system"), content: Schema.String }),
-  Schema.Struct({ role: Schema.Literal("user"), content: Schema.String }),
+  Schema.Struct({
+    role: Schema.Literal("user"),
+    content: Schema.Union([Schema.String, Schema.Array(OpenAIChatUserContent)]),
+  }),
   Schema.Struct({
     role: Schema.Literal("assistant"),
     content: Schema.NullOr(Schema.String),
     tool_calls: optionalArray(OpenAIChatAssistantToolCall),
     reasoning_content: Schema.optional(Schema.String),
+    reasoning: Schema.optional(Schema.String),
+    reasoning_text: Schema.optional(Schema.String),
+    reasoning_details: optionalArray(Schema.Unknown),
   }),
   Schema.Struct({ role: Schema.Literal("tool"), tool_call_id: Schema.String, content: Schema.String }),
 ]).pipe(Schema.toTaggedUnion("role"))
@@ -128,6 +148,9 @@ type OpenAIChatToolCallDelta = Schema.Schema.Type<typeof OpenAIChatToolCallDelta
 const OpenAIChatDelta = Schema.Struct({
   content: optionalNull(Schema.String),
   reasoning_content: optionalNull(Schema.String),
+  reasoning: optionalNull(Schema.String),
+  reasoning_text: optionalNull(Schema.String),
+  reasoning_details: optionalNull(Schema.Array(Schema.Unknown)),
   tool_calls: optionalNull(Schema.Array(OpenAIChatToolCallDelta)),
 })
 
@@ -136,35 +159,44 @@ const OpenAIChatChoice = Schema.Struct({
   finish_reason: optionalNull(Schema.String),
 })
 
-const OpenAIChatEvent = Schema.Struct({
+export const OpenAIChatEvent = Schema.Struct({
   choices: Schema.Array(OpenAIChatChoice),
   usage: optionalNull(OpenAIChatUsage),
 })
-type OpenAIChatEvent = Schema.Schema.Type<typeof OpenAIChatEvent>
+export type OpenAIChatEvent = Schema.Schema.Type<typeof OpenAIChatEvent>
 type OpenAIChatRequestMessage = LLMRequest["messages"][number]
 
-interface ParserState {
+interface PendingToolDelta {
+  readonly id?: string
+  readonly name?: string
+  readonly input: string
+}
+
+export interface ParserState {
   readonly tools: ToolStream.State<number>
+  readonly pendingTools: Partial<Record<number, PendingToolDelta>>
   readonly toolCallEvents: ReadonlyArray<LLMEvent>
   readonly usage?: Usage
   readonly finishReason?: FinishReason
   readonly lifecycle: Lifecycle.State
+  readonly reasoningField?: "reasoning" | "reasoning_content" | "reasoning_text"
+  readonly reasoningDetails: Array<unknown>
+  readonly reasoningDetailsObserved: boolean
+  readonly reasoningEmitted: boolean
 }
 
-const invalid = ProviderShared.invalidRequest
-
 // =============================================================================
 // Request Lowering
 // =============================================================================
 // Lowering is the only place that knows how common LLM messages map onto the
 // OpenAI Chat wire format. Keep provider quirks here instead of leaking native
 // fields into `LLMRequest`.
-const lowerTool = (tool: ToolDefinition): OpenAIChatTool => ({
+const lowerTool = (tool: ToolDefinition, inputSchema: JsonSchema): OpenAIChatTool => ({
   type: "function",
   function: {
     name: tool.name,
     description: tool.description,
-    parameters: tool.inputSchema,
+    parameters: ToolSchemaProjection.openAI(inputSchema),
   },
 })
 
@@ -185,71 +217,166 @@ const lowerToolCall = (part: ToolCallPart): OpenAIChatAssistantToolCall => ({
   },
 })
 
+const lowerMedia = Effect.fn("OpenAIChat.lowerMedia")(function* (part: MediaPart) {
+  const media = yield* ProviderShared.validateMedia("OpenAI Chat", part, IMAGE_MIMES)
+  return { type: "image_url" as const, image_url: { url: media.dataUrl } }
+})
+
 const openAICompatibleReasoningContent = (native: unknown) =>
   isRecord(native) && typeof native.reasoning_content === "string" ? native.reasoning_content : undefined
 
+const reasoningField = (part: ReasoningPart) => {
+  const field = part.providerMetadata?.openai?.reasoningField
+  if (field === "reasoning" || field === "reasoning_content" || field === "reasoning_text") return field
+}
+
+const reasoningDetails = (parts: ReadonlyArray<ReasoningPart>, native: unknown) => {
+  const observed = parts.flatMap((part) => {
+    const details = part.providerMetadata?.openai?.reasoningDetails
+    return Array.isArray(details) ? details : []
+  })
+  if (parts.some((part) => Array.isArray(part.providerMetadata?.openai?.reasoningDetails))) return observed
+  if (isRecord(native) && Array.isArray(native.reasoning_details)) return native.reasoning_details
+}
+
 const lowerUserMessage = Effect.fn("OpenAIChat.lowerUserMessage")(function* (message: OpenAIChatRequestMessage) {
-  const content: TextPart[] = []
+  const content: Array<Schema.Schema.Type<typeof OpenAIChatUserContent>> = []
   for (const part of message.content) {
-    if (!ProviderShared.supportsContent(part, ["text"]))
-      return yield* ProviderShared.unsupportedContent("OpenAI Chat", "user", ["text"])
-    content.push(part)
+    if (part.type === "text") {
+      content.push({ type: "text", text: part.text })
+      continue
+    }
+    if (part.type === "media") {
+      content.push(yield* lowerMedia(part))
+      continue
+    }
+    return yield* ProviderShared.unsupportedContent("OpenAI Chat", "user", ["text", "media"])
   }
-  return { role: "user" as const, content: ProviderShared.joinText(content) }
+  if (content.every((part) => part.type === "text"))
+    return { role: "user" as const, content: content.map((part) => part.text).join("") }
+  return { role: "user" as const, content }
 })
 
 const lowerAssistantMessage = Effect.fn("OpenAIChat.lowerAssistantMessage")(function* (
   message: OpenAIChatRequestMessage,
 ) {
   const content: TextPart[] = []
+  const reasoning: ReasoningPart[] = []
   const toolCalls: OpenAIChatAssistantToolCall[] = []
   for (const part of message.content) {
-    if (!ProviderShared.supportsContent(part, ["text", "tool-call"]))
-      return yield* ProviderShared.unsupportedContent("OpenAI Chat", "assistant", ["text", "tool-call"])
+    if (!ProviderShared.supportsContent(part, ["text", "reasoning", "tool-call"]))
+      return yield* ProviderShared.unsupportedContent("OpenAI Chat", "assistant", ["text", "reasoning", "tool-call"])
     if (part.type === "text") {
       content.push(part)
       continue
     }
+    if (part.type === "reasoning") {
+      reasoning.push(part)
+      continue
+    }
     if (part.type === "tool-call") {
       toolCalls.push(lowerToolCall(part))
       continue
     }
   }
+  const text = reasoning.map((part) => part.text).join("")
+  const details = reasoningDetails(reasoning, message.native?.openaiCompatible)
+  const observedField = reasoning.map(reasoningField).find((value) => value !== undefined)
+  const nativeReasoning = openAICompatibleReasoningContent(message.native?.openaiCompatible)
+  const fullyStructured = reasoning.every((part) => Array.isArray(part.providerMetadata?.openai?.reasoningDetails))
+  const field = (() => {
+    if (reasoning.length === 0) return
+    if (observedField !== undefined) return observedField
+    if (nativeReasoning !== undefined) return "reasoning_content"
+    if (!fullyStructured) return "reasoning_content"
+  })()
+  const reasoningContent = (() => {
+    if (reasoning.length === 0) return nativeReasoning
+    if (field === "reasoning_content") return text
+  })()
   return {
     role: "assistant" as const,
     content: content.length === 0 ? null : ProviderShared.joinText(content),
     tool_calls: toolCalls.length === 0 ? undefined : toolCalls,
-    reasoning_content: openAICompatibleReasoningContent(message.native?.openaiCompatible),
+    reasoning_content: reasoningContent,
+    reasoning: reasoning.length > 0 && field === "reasoning" ? text : undefined,
+    reasoning_text: reasoning.length > 0 && field === "reasoning_text" ? text : undefined,
+    reasoning_details: details,
   }
 })
 
 const lowerToolMessages = Effect.fn("OpenAIChat.lowerToolMessages")(function* (message: OpenAIChatRequestMessage) {
   const messages: OpenAIChatMessage[] = []
+  const images: Array<Schema.Schema.Type<typeof OpenAIChatUserContent>> = []
   for (const part of message.content) {
     if (!ProviderShared.supportsContent(part, ["tool-result"]))
       return yield* ProviderShared.unsupportedContent("OpenAI Chat", "tool", ["tool-result"])
-    messages.push({ role: "tool", tool_call_id: part.id, content: ProviderShared.toolResultText(part) })
+    if (part.result.type !== "content") {
+      messages.push({ role: "tool", tool_call_id: part.id, content: ProviderShared.toolResultText(part) })
+      continue
+    }
+    const content: ReadonlyArray<ToolContent> = part.result.value
+    const text = content.filter((item) => item.type === "text").map((item) => item.text)
+    messages.push({ role: "tool", tool_call_id: part.id, content: text.join("\n") })
+    const files = content.filter((item) => item.type === "file")
+    images.push(
+      ...(yield* Effect.forEach(files, (item) =>
+        lowerMedia({ type: "media", mediaType: item.mime, data: item.uri, filename: item.name }),
+      )),
+    )
   }
-  return messages
+  return { messages, images }
 })
 
 const lowerMessage = Effect.fn("OpenAIChat.lowerMessage")(function* (message: OpenAIChatRequestMessage) {
   if (message.role === "user") return [yield* lowerUserMessage(message)]
   if (message.role === "assistant") return [yield* lowerAssistantMessage(message)]
-  return yield* lowerToolMessages(message)
+  return (yield* lowerToolMessages(message)).messages
 })
 
 const lowerMessages = Effect.fn("OpenAIChat.lowerMessages")(function* (request: LLMRequest) {
   const system: OpenAIChatMessage[] =
     request.system.length === 0 ? [] : [{ role: "system", content: ProviderShared.joinText(request.system) }]
-  return [...system, ...Arr.flatten(yield* Effect.forEach(request.messages, lowerMessage))]
+  const messages = [...system]
+  const pendingImages: Array<Schema.Schema.Type<typeof OpenAIChatUserContent>> = []
+  const flushImages = () => {
+    if (pendingImages.length === 0) return
+    messages.push({ role: "user", content: pendingImages.splice(0) })
+  }
+  for (const message of request.messages) {
+    if (message.role === "system") {
+      const part = yield* ProviderShared.wrappedSystemUpdate("OpenAI Chat", message)
+      if (pendingImages.length > 0) {
+        messages.push({ role: "user", content: [...pendingImages.splice(0), { type: "text", text: part.text }] })
+        continue
+      }
+      const previous = messages.at(-1)
+      if (previous?.role === "user" && typeof previous.content === "string")
+        messages[messages.length - 1] = { role: "user", content: `${previous.content}\n${part.text}` }
+      else if (previous?.role === "user" && Array.isArray(previous.content))
+        messages[messages.length - 1] = {
+          role: "user",
+          content: [...previous.content, { type: "text", text: part.text }],
+        }
+      else messages.push({ role: "user", content: part.text })
+      continue
+    }
+    if (message.role === "tool") {
+      const lowered = yield* lowerToolMessages(message)
+      messages.push(...lowered.messages)
+      pendingImages.push(...lowered.images)
+      continue
+    }
+    flushImages()
+    messages.push(...(yield* lowerMessage(message)))
+  }
+  flushImages()
+  return messages
 })
 
 const lowerOptions = Effect.fn("OpenAIChat.lowerOptions")(function* (request: LLMRequest) {
   const store = OpenAIOptions.store(request)
   const reasoningEffort = OpenAIOptions.reasoningEffort(request)
-  if (reasoningEffort && !OpenAIOptions.isReasoningEffort(reasoningEffort))
-    return yield* invalid(`OpenAI Chat does not support reasoning effort ${reasoningEffort}`)
   return {
     ...(store !== undefined ? { store } : {}),
     ...(reasoningEffort ? { reasoning_effort: reasoningEffort } : {}),
@@ -260,10 +387,16 @@ const fromRequest = Effect.fn("OpenAIChat.fromRequest")(function* (request: LLMR
   // `fromRequest` returns the provider body only. Endpoint, auth, framing,
   // validation, and HTTP execution are composed by `Route.make`.
   const generation = request.generation
+  const toolSchemaCompatibility = request.model.compatibility?.toolSchema
   return {
     model: request.model.id,
     messages: yield* lowerMessages(request),
-    tools: request.tools.length === 0 ? undefined : request.tools.map(lowerTool),
+    tools:
+      request.tools.length === 0
+        ? undefined
+        : request.tools.map((tool) =>
+            lowerTool(tool, ToolSchemaProjection.modelCompatibility(tool.inputSchema, toolSchemaCompatibility)),
+          ),
     tool_choice: request.toolChoice ? yield* lowerToolChoice(request.toolChoice) : undefined,
     stream: true as const,
     stream_options: { include_usage: true },
@@ -313,6 +446,65 @@ const mapUsage = (usage: OpenAIChatEvent["usage"]): Usage | undefined => {
   })
 }
 
+const reasoningDelta = (delta: Schema.Schema.Type<typeof OpenAIChatDelta> | null | undefined) => {
+  if (delta?.reasoning_content) return { field: "reasoning_content", text: delta.reasoning_content } as const
+  if (delta?.reasoning) return { field: "reasoning", text: delta.reasoning } as const
+  if (delta?.reasoning_text) return { field: "reasoning_text", text: delta.reasoning_text } as const
+}
+
+const detailText = (details: ReadonlyArray<unknown>) => {
+  const text = details.flatMap((detail) => {
+    if (!isRecord(detail)) return []
+    if (detail.type === "reasoning.text" && typeof detail.text === "string" && detail.text) return [detail.text]
+    if (detail.type === "reasoning.summary" && typeof detail.summary === "string" && detail.summary)
+      return [detail.summary]
+    return []
+  })
+  if (text.length > 0) return text.join("")
+}
+
+const appendReasoningDetails = (result: Array<unknown>, details: ReadonlyArray<unknown>) => {
+  for (const detail of details) {
+    const previous = result.at(-1)
+    if (
+      !isRecord(previous) ||
+      previous.type !== "reasoning.text" ||
+      !isRecord(detail) ||
+      detail.type !== "reasoning.text" ||
+      conflictingReasoningTextDetails(previous, detail)
+    ) {
+      result.push(detail)
+      continue
+    }
+    result[result.length - 1] = {
+      ...previous,
+      ...Object.fromEntries(Object.entries(detail).filter((entry) => entry[1] !== undefined)),
+      text: `${typeof previous.text === "string" ? previous.text : ""}${typeof detail.text === "string" ? detail.text : ""}`,
+      signature: mergeDetailValue(previous.signature, detail.signature),
+      format: mergeDetailValue(previous.format, detail.format),
+    }
+  }
+}
+
+const mergeDetailValue = (previous: unknown, current: unknown) =>
+  previous || current || (previous !== undefined ? previous : current)
+
+const conflictingReasoningTextDetails = (previous: Record<string, unknown>, current: Record<string, unknown>) =>
+  conflictingDetailValue(previous.id, current.id) ||
+  conflictingDetailValue(previous.index, current.index) ||
+  conflictingDetailValue(previous.format, current.format) ||
+  (Boolean(previous.signature) && Boolean(current.signature) && previous.signature !== current.signature)
+
+const conflictingDetailValue = (previous: unknown, current: unknown) =>
+  previous !== undefined && previous !== null && current !== undefined && current !== null && previous !== current
+
+const reasoningMetadata = (field: ParserState["reasoningField"], details?: ReadonlyArray<unknown>) => ({
+  openai: {
+    ...(field ? { reasoningField: field } : {}),
+    ...(details ? { reasoningDetails: details } : {}),
+  },
+})
+
 const step = (state: ParserState, event: OpenAIChatEvent) =>
   Effect.gen(function* () {
     const events: LLMEvent[] = []
@@ -322,20 +514,56 @@ const step = (state: ParserState, event: OpenAIChatEvent) =>
     const delta = choice?.delta
     const toolDeltas = delta?.tool_calls ?? []
     let tools = state.tools
+    let pendingTools = state.pendingTools
 
     let lifecycle = state.lifecycle
 
-    if (delta?.reasoning_content)
-      lifecycle = Lifecycle.reasoningDelta(lifecycle, events, "reasoning-0", delta.reasoning_content)
+    const reasoning = reasoningDelta(delta)
+    const reasoningField = state.reasoningField ?? (!state.lifecycle.text.has("text-0") ? reasoning?.field : undefined)
+    const detailDelta = Array.isArray(delta?.reasoning_details) ? delta.reasoning_details : undefined
+    if (detailDelta !== undefined) appendReasoningDetails(state.reasoningDetails, detailDelta)
+    const reasoningDetailsObserved = state.reasoningDetailsObserved || detailDelta !== undefined
+    const deltaMetadata = reasoningMetadata(reasoningField)
+    const text = detailDelta?.length ? (detailText(detailDelta) ?? reasoning?.text) : reasoning?.text
+    if (!state.lifecycle.text.has("text-0") && text !== undefined)
+      lifecycle = Lifecycle.reasoningDelta(lifecycle, events, "reasoning-0", text, deltaMetadata)
+    else if (
+      reasoningDetailsObserved &&
+      !lifecycle.reasoning.has("reasoning-0") &&
+      (Boolean(delta?.content) || toolDeltas.length > 0)
+    )
+      lifecycle = Lifecycle.reasoningStart(lifecycle, events, "reasoning-0", deltaMetadata)
+    const reasoningEmitted = state.reasoningEmitted || lifecycle.reasoning.has("reasoning-0")
 
-    if (delta?.content) lifecycle = Lifecycle.textDelta(lifecycle, events, "text-0", delta.content)
+    if (delta?.content) {
+      lifecycle = Lifecycle.reasoningEnd(
+        lifecycle,
+        events,
+        "reasoning-0",
+        reasoningMetadata(reasoningField, reasoningDetailsObserved ? state.reasoningDetails : undefined),
+      )
+      lifecycle = Lifecycle.textDelta(lifecycle, events, "text-0", delta.content)
+    }
 
     for (const tool of toolDeltas) {
+      const current = tools[tool.index]
+      const pending = pendingTools[tool.index]
+      const id = current?.id ?? pending?.id ?? (tool.id || undefined)
+      const name = current?.name ?? pending?.name ?? (tool.function?.name || undefined)
+      const text = `${pending?.input ?? ""}${tool.function?.arguments ?? ""}`
+      if (!current && (!id || !name)) {
+        pendingTools = { ...pendingTools, [tool.index]: { id: id || undefined, name: name || undefined, input: text } }
+        continue
+      }
+      if (pending) {
+        pendingTools = { ...pendingTools }
+        delete pendingTools[tool.index]
+      }
       const result = ToolStream.appendOrStart(
         ADAPTER,
         tools,
         tool.index,
-        { id: tool.id ?? undefined, name: tool.function?.name ?? undefined, text: tool.function?.arguments ?? "" },
+        { id: id || undefined, name: name || undefined, text },
         "OpenAI Chat tool call delta is missing id or name",
       )
       if (ToolStream.isError(result)) return yield* result
@@ -344,8 +572,11 @@ const step = (state: ParserState, event: OpenAIChatEvent) =>
       events.push(...result.events)
     }
 
+    if (finishReason !== undefined && state.finishReason === undefined && Object.keys(pendingTools).length > 0)
+      return yield* ProviderShared.eventError(ADAPTER, "OpenAI Chat tool call delta is missing id or name")
+
     // Finalize accumulated tool inputs eagerly when finish_reason arrives so
-    // JSON parse failures fail the stream at the boundary rather than at halt.
+    // valid calls and malformed local calls settle independently.
     const finished =
       finishReason !== undefined && state.finishReason === undefined && Object.keys(tools).length > 0
         ? yield* ToolStream.finishAll(ADAPTER, tools)
@@ -354,10 +585,15 @@ const step = (state: ParserState, event: OpenAIChatEvent) =>
     return [
       {
         tools: finished?.tools ?? tools,
+        pendingTools,
         toolCallEvents: finished?.events ?? state.toolCallEvents,
         usage,
         finishReason,
         lifecycle,
+        reasoningField,
+        reasoningDetails: state.reasoningDetails,
+        reasoningDetailsObserved,
+        reasoningEmitted,
       },
       events,
     ] as const
@@ -367,7 +603,16 @@ const finishEvents = (state: ParserState): ReadonlyArray<LLMEvent> => {
   const events: LLMEvent[] = []
   const hasToolCalls = state.toolCallEvents.length > 0
   const reason = state.finishReason === "stop" && hasToolCalls ? "tool-calls" : state.finishReason
-  const lifecycle = state.toolCallEvents.length ? Lifecycle.stepStart(state.lifecycle, events) : state.lifecycle
+  const metadata = reasoningMetadata(
+    state.reasoningField,
+    state.reasoningDetailsObserved ? state.reasoningDetails : undefined,
+  )
+  const started =
+    state.reasoningDetailsObserved && !state.reasoningEmitted
+      ? Lifecycle.reasoningStart(state.lifecycle, events, "reasoning-0", reasoningMetadata(state.reasoningField))
+      : state.lifecycle
+  const ended = Lifecycle.reasoningEnd(started, events, "reasoning-0", metadata)
+  const lifecycle = state.toolCallEvents.length ? Lifecycle.stepStart(ended, events) : ended
   events.push(...state.toolCallEvents)
   if (reason) Lifecycle.finish(lifecycle, events, { reason, usage: state.usage })
   return events
@@ -390,7 +635,16 @@ export const protocol = Protocol.make({
   },
   stream: {
     event: Protocol.jsonEvent(OpenAIChatEvent),
-    initial: () => ({ tools: ToolStream.empty<number>(), toolCallEvents: [], lifecycle: Lifecycle.initial() }),
+    initial: () => ({
+      tools: ToolStream.empty<number>(),
+      pendingTools: {},
+      toolCallEvents: [],
+      lifecycle: Lifecycle.initial(),
+      reasoningField: undefined,
+      reasoningDetails: [],
+      reasoningDetailsObserved: false,
+      reasoningEmitted: false,
+    }),
     step,
     onHalt: finishEvents,
   },
@@ -401,6 +655,7 @@ export const httpTransport = HttpTransport.sseJson.with<OpenAIChatBody>()
 export const route = Route.make({
   id: ADAPTER,
   provider: "openai",
+  providerMetadataKey: "openai",
   protocol,
   endpoint: Endpoint.path(PATH, { baseURL: DEFAULT_BASE_URL }),
   auth: Auth.none,

packages/ai/src/protocols/openai-compatible-chat.ts

@@ -16,6 +16,7 @@ export type OpenAICompatibleChatModelInput = RouteRoutedModelInput
  */
 export const route = Route.make({
   id: ADAPTER,
+  providerMetadataKey: "openai",
   protocol: OpenAIChat.protocol,
   endpoint: Endpoint.path("/chat/completions"),
   framing: Framing.sse,

packages/ai/src/protocols/openai-compatible-responses.ts

@@ -0,0 +1,23 @@
+import { Route, type RouteRoutedModelInput } from "../route/client"
+import { Endpoint } from "../route/endpoint"
+import { OpenAIResponses } from "./openai-responses"
+
+const ADAPTER = "openai-compatible-responses"
+
+export type OpenAICompatibleResponsesModelInput = RouteRoutedModelInput
+
+/**
+ * Route for providers that expose an OpenAI Responses-compatible `/responses`
+ * endpoint. Provider helpers configure identity, endpoint, and auth before
+ * model selection while this route reuses the OpenAI Responses protocol.
+ */
+export const route = Route.make({
+  id: ADAPTER,
+  providerMetadataKey: "openai",
+  protocol: OpenAIResponses.protocol,
+  endpoint: Endpoint.path(OpenAIResponses.PATH),
+  transport: OpenAIResponses.httpTransport,
+  defaults: { providerOptions: { openai: { store: false } } },
+})
+
+export * as OpenAICompatibleResponses from "./openai-compatible-responses"

packages/ai/src/protocols/openai-images.ts

@@ -0,0 +1,208 @@
+import { Effect, Encoding, Schema } from "effect"
+import { Headers, HttpClientRequest } from "effect/unstable/http"
+import {
+  ImageModel,
+  GeneratedImage,
+  ImageResponse,
+  type ImageRequest,
+  type ImageModelDefaults,
+  type ImageRoute,
+} from "../image"
+import { Auth, type Definition as AuthDefinition } from "../route/auth"
+import { InvalidProviderOutputReason, LLMError, Usage, mergeHttpOptions, mergeJsonRecords } from "../schema"
+import { ProviderShared } from "./shared"
+import { OpenAIImage } from "./utils/openai-image"
+
+const ADAPTER = "openai-images"
+export const DEFAULT_BASE_URL = "https://api.openai.com/v1"
+export const PATH = "/images/generations"
+
+export interface OpenAIImageOptions {
+  readonly quality?: "auto" | "low" | "medium" | "high"
+  readonly background?: "auto" | "opaque" | "transparent"
+  readonly moderation?: "auto" | "low"
+  readonly outputFormat?: "png" | "jpeg" | "webp"
+  readonly outputCompression?: number
+}
+
+const OpenAIImageBody = Schema.Struct({
+  model: Schema.String,
+  prompt: Schema.String,
+  n: Schema.optional(Schema.Int.check(Schema.isGreaterThanOrEqualTo(1))),
+  size: Schema.optional(Schema.String),
+  quality: Schema.optional(Schema.Literals(["auto", "low", "medium", "high"])),
+  background: Schema.optional(Schema.Literals(["auto", "opaque", "transparent"])),
+  moderation: Schema.optional(Schema.Literals(["auto", "low"])),
+  output_format: Schema.optional(Schema.Literals(["png", "jpeg", "webp"])),
+  output_compression: Schema.optional(Schema.Int.check(Schema.isBetween({ minimum: 0, maximum: 100 }))),
+})
+export type OpenAIImageBody = Schema.Schema.Type<typeof OpenAIImageBody>
+
+const OpenAIImageResponse = Schema.Struct({
+  data: Schema.Array(
+    Schema.Struct({
+      b64_json: Schema.optional(Schema.String),
+      url: Schema.optional(Schema.String),
+      revised_prompt: Schema.optional(Schema.String),
+    }),
+  ),
+  output_format: Schema.optional(Schema.String),
+  usage: Schema.optional(
+    Schema.Struct({
+      input_tokens: Schema.optional(Schema.Number),
+      output_tokens: Schema.optional(Schema.Number),
+      total_tokens: Schema.optional(Schema.Number),
+      input_tokens_details: Schema.optional(Schema.Record(Schema.String, Schema.Unknown)),
+      output_tokens_details: Schema.optional(Schema.Record(Schema.String, Schema.Unknown)),
+    }),
+  ),
+})
+
+export interface ModelInput {
+  readonly id: string
+  readonly auth: AuthDefinition
+  readonly baseURL?: string
+  readonly headers?: Record<string, string>
+  readonly defaults?: ImageModelDefaults
+}
+
+const providerOptions = (request: ImageRequest): OpenAIImageOptions => ({
+  ...request.model.defaults?.providerOptions?.openai,
+  ...request.providerOptions?.openai,
+})
+
+const body = (request: ImageRequest): OpenAIImageBody => {
+  const options = providerOptions(request)
+  return {
+    model: request.model.id,
+    prompt: request.prompt,
+    n: request.count,
+    size: request.size === undefined ? undefined : `${request.size.width}x${request.size.height}`,
+    quality: options.quality,
+    background: options.background,
+    moderation: options.moderation,
+    output_format: options.outputFormat,
+    output_compression: options.outputCompression,
+  }
+}
+
+const invalidOutput = (message: string) =>
+  new LLMError({
+    module: ADAPTER,
+    method: "generate",
+    reason: new InvalidProviderOutputReason({ message, route: ADAPTER }),
+  })
+
+const applyQuery = (url: string, query: Record<string, string> | undefined) => {
+  if (!query) return url
+  const next = new URL(url)
+  Object.entries(query).forEach(([key, value]) => next.searchParams.set(key, value))
+  return next.toString()
+}
+
+const PROTOCOL_BODY_FIELDS = new Set([
+  "model",
+  "prompt",
+  "n",
+  "size",
+  "quality",
+  "background",
+  "moderation",
+  "output_format",
+  "output_compression",
+])
+
+const bodyWithOverlay = Effect.fn("OpenAIImages.bodyWithOverlay")(function* (
+  imageBody: OpenAIImageBody,
+  overlay: Record<string, unknown> | undefined,
+) {
+  if (!overlay) return imageBody
+  const reserved = Object.keys(overlay).filter((key) => PROTOCOL_BODY_FIELDS.has(key))
+  if (reserved.length > 0)
+    return yield* ProviderShared.invalidRequest(
+      `http.body cannot overlay protocol-owned field(s): ${reserved.join(", ")}`,
+    )
+  return mergeJsonRecords(imageBody, overlay) ?? imageBody
+})
+
+export const model = (input: ModelInput) => {
+  const route: ImageRoute = {
+    id: ADAPTER,
+    generate: Effect.fn("OpenAIImages.generate")(function* (request: ImageRequest, execute) {
+      if (request.aspectRatio !== undefined)
+        return yield* ProviderShared.invalidRequest("OpenAI Images does not support the common aspectRatio option")
+      if (request.seed !== undefined)
+        return yield* ProviderShared.invalidRequest("OpenAI Images does not support the common seed option")
+
+      const requestBody = yield* ProviderShared.validateWith(Schema.decodeUnknownEffect(OpenAIImageBody))(body(request))
+      const http = mergeHttpOptions(request.model.defaults?.http, request.http)
+      const overlaidBody = yield* bodyWithOverlay(requestBody, http?.body)
+      const text = ProviderShared.encodeJson(overlaidBody)
+      const url = applyQuery(`${(input.baseURL ?? DEFAULT_BASE_URL).replace(/\/$/, "")}${PATH}`, http?.query)
+      const headers = yield* Auth.toEffect(input.auth)({
+        request,
+        method: "POST",
+        url,
+        body: text,
+        headers: Headers.fromInput({ ...input.headers, ...http?.headers }),
+      })
+      const response = yield* execute(
+        HttpClientRequest.post(url).pipe(
+          HttpClientRequest.setHeaders(headers),
+          HttpClientRequest.bodyText(text, "application/json"),
+        ),
+      )
+      const payload = yield* response.json.pipe(
+        Effect.mapError(() => invalidOutput("Failed to read the OpenAI Images response")),
+      )
+      const decoded = yield* Schema.decodeUnknownEffect(OpenAIImageResponse)(payload).pipe(
+        Effect.mapError(() => invalidOutput("OpenAI Images returned an invalid response")),
+      )
+      const format = decoded.output_format ?? providerOptions(request).outputFormat ?? "png"
+      const images = yield* Effect.forEach(decoded.data, (item, index) => {
+        if (item.b64_json)
+          return Effect.fromResult(Encoding.decodeBase64(item.b64_json)).pipe(
+            Effect.mapError(() => invalidOutput(`OpenAI Images result ${index} contains invalid base64 data`)),
+            Effect.map(
+              (data) =>
+                new GeneratedImage({
+                  mediaType: `image/${format}`,
+                  data,
+                  providerMetadata:
+                    item.revised_prompt === undefined ? undefined : { openai: { revisedPrompt: item.revised_prompt } },
+                }),
+            ),
+          )
+        if (item.url)
+          return Effect.succeed(
+            new GeneratedImage({
+              mediaType: `image/${format}`,
+              data: item.url,
+              providerMetadata:
+                item.revised_prompt === undefined ? undefined : { openai: { revisedPrompt: item.revised_prompt } },
+            }),
+          )
+        return Effect.fail(invalidOutput(`OpenAI Images result ${index} has neither image data nor a URL`))
+      })
+      if (images.length === 0) return yield* invalidOutput("OpenAI Images returned no images")
+      return new ImageResponse({
+        images,
+        usage:
+          decoded.usage === undefined
+            ? undefined
+            : new Usage({
+                inputTokens: decoded.usage.input_tokens,
+                outputTokens: decoded.usage.output_tokens,
+                totalTokens: decoded.usage.total_tokens,
+                providerMetadata: { openai: decoded.usage },
+              }),
+        providerMetadata: { openai: { outputFormat: format } },
+      })
+    }),
+  }
+  return ImageModel.make({ id: input.id, provider: "openai", route, defaults: input.defaults })
+}
+
+export const OpenAIImages = {
+  model,
+} as const

packages/ai/src/protocols/openai-responses.ts

@@ -1,26 +1,31 @@
-import { Effect, Schema } from "effect"
+import { Effect, Encoding, Schema } from "effect"
 import { Route } from "../route/client"
 import { Auth } from "../route/auth"
 import { Endpoint } from "../route/endpoint"
 import { HttpTransport, WebSocketTransport } from "../route/transport"
 import { Protocol } from "../route/protocol"
 import {
+  LLMError,
   LLMEvent,
   Usage,
   type FinishReason,
+  type JsonSchema,
   type LLMRequest,
   type ProviderMetadata,
   type ReasoningPart,
   type TextPart,
   type ToolCallPart,
   type ToolDefinition,
-  type ToolResultContentPart,
+  type ToolContent,
   type ToolResultPart,
 } from "../schema"
 import { JsonObject, optionalArray, optionalNull, ProviderShared } from "./shared"
+import { classifyProviderFailure } from "../provider-error"
 import { OpenAIOptions } from "./utils/openai-options"
 import { Lifecycle } from "./utils/lifecycle"
+import { ToolSchemaProjection } from "./utils/tool-schema"
 import { ToolStream } from "./utils/tool-stream"
+import { OpenAIImage } from "./utils/openai-image"
 
 const ADAPTER = "openai-responses"
 export const DEFAULT_BASE_URL = "https://api.openai.com/v1"
@@ -52,7 +57,7 @@ const OpenAIResponsesReasoningSummaryText = Schema.Struct({
 
 const OpenAIResponsesReasoningItem = Schema.Struct({
   type: Schema.tag("reasoning"),
-  id: Schema.String,
+  id: Schema.optionalKey(Schema.String),
   summary: Schema.Array(OpenAIResponsesReasoningSummaryText),
   encrypted_content: optionalNull(Schema.String),
 })
@@ -100,6 +105,7 @@ type OpenAIResponsesReasoningInput = {
   summary: Array<{ type: "summary_text"; text: string }>
   encrypted_content?: string | null
 }
+type OpenAIResponsesReasoningReplay = Omit<OpenAIResponsesReasoningInput, "id">
 
 const OpenAIResponsesTool = Schema.Struct({
   type: Schema.tag("function"),
@@ -108,11 +114,24 @@ const OpenAIResponsesTool = Schema.Struct({
   parameters: JsonObject,
   strict: Schema.optional(Schema.Boolean),
 })
-type OpenAIResponsesTool = Schema.Schema.Type<typeof OpenAIResponsesTool>
+const OpenAIResponsesImageGenerationTool = Schema.Struct({
+  type: Schema.tag("image_generation"),
+  action: Schema.optional(Schema.Literals(["auto", "generate", "edit"])),
+  background: Schema.optional(Schema.Literals(["auto", "opaque", "transparent"])),
+  input_fidelity: Schema.optional(Schema.Literals(["low", "high"])),
+  output_compression: Schema.optional(Schema.Int.check(Schema.isBetween({ minimum: 0, maximum: 100 }))),
+  output_format: Schema.optional(Schema.Literals(["png", "jpeg", "webp"])),
+  partial_images: Schema.optional(Schema.Int.check(Schema.isGreaterThanOrEqualTo(0))),
+  quality: Schema.optional(Schema.Literals(["auto", "low", "medium", "high"])),
+  size: Schema.optional(OpenAIImage.Size),
+})
+const OpenAIResponsesTools = Schema.Union([OpenAIResponsesTool, OpenAIResponsesImageGenerationTool])
+type OpenAIResponsesTool = Schema.Schema.Type<typeof OpenAIResponsesTools>
 
 const OpenAIResponsesToolChoice = Schema.Union([
   Schema.Literals(["auto", "none", "required"]),
   Schema.Struct({ type: Schema.tag("function"), name: Schema.String }),
+  Schema.Struct({ type: Schema.tag("image_generation") }),
 ])
 
 // Fields shared between the HTTP body and the WebSocket `response.create`
@@ -123,9 +142,10 @@ const OpenAIResponsesCoreFields = {
   model: Schema.String,
   input: Schema.Array(OpenAIResponsesInputItem),
   instructions: Schema.optional(Schema.String),
-  tools: optionalArray(OpenAIResponsesTool),
+  tools: optionalArray(OpenAIResponsesTools),
   tool_choice: Schema.optional(OpenAIResponsesToolChoice),
   store: Schema.optional(Schema.Boolean),
+  service_tier: Schema.optional(OpenAIOptions.OpenAIServiceTier),
   prompt_cache_key: Schema.optional(Schema.String),
   include: optionalArray(OpenAIOptions.OpenAIResponseIncludable),
   reasoning: Schema.optional(
@@ -188,16 +208,18 @@ const OpenAIResponsesStreamItem = Schema.Struct({
   outputs: Schema.optional(Schema.Unknown),
   server_label: Schema.optional(Schema.String),
   output: Schema.optional(Schema.Unknown),
+  result: Schema.optional(Schema.String),
+  output_format: Schema.optional(Schema.Literals(["png", "jpeg", "webp"])),
   error: Schema.optional(Schema.Unknown),
   encrypted_content: optionalNull(Schema.String),
 })
 type OpenAIResponsesStreamItem = Schema.Schema.Type<typeof OpenAIResponsesStreamItem>
 
-// OpenAI Responses surfaces provider failures in two related shapes. The
-// streaming `error` event carries the details at the top level
-// (`{ type: "error", code, message, param, sequence_number }`), while
-// `response.failed` carries them under `response.error`. We capture both so
-// the parser can surface a useful provider-error message in either path.
+// The Responses schema puts streaming error details at the top level and
+// response failures under `response.error`. The official SDK also recognizes
+// an event-level HTTP-style `error` envelope, so accept all three shapes here.
+// https://github.com/openai/openai-openapi/blob/5162af98d3147432c14680df789e8e12d4891e6b/openapi.yaml#L67234-L67382
+// https://github.com/openai/openai-node/blob/61539248cbe04665de68a71e6fd878127ae4db87/src/core/streaming.ts#L58-L85
 const OpenAIResponsesErrorPayload = Schema.Struct({
   code: optionalNull(Schema.String),
   message: optionalNull(Schema.String),
@@ -222,9 +244,10 @@ const OpenAIResponsesEvent = Schema.Struct({
       [Schema.Record(Schema.String, Schema.Unknown)],
     ),
   ),
-  code: Schema.optional(Schema.String),
+  code: optionalNull(Schema.String),
   message: Schema.optional(Schema.String),
-  param: Schema.optional(Schema.String),
+  param: optionalNull(Schema.String),
+  error: optionalNull(OpenAIResponsesErrorPayload),
 })
 type OpenAIResponsesEvent = Schema.Schema.Type<typeof OpenAIResponsesEvent>
 
@@ -251,19 +274,41 @@ const invalid = ProviderShared.invalidRequest
 // =============================================================================
 // Request Lowering
 // =============================================================================
-const lowerTool = (tool: ToolDefinition): OpenAIResponsesTool => ({
-  type: "function",
-  name: tool.name,
-  description: tool.description,
-  parameters: tool.inputSchema,
+const nativeImageToolInput = (tool: ToolDefinition) => {
+  const native = tool.native?.openai
+  return ProviderShared.isRecord(native) && native.type === "image_generation" ? native : undefined
+}
+
+const nativeImageTool = (tool: ToolDefinition) => {
+  const native = nativeImageToolInput(tool)
+  return Schema.is(OpenAIResponsesImageGenerationTool)(native) ? native : undefined
+}
+
+const lowerTool = Effect.fn("OpenAIResponses.lowerTool")(function* (tool: ToolDefinition, inputSchema: JsonSchema) {
+  const native = nativeImageToolInput(tool)
+  if (native !== undefined) {
+    if (Schema.is(OpenAIResponsesImageGenerationTool)(native)) return native
+    return yield* invalid("OpenAI Responses image generation tool options are invalid")
+  }
+  return {
+    type: "function" as const,
+    name: tool.name,
+    description: tool.description,
+    parameters: ToolSchemaProjection.openAI(inputSchema),
+    // TODO: Read this from OpenAI-specific tool options so direct LLM callers can opt into strict schemas.
+    strict: false,
+  }
 })
 
-const lowerToolChoice = (toolChoice: NonNullable<LLMRequest["toolChoice"]>) =>
+const lowerToolChoice = (toolChoice: NonNullable<LLMRequest["toolChoice"]>, tools: ReadonlyArray<ToolDefinition>) =>
   ProviderShared.matchToolChoice("OpenAI Responses", toolChoice, {
     auto: () => "auto" as const,
     none: () => "none" as const,
     required: () => "required" as const,
-    tool: (name) => ({ type: "function" as const, name }),
+    tool: (name) =>
+      tools.some((tool) => tool.name === name && nativeImageTool(tool) !== undefined)
+        ? ({ type: "image_generation" } as const)
+        : { type: "function" as const, name },
   })
 
 const lowerToolCall = (part: ToolCallPart): OpenAIResponsesInputItem => ({
@@ -291,29 +336,40 @@ const lowerReasoning = (part: ReasoningPart): OpenAIResponsesReasoningInput | un
   }
 }
 
+const hostedToolItemID = (part: ToolResultPart) => {
+  const openai = part.providerMetadata?.openai
+  return ProviderShared.isRecord(openai) && typeof openai.itemId === "string" && openai.itemId.length > 0
+    ? openai.itemId
+    : undefined
+}
+
 const lowerUserContent = Effect.fn("OpenAIResponses.lowerUserContent")(function* (
   part: LLMRequest["messages"][number]["content"][number],
 ) {
   if (part.type === "text") return { type: "input_text" as const, text: part.text }
-  if (part.type === "media" && part.mediaType.startsWith("image/")) {
-    return { type: "input_image" as const, image_url: ProviderShared.mediaDataUrl(part) }
+  if (part.type === "media") {
+    const media = yield* ProviderShared.validateMedia(
+      "OpenAI Responses",
+      part,
+      new Set<string>(ProviderShared.IMAGE_MIMES),
+    )
+    return { type: "input_image" as const, image_url: media.dataUrl }
   }
-  if (part.type === "media") return yield* invalid("OpenAI Responses user media content only supports images")
   return yield* ProviderShared.unsupportedContent("OpenAI Responses", "user", ["text", "media"])
 })
 
 // Tool results may carry structured text/images. Keep media as provider-native
 // content instead of JSON-stringifying base64 into a prompt string.
 const lowerToolResultContentItem = Effect.fn("OpenAIResponses.lowerToolResultContentItem")(function* (
-  item: ToolResultContentPart,
+  item: ToolContent,
 ) {
   if (item.type === "text") return { type: "input_text" as const, text: item.text }
-  if (item.mediaType.startsWith("image/"))
-    return {
-      type: "input_image" as const,
-      image_url: ProviderShared.mediaDataUrl(item),
-    }
-  return yield* invalid(`OpenAI Responses tool-result media content only supports images, got ${item.mediaType}`)
+  const media = yield* ProviderShared.validateToolFile(
+    "OpenAI Responses",
+    item,
+    new Set<string>(ProviderShared.IMAGE_MIMES),
+  )
+  return { type: "input_image" as const, image_url: media.dataUrl }
 })
 
 const lowerToolResultOutput = Effect.fn("OpenAIResponses.lowerToolResultOutput")(function* (part: ToolResultPart) {
@@ -321,7 +377,7 @@ const lowerToolResultOutput = Effect.fn("OpenAIResponses.lowerToolResultOutput")
   // compatibility with existing cassettes and provider expectations.
   if (part.result.type !== "content") return ProviderShared.toolResultText(part)
   // Preserve the narrowed array element type when compiled through a consumer package.
-  const content: ReadonlyArray<ToolResultContentPart> = part.result.value
+  const content: ReadonlyArray<ToolContent> = part.result.value
   return yield* Effect.forEach(content, lowerToolResultContentItem)
 })
 
@@ -332,6 +388,18 @@ const lowerMessages = Effect.fn("OpenAIResponses.lowerMessages")(function* (requ
   const store = OpenAIOptions.store(request)
 
   for (const message of request.messages) {
+    if (message.role === "system") {
+      const part = yield* ProviderShared.wrappedSystemUpdate("OpenAI Responses", message)
+      const previous = input.at(-1)
+      if (previous && "role" in previous && previous.role === "user")
+        input[input.length - 1] = {
+          role: "user",
+          content: [...previous.content, { type: "input_text", text: part.text }],
+        }
+      else input.push({ role: "user", content: [{ type: "input_text", text: part.text }] })
+      continue
+    }
+
     if (message.role === "user") {
       input.push({ role: "user", content: yield* Effect.forEach(message.content, lowerUserContent) })
       continue
@@ -339,8 +407,9 @@ const lowerMessages = Effect.fn("OpenAIResponses.lowerMessages")(function* (requ
 
     if (message.role === "assistant") {
       const content: TextPart[] = []
-      const reasoningItems: Record<string, OpenAIResponsesReasoningInput> = {}
+      const reasoningItems: Record<string, OpenAIResponsesReasoningReplay> = {}
       const reasoningReferences = new Set<string>()
+      const hostedToolReferences = new Set<string>()
       const flushText = () => {
         if (content.length === 0) return
         input.push({ role: "assistant", content: content.map((part) => ({ type: "output_text", text: part.text })) })
@@ -355,7 +424,7 @@ const lowerMessages = Effect.fn("OpenAIResponses.lowerMessages")(function* (requ
           flushText()
           const reasoning = lowerReasoning(part)
           if (!reasoning) continue
-          if (store !== false && reasoning.id) {
+          if (store !== false) {
             if (!reasoningReferences.has(reasoning.id)) input.push({ type: "item_reference", id: reasoning.id })
             reasoningReferences.add(reasoning.id)
             continue
@@ -367,19 +436,41 @@ const lowerMessages = Effect.fn("OpenAIResponses.lowerMessages")(function* (requ
               existing.encrypted_content = reasoning.encrypted_content
             continue
           }
-          reasoningItems[reasoning.id] = reasoning
-          input.push(reasoning)
+          const replay = {
+            type: reasoning.type,
+            summary: reasoning.summary,
+            encrypted_content: reasoning.encrypted_content,
+          }
+          reasoningItems[reasoning.id] = replay
+          input.push(replay)
           continue
         }
         if (part.type === "tool-call") {
           flushText()
+          if (part.providerExecuted === true) continue
           input.push(lowerToolCall(part))
           continue
         }
+        if (part.type === "tool-result" && part.providerExecuted === true) {
+          flushText()
+          const itemID = hostedToolItemID(part)
+          if (store !== false && itemID && !hostedToolReferences.has(itemID))
+            input.push({ type: "item_reference", id: itemID })
+          if (store === false && part.name === "image_generation" && part.result.type === "content") {
+            const content: ReadonlyArray<ToolContent> = part.result.value
+            input.push({
+              role: "user",
+              content: yield* Effect.forEach(content, lowerToolResultContentItem),
+            })
+          }
+          if (itemID) hostedToolReferences.add(itemID)
+          continue
+        }
         return yield* ProviderShared.unsupportedContent("OpenAI Responses", "assistant", [
           "text",
           "reasoning",
           "tool-call",
+          "tool-result",
         ])
       }
       flushText()
@@ -411,12 +502,11 @@ const lowerOptions = Effect.fn("OpenAIResponses.lowerOptions")(function* (reques
   const store = OpenAIOptions.store(request)
   const promptCacheKey = OpenAIOptions.promptCacheKey(request)
   const effort = OpenAIOptions.reasoningEffort(request)
-  if (effort && !OpenAIOptions.isReasoningEffort(effort))
-    return yield* invalid(`OpenAI Responses does not support reasoning effort ${effort}`)
   const summary = OpenAIOptions.reasoningSummary(request)
   const include = OpenAIOptions.include(request)
   const verbosity = OpenAIOptions.textVerbosity(request)
   const instructions = OpenAIOptions.instructions(request)
+  const serviceTier = OpenAIOptions.serviceTier(request)
   return {
     ...(instructions ? { instructions } : {}),
     ...(store !== undefined ? { store } : {}),
@@ -424,17 +514,24 @@ const lowerOptions = Effect.fn("OpenAIResponses.lowerOptions")(function* (reques
     ...(include ? { include } : {}),
     ...(effort || summary ? { reasoning: { effort, summary } } : {}),
     ...(verbosity ? { text: { verbosity } } : {}),
+    ...(serviceTier ? { service_tier: serviceTier } : {}),
   }
 })
 
 const fromRequest = Effect.fn("OpenAIResponses.fromRequest")(function* (request: LLMRequest) {
   const generation = request.generation
   const options = yield* lowerOptions(request)
+  const toolSchemaCompatibility = request.model.compatibility?.toolSchema
   return {
     model: request.model.id,
     input: yield* lowerMessages(request),
-    tools: request.tools.length === 0 ? undefined : request.tools.map(lowerTool),
-    tool_choice: request.toolChoice ? yield* lowerToolChoice(request.toolChoice) : undefined,
+    tools:
+      request.tools.length === 0
+        ? undefined
+        : yield* Effect.forEach(request.tools, (tool) =>
+            lowerTool(tool, ToolSchemaProjection.modelCompatibility(tool.inputSchema, toolSchemaCompatibility)),
+          ),
+    tool_choice: request.toolChoice ? yield* lowerToolChoice(request.toolChoice, request.tools) : undefined,
     stream: true as const,
     max_output_tokens: generation?.maxTokens,
     temperature: generation?.temperature,
@@ -520,14 +617,29 @@ const isReasoningItem = (
 
 // Round-trip the full item as the structured result so consumers can extract
 // outputs / sources / status without re-decoding.
-const hostedToolResult = (item: OpenAIResponsesStreamItem) => {
+const hostedToolResult = Effect.fn("OpenAIResponses.hostedToolResult")(function* (item: OpenAIResponsesStreamItem) {
   const isError = typeof item.error !== "undefined" && item.error !== null
+  if (item.type === "image_generation_call" && item.result) {
+    yield* Effect.fromResult(Encoding.decodeBase64(item.result)).pipe(
+      Effect.mapError(() => ProviderShared.eventError(ADAPTER, "OpenAI Responses returned invalid image base64")),
+    )
+    return {
+      type: "content" as const,
+      value: [
+        {
+          type: "file" as const,
+          uri: `data:image/${item.output_format ?? "png"};base64,${item.result}`,
+          mime: `image/${item.output_format ?? "png"}`,
+        },
+      ],
+    }
+  }
   return isError ? { type: "error" as const, value: item.error } : { type: "json" as const, value: item }
-}
+})
 
-const hostedToolEvents = (
+const hostedToolEvents = Effect.fn("OpenAIResponses.hostedToolEvents")(function* (
   item: OpenAIResponsesStreamItem & { type: HostedToolType; id: string },
-): ReadonlyArray<LLMEvent> => {
+) {
   const tool = HOSTED_TOOLS[item.type]
   const providerMetadata = openaiMetadata({ itemId: item.id })
   return [
@@ -541,21 +653,20 @@ const hostedToolEvents = (
     LLMEvent.toolResult({
       id: item.id,
       name: tool.name,
-      result: hostedToolResult(item),
+      result: yield* hostedToolResult(item),
       providerExecuted: true,
       providerMetadata,
     }),
   ]
-}
+})
 
 type StepResult = readonly [ParserState, ReadonlyArray<LLMEvent>]
 
 const NO_EVENTS: StepResult["1"] = []
 
 // `response.completed` / `response.incomplete` are clean finishes that emit a
-// `finish` event; `response.failed` is a hard failure that emits a
-// `provider-error`. All three end the stream — kept in one set so `step` and
-// the protocol's `terminal` predicate stay in sync.
+// `finish` event; `response.failed` is a hard failure. All three end the stream,
+// so keep this set aligned with `step` and the protocol's terminal predicate.
 const TERMINAL_TYPES = new Set(["response.completed", "response.incomplete", "response.failed"])
 
 const onOutputTextDelta = (state: ParserState, event: OpenAIResponsesEvent): StepResult => {
@@ -567,6 +678,11 @@ const onOutputTextDelta = (state: ParserState, event: OpenAIResponsesEvent): Ste
   ]
 }
 
+const onOutputTextDone = (state: ParserState, event: OpenAIResponsesEvent): StepResult => {
+  const events: LLMEvent[] = []
+  return [{ ...state, lifecycle: Lifecycle.textEnd(state.lifecycle, events, event.item_id ?? "text-0") }, events]
+}
+
 const onReasoningDelta = (state: ParserState, event: OpenAIResponsesEvent): StepResult => {
   if (!event.delta) return [state, NO_EVENTS]
   const events: LLMEvent[] = []
@@ -758,6 +874,8 @@ const onOutputItemDone = Effect.fn("OpenAIResponses.onOutputItemDone")(function*
   const item = event.item
   if (!item) return [state, NO_EVENTS] satisfies StepResult
 
+  if (item.type === "message" && item.id) return onOutputTextDone(state, { ...event, item_id: item.id })
+
   if (item.type === "function_call") {
     if (!item.id || !item.call_id || !item.name) return [state, NO_EVENTS] satisfies StepResult
     const tools = state.tools[item.id]
@@ -775,7 +893,9 @@ const onOutputItemDone = Effect.fn("OpenAIResponses.onOutputItemDone")(function*
       {
         ...state,
         lifecycle,
-        hasFunctionCall: resultEvents.some(LLMEvent.is.toolCall) ? true : state.hasFunctionCall,
+        hasFunctionCall:
+          resultEvents.some((event) => LLMEvent.is.toolCall(event) || LLMEvent.is.toolInputError(event)) ||
+          state.hasFunctionCall,
         tools: result.tools,
       },
       events,
@@ -785,7 +905,7 @@ const onOutputItemDone = Effect.fn("OpenAIResponses.onOutputItemDone")(function*
   if (isHostedToolItem(item)) {
     const events: LLMEvent[] = []
     const lifecycle = Lifecycle.stepStart(state.lifecycle, events)
-    events.push(...hostedToolEvents(item))
+    events.push(...(yield* hostedToolEvents(item)))
     return [{ ...state, lifecycle }, events] satisfies StepResult
   }
 
@@ -840,25 +960,26 @@ const onResponseFinish = (state: ParserState, event: OpenAIResponsesEvent): Step
 // the bare message — production rate limits and context-length failures used
 // to be indistinguishable from generic stream drops.
 const providerErrorMessage = (event: OpenAIResponsesEvent, fallback: string): string => {
-  const nested = event.response?.error ?? undefined
+  const nested = event.error ?? event.response?.error ?? undefined
   const message = event.message || nested?.message || undefined
   const code = event.code || nested?.code || undefined
   if (message && code) return `${code}: ${message}`
   return message || code || fallback
 }
 
-const onResponseFailed = (state: ParserState, event: OpenAIResponsesEvent): StepResult => [
-  state,
-  [LLMEvent.providerError({ message: providerErrorMessage(event, "OpenAI Responses response failed") })],
-]
-
-const onError = (state: ParserState, event: OpenAIResponsesEvent): StepResult => [
-  state,
-  [LLMEvent.providerError({ message: providerErrorMessage(event, "OpenAI Responses stream error") })],
-]
+const providerError = (event: OpenAIResponsesEvent, fallback: string) => {
+  const code = event.code || event.error?.code || event.response?.error?.code || undefined
+  const message = providerErrorMessage(event, fallback)
+  return new LLMError({
+    module: ADAPTER,
+    method: "stream",
+    reason: classifyProviderFailure({ message, code }),
+  })
+}
 
 const step = (state: ParserState, event: OpenAIResponsesEvent) => {
   if (event.type === "response.output_text.delta") return Effect.succeed(onOutputTextDelta(state, event))
+  if (event.type === "response.output_text.done") return Effect.succeed(onOutputTextDone(state, event))
   if (
     event.type === "response.reasoning_text.delta" ||
     event.type === "response.reasoning_summary.delta" ||
@@ -880,8 +1001,8 @@ const step = (state: ParserState, event: OpenAIResponsesEvent) => {
   if (event.type === "response.output_item.done") return onOutputItemDone(state, event)
   if (event.type === "response.completed" || event.type === "response.incomplete")
     return Effect.succeed(onResponseFinish(state, event))
-  if (event.type === "response.failed") return Effect.succeed(onResponseFailed(state, event))
-  if (event.type === "error") return Effect.succeed(onError(state, event))
+  if (event.type === "response.failed") return providerError(event, "OpenAI Responses response failed")
+  if (event.type === "error") return providerError(event, "OpenAI Responses stream error")
   return Effect.succeed<StepResult>([state, NO_EVENTS])
 }
 
@@ -921,10 +1042,12 @@ export const httpTransport = HttpTransport.sseJson.with<OpenAIResponsesBody>()
 export const route = Route.make({
   id: ADAPTER,
   provider: "openai",
+  providerMetadataKey: "openai",
   protocol,
   endpoint,
   auth,
   transport: httpTransport,
+  defaults: { providerOptions: { openai: { store: false } } },
 })
 
 const decodeWebSocketMessage = ProviderShared.validateWith(Schema.decodeUnknownEffect(OpenAIResponsesWebSocketMessage))
@@ -948,10 +1071,12 @@ export const webSocketTransport = WebSocketTransport.jsonTransport.with<
 export const webSocketRoute = Route.make({
   id: `${ADAPTER}-websocket`,
   provider: "openai",
+  providerMetadataKey: "openai",
   protocol,
   endpoint,
   auth,
   transport: webSocketTransport,
+  defaults: { providerOptions: { openai: { store: false } } },
 })
 
 export * as OpenAIResponses from "./openai-responses"

packages/ai/src/protocols/shared.ts

@@ -9,13 +9,17 @@ import {
   type ContentPart,
   type LLMRequest,
   type MediaPart,
+  type ToolFileContent,
+  type TextPart,
   type ToolResultPart,
 } from "../schema"
-export { isRecord } from "../utils/record"
+import { isRecord } from "../utils/record"
+export { isRecord }
 
 export const Json = Schema.fromJsonString(Schema.Unknown)
 export const decodeJson = Schema.decodeUnknownSync(Json)
 export const encodeJson = Schema.encodeSync(Json)
+const isJson = Schema.is(Schema.Json)
 export const JsonObject = Schema.Record(Schema.String, Schema.Unknown)
 export const optionalArray = <const S extends Schema.Top>(schema: S) => Schema.optional(Schema.Array(schema))
 export const optionalNull = <const S extends Schema.Top>(schema: S) => Schema.optional(Schema.NullOr(schema))
@@ -104,6 +108,44 @@ export const parseJson = (route: string, input: string, message: string) =>
  */
 export const joinText = (parts: ReadonlyArray<{ readonly text: string }>) => parts.map((part) => part.text).join("\n")
 
+const escapeSystemUpdateText = (text: string) =>
+  text.replaceAll("&", "&amp;").replaceAll("<", "&lt;").replaceAll(">", "&gt;")
+
+/**
+ * Stable fallback representation for chronological `Message.system(...)`
+ * updates on routes that do not support that privileged role natively. The
+ * wrapper remains visibly lower-authority user text, preserves the original
+ * temporal position, and XML-escapes content so it cannot close the wrapper.
+ */
+export const wrapSystemUpdate = (parts: ReadonlyArray<{ readonly text: string }>) =>
+  `<system-update>\n${escapeSystemUpdateText(joinText(parts))}\n</system-update>`
+
+/**
+ * Chronological system updates deliberately accept text only. Do not insert
+ * raw retrieved, tool, or web content into privileged updates: keep untrusted
+ * data in ordinary user/tool messages instead.
+ */
+export const systemUpdateText = Effect.fn("ProviderShared.systemUpdateText")(function* (
+  route: string,
+  message: LLMRequest["messages"][number],
+) {
+  const content: TextPart[] = []
+  for (const part of message.content) {
+    if (!supportsContent(part, ["text"])) return yield* unsupportedContent(route, "system", ["text"])
+    content.push(part)
+  }
+  return content
+})
+
+/** Lower an unsupported privileged update into visible, in-order user text. */
+export const wrappedSystemUpdate = Effect.fn("ProviderShared.wrappedSystemUpdate")(function* (
+  route: string,
+  message: LLMRequest["messages"][number],
+) {
+  const content = yield* systemUpdateText(route, message)
+  return { type: "text" as const, text: wrapSystemUpdate(content), cache: content.at(-1)?.cache }
+})
+
 /**
  * Parse the streamed JSON input of a tool call. Treats an empty string as
  * `"{}"` — providers occasionally finish a tool call without ever emitting
@@ -113,30 +155,70 @@ export const joinText = (parts: ReadonlyArray<{ readonly text: string }>) => par
 export const parseToolInput = (route: string, name: string, raw: string) =>
   parseJson(route, raw || "{}", `Invalid JSON input for ${route} tool call ${name}`)
 
-/**
- * Encode a `MediaPart`'s raw bytes for inclusion in a JSON request body.
- * `data: string` is assumed to already be base64 (matches caller convention
- * across Gemini / Bedrock); `data: Uint8Array` is base64-encoded here. Used
- * by every route that supports image / document inputs.
- */
-export const mediaBytes = (part: MediaPart) =>
-  typeof part.data === "string" ? part.data : Buffer.from(part.data).toString("base64")
+export const IMAGE_MIMES = ["image/png", "image/jpeg", "image/gif", "image/webp"] as const
+export const VIDEO_MIMES = ["video/mp4", "video/webm", "video/quicktime"] as const
+export const AUDIO_MIMES = ["audio/wav", "audio/mp3", "audio/aiff", "audio/aac", "audio/ogg", "audio/flac"] as const
+export const MEDIA_MIMES = [...IMAGE_MIMES, ...VIDEO_MIMES, ...AUDIO_MIMES] as const
+export const MAX_MEDIA_ENCODED_BYTES = 28 * 1024 * 1024
+export const MAX_MEDIA_DECODED_BYTES = 20 * 1024 * 1024
 
-export const mediaBase64 = (part: MediaPart) => {
-  if (typeof part.data !== "string" || !part.data.startsWith("data:")) return mediaBytes(part)
-  return part.data.slice(part.data.indexOf(",") + 1)
+const base64Pattern = /^(?:[A-Za-z0-9+/]{4})*(?:[A-Za-z0-9+/]{2}==|[A-Za-z0-9+/]{3}=)?$/
+
+export interface ValidatedMedia {
+  readonly mime: string
+  readonly base64: string
+  readonly dataUrl: string
+  readonly bytes: Uint8Array
 }
 
-export const mediaDataUrl = (part: MediaPart) =>
-  typeof part.data === "string" && part.data.startsWith("data:")
-    ? part.data
-    : `data:${part.mediaType};base64,${mediaBytes(part)}`
+export const validateMedia = Effect.fn("ProviderShared.validateMedia")(function* (
+  route: string,
+  part: MediaPart,
+  supportedMimes: ReadonlySet<string>,
+) {
+  const mime = part.mediaType.toLowerCase()
+  if (!supportedMimes.has(mime)) return yield* invalidRequest(`${route} does not support media type ${part.mediaType}`)
+
+  let base64: string
+  if (typeof part.data !== "string") {
+    if (part.data.byteLength > MAX_MEDIA_DECODED_BYTES)
+      return yield* invalidRequest(`${route} media exceeds the ${MAX_MEDIA_DECODED_BYTES} byte decoded limit`)
+    base64 = Buffer.from(part.data).toString("base64")
+  } else if (part.data.startsWith("data:")) {
+    const match = /^data:([^;,]+);base64,([A-Za-z0-9+/]*={0,2})$/s.exec(part.data)
+    if (!match) return yield* invalidRequest(`${route} media data URL must contain valid base64`)
+    if (match[1]!.toLowerCase() !== mime)
+      return yield* invalidRequest(`${route} media type ${part.mediaType} does not match data URL type ${match[1]}`)
+    base64 = match[2]!
+  } else {
+    base64 = part.data
+  }
+
+  if (Buffer.byteLength(base64, "utf8") > MAX_MEDIA_ENCODED_BYTES)
+    return yield* invalidRequest(`${route} media exceeds the ${MAX_MEDIA_ENCODED_BYTES} byte encoded limit`)
+  if (!base64 || base64.length % 4 !== 0 || !base64Pattern.test(base64))
+    return yield* invalidRequest(`${route} media must contain valid base64`)
+  const bytes = Buffer.from(base64, "base64")
+  if (bytes.byteLength > MAX_MEDIA_DECODED_BYTES)
+    return yield* invalidRequest(`${route} media exceeds the ${MAX_MEDIA_DECODED_BYTES} byte decoded limit`)
+  if (bytes.toString("base64") !== base64) return yield* invalidRequest(`${route} media must contain canonical base64`)
+  return { mime, base64, dataUrl: `data:${mime};base64,${base64}`, bytes } satisfies ValidatedMedia
+})
+
+export const validateToolFile = (route: string, part: ToolFileContent, supportedMimes: ReadonlySet<string>) =>
+  validateMedia(route, { type: "media", mediaType: part.mime, data: part.uri, filename: part.name }, supportedMimes)
 
 export const trimBaseUrl = (value: string) => value.replace(/\/+$/, "")
 
 export const toolResultText = (part: ToolResultPart) => {
-  if (part.result.type === "text" || part.result.type === "error") return String(part.result.value)
-  if (part.result.type === "content") return encodeJson(part.result.value)
+  if (part.result.type === "text") return String(part.result.value)
+  if (part.result.type === "error") {
+    const value = part.result.value
+    const prototype =
+      typeof value === "object" && value !== null && !Array.isArray(value) && Object.getPrototypeOf(value)
+    const structured = Array.isArray(value) || prototype === Object.prototype || prototype === null
+    return structured && isJson(value) ? encodeJson(value) : String(value)
+  }
   return encodeJson(part.result.value)
 }
 

packages/ai/src/protocols/utils/bedrock-media.ts

@@ -49,15 +49,11 @@ const DOCUMENT_FORMATS = {
   "text/markdown": "md",
 } as const satisfies Record<string, DocumentFormat>
 
-const imageBlock = (part: MediaPart, format: ImageFormat): ImageBlock => ({
-  image: { format, source: { bytes: ProviderShared.mediaBytes(part) } },
-})
-
-const documentBlock = (part: MediaPart, format: DocumentFormat): DocumentBlock => ({
+const documentBlock = (part: MediaPart, format: DocumentFormat, bytes: string): DocumentBlock => ({
   document: {
     format,
     name: part.filename ?? `document.${format}`,
-    source: { bytes: ProviderShared.mediaBytes(part) },
+    source: { bytes },
   },
 })
 
@@ -66,15 +62,29 @@ const documentBlock = (part: MediaPart, format: DocumentFormat): DocumentBlock =
 // document block. Image MIME types not in `IMAGE_FORMATS` (e.g. `image/svg+xml`)
 // get an image-specific error so the caller knows it's a format-support issue,
 // not a kind-detection issue.
-export const lower = (part: MediaPart) => {
+export const lower = Effect.fn("BedrockMedia.lower")(function* (part: MediaPart) {
   const mime = part.mediaType.toLowerCase()
   const imageFormat = IMAGE_FORMATS[mime as keyof typeof IMAGE_FORMATS]
-  if (imageFormat) return Effect.succeed(imageBlock(part, imageFormat))
+  if (imageFormat) {
+    const media = yield* ProviderShared.validateMedia(
+      "Bedrock Converse",
+      part,
+      new Set<string>(Object.keys(IMAGE_FORMATS)),
+    )
+    return { image: { format: imageFormat, source: { bytes: media.base64 } } } satisfies ImageBlock
+  }
   if (mime.startsWith("image/"))
-    return ProviderShared.invalidRequest(`Bedrock Converse does not support image media type ${part.mediaType}`)
+    return yield* ProviderShared.invalidRequest(`Bedrock Converse does not support image media type ${part.mediaType}`)
   const documentFormat = DOCUMENT_FORMATS[mime as keyof typeof DOCUMENT_FORMATS]
-  if (documentFormat) return Effect.succeed(documentBlock(part, documentFormat))
-  return ProviderShared.invalidRequest(`Bedrock Converse does not support media type ${part.mediaType}`)
-}
+  if (documentFormat) {
+    const media = yield* ProviderShared.validateMedia(
+      "Bedrock Converse",
+      part,
+      new Set<string>(Object.keys(DOCUMENT_FORMATS)),
+    )
+    return documentBlock(part, documentFormat, media.base64)
+  }
+  return yield* ProviderShared.invalidRequest(`Bedrock Converse does not support media type ${part.mediaType}`)
+})
 
 export * as BedrockMedia from "./bedrock-media"

packages/ai/src/protocols/utils/gemini-tool-schema.ts

@@ -1,4 +1,4 @@
-import { ProviderShared } from "../shared"
+import { isRecord } from "../../utils/record"
 
 // Gemini accepts a JSON Schema-like dialect for tool parameters, but rejects a
 // handful of common JSON Schema shapes. Keep this projection isolated so the
@@ -20,8 +20,6 @@ const SCHEMA_INTENT_KEYS = [
   "else",
 ]
 
-const isRecord = ProviderShared.isRecord
-
 const hasCombiner = (schema: unknown) =>
   isRecord(schema) && (Array.isArray(schema.anyOf) || Array.isArray(schema.oneOf) || Array.isArray(schema.allOf))
 

packages/ai/src/protocols/utils/lifecycle.ts

@@ -36,9 +36,15 @@ export const reasoningStart = (
   return { ...stepped, reasoning: new Set([...stepped.reasoning, id]) }
 }
 
-export const reasoningDelta = (state: State, events: LLMEvent[], id: string, text: string): State => {
-  const started = reasoningStart(state, events, id)
-  events.push(LLMEvent.reasoningDelta({ id, text }))
+export const reasoningDelta = (
+  state: State,
+  events: LLMEvent[],
+  id: string,
+  text: string,
+  providerMetadata?: ProviderMetadata,
+): State => {
+  const started = reasoningStart(state, events, id, providerMetadata)
+  events.push(LLMEvent.reasoningDelta({ id, text, providerMetadata }))
   return started
 }
 

packages/ai/src/protocols/utils/openai-image.ts

@@ -0,0 +1,20 @@
+import { Schema } from "effect"
+
+const dimensions = (value: string) => {
+  const match = /^(\d+)x(\d+)$/.exec(value)
+  if (!match) return undefined
+  return { width: Number(match[1]), height: Number(match[2]) }
+}
+
+export const Size = Schema.String.check(
+  Schema.makeFilter((value) => {
+    if (value === "auto") return undefined
+    const parsed = dimensions(value)
+    if (!parsed) return "image size must be `auto` or `{width}x{height}`"
+    return parsed.width > 0 && parsed.height > 0 ? undefined : "image dimensions must be positive integers"
+  }),
+)
+
+export const OpenAIImage = {
+  Size,
+} as const

packages/ai/src/protocols/utils/openai-options.ts

@@ -1,11 +1,9 @@
 import { Schema } from "effect"
-import type { LLMRequest, ReasoningEffort, TextVerbosity as TextVerbosityValue } from "../../schema"
+import type { LLMRequest, TextVerbosity as TextVerbosityValue } from "../../schema"
 import { ReasoningEfforts, TextVerbosity } from "../../schema"
 
-export const OpenAIReasoningEfforts = ReasoningEfforts.filter(
-  (effort): effort is Exclude<ReasoningEffort, "max"> => effort !== "max",
-)
-export type OpenAIReasoningEffort = (typeof OpenAIReasoningEfforts)[number]
+export const OpenAIReasoningEfforts = ReasoningEfforts
+export type OpenAIReasoningEffort = string
 
 // Mirrors OpenAI's `ResponseIncludable` union from the official SDK. Keep this
 // in lockstep with `openai-node/src/resources/responses/responses.ts`.
@@ -20,21 +18,19 @@ export const OpenAIResponseIncludables = [
   "message.output_text.logprobs",
 ] as const
 export type OpenAIResponseIncludable = (typeof OpenAIResponseIncludables)[number]
+export const OpenAIServiceTiers = ["auto", "default", "flex", "priority"] as const
+export type OpenAIServiceTier = (typeof OpenAIServiceTiers)[number]
 
-const REASONING_EFFORTS = new Set<string>(ReasoningEfforts)
-const OPENAI_REASONING_EFFORTS = new Set<string>(OpenAIReasoningEfforts)
 const TEXT_VERBOSITY = new Set<string>(["low", "medium", "high"])
 const INCLUDABLES = new Set<string>(OpenAIResponseIncludables)
+const SERVICE_TIERS = new Set<string>(OpenAIServiceTiers)
 
-export const OpenAIReasoningEffort = Schema.Literals(OpenAIReasoningEfforts)
+export const OpenAIReasoningEffort = Schema.String
 export const OpenAITextVerbosity = TextVerbosity
 export const OpenAIResponseIncludable = Schema.Literals(OpenAIResponseIncludables)
+export const OpenAIServiceTier = Schema.Literals(OpenAIServiceTiers)
 
-const isAnyReasoningEffort = (effort: unknown): effort is ReasoningEffort =>
-  typeof effort === "string" && REASONING_EFFORTS.has(effort)
-
-export const isReasoningEffort = (effort: unknown): effort is OpenAIReasoningEffort =>
-  typeof effort === "string" && OPENAI_REASONING_EFFORTS.has(effort)
+export const isReasoningEffort = (effort: unknown): effort is OpenAIReasoningEffort => typeof effort === "string"
 
 const isTextVerbosity = (value: unknown): value is TextVerbosityValue =>
   typeof value === "string" && TEXT_VERBOSITY.has(value)
@@ -46,9 +42,9 @@ export const store = (request: LLMRequest): boolean | undefined => {
   return typeof value === "boolean" ? value : undefined
 }
 
-export const reasoningEffort = (request: LLMRequest): ReasoningEffort | undefined => {
+export const reasoningEffort = (request: LLMRequest): string | undefined => {
   const value = options(request)?.reasoningEffort
-  return isAnyReasoningEffort(value) ? value : undefined
+  return typeof value === "string" ? value : undefined
 }
 
 export const reasoningSummary = (request: LLMRequest): "auto" | undefined =>
@@ -76,6 +72,11 @@ export const textVerbosity = (request: LLMRequest) => {
   return isTextVerbosity(value) ? value : undefined
 }
 
+export const serviceTier = (request: LLMRequest) => {
+  const value = options(request)?.serviceTier
+  return typeof value === "string" && SERVICE_TIERS.has(value) ? (value as OpenAIServiceTier) : undefined
+}
+
 export const instructions = (request: LLMRequest) => {
   const value = options(request)?.instructions
   return typeof value === "string" ? value : undefined

packages/ai/src/protocols/utils/tool-schema.ts

@@ -0,0 +1,86 @@
+import type { JsonSchema, ModelToolSchemaCompatibility } from "../../schema"
+import { isRecord } from "../../utils/record"
+import { GeminiToolSchema } from "./gemini-tool-schema"
+
+const removeNullSchemas = (value: unknown): unknown => {
+  if (Array.isArray(value)) return value.map(removeNullSchemas)
+  if (!isRecord(value)) return value
+  const fields = Object.fromEntries(
+    Object.entries(value)
+      .filter(([key]) => key !== "anyOf")
+      .map(([key, field]) => [key, removeNullSchemas(field)]),
+  )
+  if (!Array.isArray(value.anyOf)) return fields
+  const variants = value.anyOf.filter((variant) => !isRecord(variant) || variant.type !== "null").map(removeNullSchemas)
+  if (variants.length === 1 && isRecord(variants[0])) return { ...fields, ...variants[0] }
+  return { ...fields, anyOf: variants }
+}
+
+const tupleItemsSchema = (items: ReadonlyArray<unknown>) => {
+  const projected = items.map(moonshotNode)
+  if (projected.length === 0) return {}
+  if (projected.length === 1) return projected[0]
+  return { anyOf: projected }
+}
+
+const moonshotNode = (schema: unknown): unknown => {
+  if (Array.isArray(schema)) return schema.map(moonshotNode)
+  if (!isRecord(schema)) return schema
+  if (typeof schema.$ref === "string") return { $ref: schema.$ref }
+  return Object.fromEntries(
+    Object.entries(schema).flatMap(([key, value]) => {
+      if (key === "items" && Array.isArray(value)) return [[key, tupleItemsSchema(value)]]
+      if (key === "prefixItems") {
+        if ("items" in schema) return []
+        return [["items", tupleItemsSchema(Array.isArray(value) ? value : [])]]
+      }
+      if (key === "unevaluatedItems") return []
+      return [[key, moonshotNode(value)]]
+    }),
+  )
+}
+
+const moonshot = (schema: JsonSchema): JsonSchema => {
+  const projected = moonshotNode(schema)
+  return isRecord(projected) ? projected : {}
+}
+
+const openAI = (schema: JsonSchema): JsonSchema => {
+  const variants = Array.isArray(schema.anyOf) ? schema.anyOf.filter(isRecord) : []
+  const flattened =
+    variants.length === 0
+      ? { ...schema, type: "object" }
+      : {
+          ...Object.fromEntries(Object.entries(schema).filter(([key]) => key !== "anyOf")),
+          type: "object",
+          properties: variants.reduce(
+            (properties, variant) => ({ ...(isRecord(variant.properties) ? variant.properties : {}), ...properties }),
+            {},
+          ),
+          additionalProperties: false,
+        }
+  const normalized = removeNullSchemas(flattened)
+  return isRecord(normalized) ? normalized : { type: "object" }
+}
+
+const gemini = (schema: JsonSchema): JsonSchema => GeminiToolSchema.convert(schema) ?? {}
+
+const modelCompatibility = (
+  schema: JsonSchema,
+  compatibility: ModelToolSchemaCompatibility | undefined,
+): JsonSchema => {
+  if (compatibility === undefined) return schema
+  switch (compatibility) {
+    case "gemini":
+      return gemini(schema)
+    case "moonshot":
+      return moonshot(schema)
+  }
+}
+
+export const ToolSchemaProjection = {
+  gemini,
+  modelCompatibility,
+  moonshot,
+  openAI,
+} as const

packages/ai/src/protocols/utils/tool-stream.ts

@@ -1,5 +1,5 @@
 import { Effect } from "effect"
-import { LLMError, LLMEvent, type ProviderMetadata, type ToolCall } from "../../schema"
+import { LLMError, LLMEvent, type ProviderMetadata, type ToolCall, type ToolInputError } from "../../schema"
 import { eventError, parseToolInput, type ToolAccumulator } from "../shared"
 
 type StreamKey = string | number
@@ -53,6 +53,7 @@ const inputStart = (tool: PendingTool) =>
   LLMEvent.toolInputStart({
     id: tool.id,
     name: tool.name,
+    providerExecuted: tool.providerExecuted ? true : undefined,
     providerMetadata: tool.providerMetadata,
   })
 
@@ -63,19 +64,36 @@ const inputDelta = (tool: PendingTool, text: string) =>
     text,
   })
 
-const toolCall = (route: string, tool: PendingTool, inputOverride?: string) =>
-  parseToolInput(route, tool.name, inputOverride ?? tool.input).pipe(
-    Effect.map(
-      (input): ToolCall =>
-        LLMEvent.toolCall({
-          id: tool.id,
-          name: tool.name,
-          input,
-          providerExecuted: tool.providerExecuted ? true : undefined,
-          providerMetadata: tool.providerMetadata,
-        }),
+const toolCall = (route: string, tool: PendingTool, inputOverride?: string) => {
+  const raw = inputOverride ?? tool.input
+  return parseToolInput(route, tool.name, raw).pipe(
+    Effect.map((input): ToolCall | ToolInputError =>
+      LLMEvent.toolCall({
+        id: tool.id,
+        name: tool.name,
+        input,
+        providerExecuted: tool.providerExecuted ? true : undefined,
+        providerMetadata: tool.providerMetadata,
+      }),
+    ),
+    Effect.catch((error) =>
+      tool.providerExecuted
+        ? Effect.fail(error)
+        : Effect.succeed(
+            LLMEvent.toolInputError({
+              id: tool.id,
+              name: tool.name,
+              raw,
+            }),
+          ),
     ),
   )
+}
+
+const finishEvents = (tool: PendingTool, event: ToolCall | ToolInputError): ReadonlyArray<LLMEvent> =>
+  event.type === "tool-input-error"
+    ? [event]
+    : [LLMEvent.toolInputEnd({ id: tool.id, name: tool.name, providerMetadata: tool.providerMetadata }), event]
 
 /** Store the updated tool and produce the optional public delta event. */
 const appendTool = <K extends StreamKey>(
@@ -122,8 +140,8 @@ export const appendOrStart = <K extends StreamKey>(
   missingToolMessage: string,
 ): AppendOutcome<K> | LLMError => {
   const current = tools[key]
-  const id = delta.id ?? current?.id
-  const name = delta.name ?? current?.name
+  const id = current?.id ?? delta.id
+  const name = current?.name ?? delta.name
   if (!id || !name) return eventError(route, missingToolMessage)
 
   const tool = {
@@ -158,8 +176,9 @@ export const appendExisting = <K extends StreamKey>(
 
 /**
  * Finalize one pending tool call: parse the accumulated raw JSON, remove it
- * from state, and return the optional public `tool-call` event. Missing keys are
- * a no-op because some providers emit stop events for non-tool content blocks.
+ * from state, and return either a call or a non-executable local input error.
+ * Missing keys are a no-op because some providers emit stop events for
+ * non-tool content blocks.
  */
 export const finish = <K extends StreamKey>(route: string, tools: State<K>, key: K) =>
   Effect.gen(function* () {
@@ -167,10 +186,7 @@ export const finish = <K extends StreamKey>(route: string, tools: State<K>, key:
     if (!tool) return { tools }
     return {
       tools: withoutTool(tools, key),
-      events: [
-        LLMEvent.toolInputEnd({ id: tool.id, name: tool.name, providerMetadata: tool.providerMetadata }),
-        yield* toolCall(route, tool),
-      ],
+      events: finishEvents(tool, yield* toolCall(route, tool)),
     }
   })
 
@@ -185,17 +201,14 @@ export const finishWithInput = <K extends StreamKey>(route: string, tools: State
     if (!tool) return { tools }
     return {
       tools: withoutTool(tools, key),
-      events: [
-        LLMEvent.toolInputEnd({ id: tool.id, name: tool.name, providerMetadata: tool.providerMetadata }),
-        yield* toolCall(route, tool, input),
-      ],
+      events: finishEvents(tool, yield* toolCall(route, tool, input)),
     }
   })
 
 /**
  * Finalize every pending tool call at once. OpenAI Chat has this shape: it does
- * not emit per-tool stop events, so all accumulated calls finish when the choice
- * receives a terminal `finish_reason`.
+ * not emit per-tool stop events, so all accumulated calls finish independently
+ * when the choice receives a terminal `finish_reason`.
  */
 export const finishAll = <K extends StreamKey>(route: string, tools: State<K>) =>
   Effect.gen(function* () {
@@ -205,12 +218,7 @@ export const finishAll = <K extends StreamKey>(route: string, tools: State<K>) =
     return {
       tools: empty<K>(),
       events: yield* Effect.forEach(pending, (tool) =>
-        toolCall(route, tool).pipe(
-          Effect.map((call) => [
-            LLMEvent.toolInputEnd({ id: tool.id, name: tool.name, providerMetadata: tool.providerMetadata }),
-            call,
-          ]),
-        ),
+        toolCall(route, tool).pipe(Effect.map((event) => finishEvents(tool, event))),
       ).pipe(Effect.map((events) => events.flat())),
     }
   })