Merge remote-tracking branch 'origin/main' into codex/im-channel-connections

# Conflicts:
#	backend/app/channels/discord.py
#	backend/app/channels/manager.py
#	backend/app/channels/slack.py
#	backend/app/channels/telegram.py

backend/.gitignore

@@ -24,5 +24,10 @@ config.yaml
 # Langgraph
 .langgraph_api
 
+# Sandbox runtime working dir — pre-created and excluded from uvicorn reload
+# (scripts/serve.sh, docker/dev-entrypoint.sh). Anchored so it does not match
+# the source package backend/packages/harness/deerflow/sandbox/.
+/sandbox/
+
 # Claude Code settings
 .claude/settings.local.json

backend/CLAUDE.md

@@ -202,16 +202,17 @@ Lead-agent middlewares are assembled in strict append order across `packages/har
 6. **GuardrailMiddleware** - Pre-tool-call authorization via pluggable `GuardrailProvider` protocol (optional, if `guardrails.enabled` in config). Evaluates each tool call and returns error ToolMessage on deny. Three provider options: built-in `AllowlistProvider` (zero deps), OAP policy providers (e.g. `aport-agent-guardrails`), or custom providers. See [docs/GUARDRAILS.md](docs/GUARDRAILS.md) for setup, usage, and how to implement a provider.
 7. **SandboxAuditMiddleware** - Audits sandboxed shell/file operations for security logging before tool execution continues
 8. **ToolErrorHandlingMiddleware** - Converts tool exceptions into error `ToolMessage`s so the run can continue instead of aborting
-9. **SummarizationMiddleware** - Context reduction when approaching token limits (optional, if enabled)
-10. **TodoListMiddleware** - Task tracking with `write_todos` tool (optional, if plan_mode)
-11. **TokenUsageMiddleware** - Records token usage metrics when token tracking is enabled (optional); subagent usage is cached by `tool_call_id` only while token usage is enabled and merged back into the dispatching AIMessage by message position rather than message id
-12. **TitleMiddleware** - Auto-generates thread title after first complete exchange and normalizes structured message content before prompting the title model
-13. **MemoryMiddleware** - Queues conversations for async memory update (filters to user + final AI responses)
-14. **ViewImageMiddleware** - Injects base64 image data before LLM call (conditional on vision support)
-15. **DeferredToolFilterMiddleware** - Hides deferred (MCP) tool schemas from the bound model using a build-time deferred-name set + catalog hash, reading per-thread promotions from `ThreadState.promoted` (hash-scoped, no ContextVar); a tool becomes bound on subsequent turns after `tool_search` returns its schema (optional, if `tool_search.enabled`)
-16. **SubagentLimitMiddleware** - Truncates excess `task` tool calls from model response to enforce `MAX_CONCURRENT_SUBAGENTS` limit (optional, if `subagent_enabled`)
-17. **LoopDetectionMiddleware** - Detects repeated tool-call loops; hard-stop responses clear both structured `tool_calls` and raw provider tool-call metadata before forcing a final text answer
-18. **ClarificationMiddleware** - Intercepts `ask_clarification` tool calls, interrupts via `Command(goto=END)` (must be last)
+9. **SkillActivationMiddleware** - Detects strict `/skill-name task` syntax on the latest real user message, resolves only enabled and runtime-allowed skills, reads `SKILL.md` from trusted skill storage, injects the skill body as hidden current-turn model context, and records a `middleware:skill_activation` audit event with skill name, category, path, and content hash
+10. **SummarizationMiddleware** - Context reduction when approaching token limits (optional, if enabled)
+11. **TodoListMiddleware** - Task tracking with `write_todos` tool (optional, if plan_mode)
+12. **TokenUsageMiddleware** - Records token usage metrics when token tracking is enabled (optional); subagent usage is cached by `tool_call_id` only while token usage is enabled and merged back into the dispatching AIMessage by message position rather than message id
+13. **TitleMiddleware** - Auto-generates thread title after first complete exchange and normalizes structured message content before prompting the title model
+14. **MemoryMiddleware** - Queues conversations for async memory update (filters to user + final AI responses)
+15. **ViewImageMiddleware** - Injects base64 image data before LLM call (conditional on vision support)
+16. **DeferredToolFilterMiddleware** - Hides deferred (MCP) tool schemas from the bound model using a build-time deferred-name set + catalog hash, reading per-thread promotions from `ThreadState.promoted` (hash-scoped, no ContextVar); a tool becomes bound on subsequent turns after `tool_search` returns its schema (optional, if `tool_search.enabled`)
+17. **SubagentLimitMiddleware** - Truncates excess `task` tool calls from model response to enforce `MAX_CONCURRENT_SUBAGENTS` limit (optional, if `subagent_enabled`)
+18. **LoopDetectionMiddleware** - Detects repeated tool-call loops; hard-stop responses clear both structured `tool_calls` and raw provider tool-call metadata before forcing a final text answer
+19. **ClarificationMiddleware** - Intercepts `ask_clarification` tool calls, interrupts via `Command(goto=END)` (must be last)
 
 ### Configuration System
 
@@ -348,6 +349,7 @@ Proxied through nginx: `/api/langgraph/*` → Gateway LangGraph-compatible runti
 - **Format**: Directory with `SKILL.md` (YAML frontmatter: name, description, license, allowed-tools)
 - **Loading**: `load_skills()` recursively scans `skills/{public,custom}` for `SKILL.md`, parses metadata, and reads enabled state from extensions_config.json
 - **Injection**: Enabled skills listed in agent system prompt with container paths
+- **Slash activation**: `/skill-name task` loads that enabled skill's `SKILL.md` for the current model call only. The resolver rejects leading whitespace, missing separators, reserved channel commands (`/new`, `/help`, `/bootstrap`, `/status`, `/models`, `/memory`), disabled skills, and skills outside a custom agent's whitelist.
 - **Installation**: `POST /api/skills/install` extracts .skill ZIP archive to custom/ directory
 
 ### Model Factory (`packages/harness/deerflow/models/factory.py`)

backend/app/channels/commands.py

@@ -18,3 +18,10 @@ KNOWN_CHANNEL_COMMANDS: frozenset[str] = frozenset(
         "/help",
     }
 )
+
+
+def is_known_channel_command(text: str) -> bool:
+    """Return whether text starts with a registered channel control command."""
+    if not text.startswith("/"):
+        return False
+    return text.split(maxsplit=1)[0].lower() in KNOWN_CHANNEL_COMMANDS

backend/app/channels/dingtalk.py

@@ -14,7 +14,7 @@ from typing import Any
 import httpx
 
 from app.channels.base import Channel
-from app.channels.commands import KNOWN_CHANNEL_COMMANDS
+from app.channels.commands import is_known_channel_command
 from app.channels.message_bus import InboundMessage, InboundMessageType, MessageBus, OutboundMessage, ResolvedAttachment
 
 logger = logging.getLogger(__name__)
@@ -59,9 +59,7 @@ def _normalize_allowed_users(allowed_users: Any) -> set[str]:
 
 
 def _is_dingtalk_command(text: str) -> bool:
-    if not text.startswith("/"):
-        return False
-    return text.split(maxsplit=1)[0].lower() in KNOWN_CHANNEL_COMMANDS
+    return is_known_channel_command(text)
 
 
 def _extract_text_from_rich_text(rich_text_list: list) -> str:

backend/app/channels/discord.py

@@ -10,6 +10,7 @@ from pathlib import Path
 from typing import Any
 
 from app.channels.base import Channel
+from app.channels.commands import is_known_channel_command
 from app.channels.message_bus import InboundMessage, InboundMessageType, MessageBus, OutboundMessage, ResolvedAttachment
 
 logger = logging.getLogger(__name__)
@@ -301,7 +302,7 @@ class DiscordChannel(Channel):
 
             # If this is a known active thread, process normally
             if thread_id in self._active_thread_ids:
-                msg_type = InboundMessageType.COMMAND if text.startswith("/") else InboundMessageType.CHAT
+                msg_type = InboundMessageType.COMMAND if is_known_channel_command(text) else InboundMessageType.CHAT
                 inbound = self._make_inbound(
                     chat_id=chat_id,
                     user_id=str(message.author.id),
@@ -409,7 +410,7 @@ class DiscordChannel(Channel):
             chat_id = channel_id
             typing_target = message.channel  # Type into the channel
 
-        msg_type = InboundMessageType.COMMAND if text.startswith("/") else InboundMessageType.CHAT
+        msg_type = InboundMessageType.COMMAND if is_known_channel_command(text) else InboundMessageType.CHAT
         inbound = self._make_inbound(
             chat_id=chat_id,
             user_id=str(message.author.id),

backend/app/channels/feishu.py

@@ -11,7 +11,7 @@ import time
 from typing import Any, Literal
 
 from app.channels.base import Channel
-from app.channels.commands import KNOWN_CHANNEL_COMMANDS
+from app.channels.commands import is_known_channel_command
 from app.channels.message_bus import (
     PENDING_CLARIFICATION_METADATA_KEY,
     RESOLVED_FROM_PENDING_CLARIFICATION_METADATA_KEY,
@@ -30,9 +30,7 @@ PENDING_CLARIFICATION_TTL_SECONDS = 30 * 60
 
 
 def _is_feishu_command(text: str) -> bool:
-    if not text.startswith("/"):
-        return False
-    return text.split(maxsplit=1)[0].lower() in KNOWN_CHANNEL_COMMANDS
+    return is_known_channel_command(text)
 
 
 class FeishuChannel(Channel):

backend/app/channels/manager.py

@@ -8,6 +8,7 @@ import mimetypes
 import re
 import time
 from collections.abc import Awaitable, Callable, Mapping
+from dataclasses import dataclass
 from pathlib import Path
 from typing import Any
 
@@ -26,8 +27,13 @@ from app.channels.message_bus import (
 from app.channels.store import ChannelStore
 from app.gateway.csrf_middleware import CSRF_COOKIE_NAME, CSRF_HEADER_NAME, generate_csrf_token
 from app.gateway.internal_auth import create_internal_auth_headers
+from deerflow.config.agents_config import load_agent_config
 from deerflow.config.paths import make_safe_user_id
 from deerflow.runtime.user_context import get_effective_user_id
+from deerflow.skills.slash import parse_slash_skill_reference
+from deerflow.skills.storage import get_or_new_skill_storage
+from deerflow.skills.storage.skill_storage import SkillStorage
+from deerflow.utils.messages import ORIGINAL_USER_CONTENT_KEY
 
 logger = logging.getLogger(__name__)
 
@@ -124,6 +130,16 @@ class InvalidChannelSessionConfigError(ValueError):
     """Raised when IM channel session overrides contain invalid agent config."""
 
 
+class SlashSkillCommandResolutionError(RuntimeError):
+    """Raised when IM slash-skill command resolution cannot complete safely."""
+
+
+@dataclass(frozen=True, slots=True)
+class _SlashSkillCommandResolution:
+    route_to_chat: bool = False
+    failure_message: str | None = None
+
+
 def _is_thread_busy_error(exc: BaseException | None) -> bool:
     if exc is None:
         return False
@@ -410,6 +426,46 @@ def _format_artifact_text(artifacts: list[str]) -> str:
 _OUTPUTS_VIRTUAL_PREFIX = "/mnt/user-data/outputs/"
 
 
+def _unknown_command_reply(command: str | None = None) -> str:
+    available = " | ".join(sorted(KNOWN_CHANNEL_COMMANDS))
+    if command:
+        return f"Unknown command: /{command}. Available commands: {available}"
+    return f"Unknown command. Available commands: {available}"
+
+
+def _human_input_message(content: str, *, original_content: str | None = None) -> dict[str, Any]:
+    message: dict[str, Any] = {"role": "human", "content": content}
+    if original_content is not None and original_content != content:
+        message["additional_kwargs"] = {ORIGINAL_USER_CONTENT_KEY: original_content}
+    return message
+
+
+def _resolve_slash_skill_command(
+    text: str,
+    available_skills: set[str] | None = None,
+    storage: SkillStorage | Callable[[], SkillStorage] | None = None,
+) -> _SlashSkillCommandResolution | None:
+    reference = parse_slash_skill_reference(text)
+    if reference is None:
+        return None
+    try:
+        resolved_storage = storage() if callable(storage) else storage or get_or_new_skill_storage()
+        skills = resolved_storage.load_skills(enabled_only=False)
+
+        skill = next((candidate for candidate in skills if candidate.name == reference.name), None)
+        if skill is None:
+            return None
+        if not skill.enabled:
+            return _SlashSkillCommandResolution(failure_message=f"Skill `/{reference.name}` is installed but disabled. Enable it before using slash activation.")
+        if available_skills is not None and reference.name not in available_skills:
+            return _SlashSkillCommandResolution(failure_message=f"Skill `/{reference.name}` is not available for this agent.")
+
+        return _SlashSkillCommandResolution(route_to_chat=True)
+    except Exception as exc:
+        logger.exception("[Manager] failed to resolve slash skill command")
+        raise SlashSkillCommandResolutionError("Failed to resolve slash skill command. Please check the skill configuration.") from exc
+
+
 def _resolve_attachments(thread_id: str, artifacts: list[str]) -> list[ResolvedAttachment]:
     """Resolve virtual artifact paths to host filesystem paths with metadata.
 
@@ -626,6 +682,7 @@ class ChannelManager:
         self._channel_sessions = dict(channel_sessions or {})
         self._connection_repo = connection_repo
         self._client = None  # lazy init — langgraph_sdk async client
+        self._skill_storage: SkillStorage | None = None
         self._csrf_token = generate_csrf_token()
         self._semaphore: asyncio.Semaphore | None = None
         self._running = False
@@ -702,6 +759,21 @@ class ChannelManager:
 
         return assistant_id, run_config, run_context
 
+    def _resolve_available_skill_names(self, msg: InboundMessage) -> set[str] | None:
+        thread_id = self.store.get_thread_id(msg.channel_name, msg.chat_id, topic_id=msg.topic_id) or ""
+        _, _, run_context = self._resolve_run_params(msg, thread_id)
+        if run_context.get("is_bootstrap"):
+            return {"bootstrap"}
+
+        agent_name = run_context.get("agent_name")
+        if not isinstance(agent_name, str) or not agent_name.strip():
+            return None
+
+        agent_config = load_agent_config(_normalize_custom_agent_name(agent_name))
+        if agent_config and agent_config.skills is not None:
+            return set(agent_config.skills)
+        return None
+
     # -- LangGraph SDK client (lazy) ----------------------------------------
 
     def _get_client(self):
@@ -719,6 +791,11 @@ class ChannelManager:
             )
         return self._client
 
+    def _get_skill_storage(self) -> SkillStorage:
+        if self._skill_storage is None:
+            self._skill_storage = get_or_new_skill_storage()
+        return self._skill_storage
+
     # -- lifecycle ---------------------------------------------------------
 
     async def start(self) -> None:
@@ -788,6 +865,14 @@ class ChannelManager:
                     exc,
                 )
                 await self._send_error(msg, str(exc))
+            except SlashSkillCommandResolutionError as exc:
+                logger.warning(
+                    "Slash skill command resolution failed for %s (chat=%s): %s",
+                    msg.channel_name,
+                    msg.chat_id,
+                    exc,
+                )
+                await self._send_error(msg, str(exc))
             except Exception:
                 logger.exception(
                     "Error handling message from %s (chat=%s)",
@@ -865,9 +950,11 @@ class ChannelManager:
         if extra_context:
             run_context.update(extra_context)
 
+        original_text = msg.text
         uploaded = await _ingest_inbound_files(thread_id, msg)
         if uploaded:
             msg.text = f"{_format_uploaded_files_block(uploaded)}\n\n{msg.text}".strip()
+        human_message = _human_input_message(msg.text, original_content=original_text)
 
         if self._channel_supports_streaming(msg.channel_name):
             await self._handle_streaming_chat(
@@ -877,6 +964,7 @@ class ChannelManager:
                 assistant_id,
                 run_config,
                 run_context,
+                human_message,
             )
             return
 
@@ -885,7 +973,7 @@ class ChannelManager:
             result = await client.runs.wait(
                 thread_id,
                 assistant_id,
-                input={"messages": [{"role": "human", "content": msg.text}]},
+                input={"messages": [human_message]},
                 config=run_config,
                 context=run_context,
                 multitask_strategy="reject",
@@ -940,6 +1028,7 @@ class ChannelManager:
         assistant_id: str,
         run_config: dict[str, Any],
         run_context: dict[str, Any],
+        human_message: dict[str, Any],
     ) -> None:
         logger.info("[Manager] invoking runs.stream(thread_id=%s, text=%r)", thread_id, msg.text[:100])
 
@@ -955,7 +1044,7 @@ class ChannelManager:
             async for chunk in client.runs.stream(
                 thread_id,
                 assistant_id,
-                input={"messages": [{"role": "human", "content": msg.text}]},
+                input={"messages": [human_message]},
                 config=run_config,
                 context=run_context,
                 stream_mode=["messages-tuple", "values"],
@@ -1046,11 +1135,20 @@ class ChannelManager:
     # -- command handling --------------------------------------------------
 
     async def _handle_command(self, msg: InboundMessage) -> None:
-        text = msg.text.strip()
+        raw_text = msg.text
+        text = raw_text.strip()
         parts = text.split(maxsplit=1)
-        command = parts[0].lower().lstrip("/")
+        reply: str | None = None
+        if not parts:
+            command = None
+            reply = _unknown_command_reply()
+        else:
+            command = parts[0].lower().removeprefix("/")
 
-        if command == "bootstrap":
+        if reply is None and not raw_text.startswith("/"):
+            reply = _unknown_command_reply(command)
+
+        if reply is None and command == "bootstrap":
             from dataclasses import replace as _dc_replace
 
             chat_text = parts[1] if len(parts) > 1 else "Initialize workspace"
@@ -1058,21 +1156,21 @@ class ChannelManager:
             await self._handle_chat(chat_msg, extra_context={"is_bootstrap": True})
             return
 
-        if command == "new":
+        if reply is None and command == "new":
             # Create a new thread through Gateway
             client = self._get_client()
             thread = await client.threads.create()
             new_thread_id = thread["thread_id"]
             await self._store_thread_id(msg, new_thread_id)
             reply = "New conversation started."
-        elif command == "status":
+        elif reply is None and command == "status":
             thread_id = await self._lookup_thread_id(msg)
             reply = f"Active thread: {thread_id}" if thread_id else "No active conversation."
-        elif command == "models":
+        elif reply is None and command == "models":
             reply = await self._fetch_gateway("/api/models", "models")
-        elif command == "memory":
+        elif reply is None and command == "memory":
             reply = await self._fetch_gateway("/api/memory", "memory")
-        elif command == "help":
+        elif reply is None and command == "help":
             reply = (
                 "Available commands:\n"
                 "/bootstrap — Start a bootstrap session (enables agent setup)\n"
@@ -1080,11 +1178,27 @@ class ChannelManager:
                 "/status — Show current thread info\n"
                 "/models — List available models\n"
                 "/memory — Show memory status\n"
+                "/<skill-name> <task> — Activate an enabled skill for one turn\n"
                 "/help — Show this help"
             )
-        else:
-            available = " | ".join(sorted(KNOWN_CHANNEL_COMMANDS))
-            reply = f"Unknown command: /{command}. Available commands: {available}"
+        elif reply is None:
+            slash_resolution = await asyncio.to_thread(
+                lambda: _resolve_slash_skill_command(
+                    raw_text,
+                    self._resolve_available_skill_names(msg),
+                    self._get_skill_storage,
+                )
+            )
+            if slash_resolution and slash_resolution.failure_message:
+                reply = slash_resolution.failure_message
+            elif slash_resolution and slash_resolution.route_to_chat:
+                from dataclasses import replace as _dc_replace
+
+                chat_msg = _dc_replace(msg, msg_type=InboundMessageType.CHAT)
+                await self._handle_chat(chat_msg)
+                return
+            else:
+                reply = _unknown_command_reply(command)
 
         outbound = OutboundMessage(
             channel_name=msg.channel_name,

backend/app/channels/slack.py

@@ -9,6 +9,7 @@ from typing import Any
 from markdown_to_mrkdwn import SlackMarkdownConverter
 
 from app.channels.base import Channel
+from app.channels.commands import is_known_channel_command
 from app.channels.message_bus import InboundMessageType, MessageBus, OutboundMessage, ResolvedAttachment
 
 logger = logging.getLogger(__name__)
@@ -32,6 +33,20 @@ def _normalize_allowed_users(allowed_users: Any) -> set[str]:
     return {str(user_id) for user_id in values if str(user_id)}
 
 
+def _strip_leading_slack_bot_mention(text: str, bot_user_id: str | None) -> str:
+    if not bot_user_id:
+        return text
+    if not text.startswith("<@"):
+        return text
+    end = text.find(">")
+    if end <= 2:
+        return text
+    mentioned_user_id = text[2:end].split("|", 1)[0].lstrip("!")
+    if mentioned_user_id != bot_user_id:
+        return text
+    return text[end + 1 :].lstrip()
+
+
 class SlackChannel(Channel):
     """Slack IM channel using Socket Mode (WebSocket, no public IP).
 
@@ -51,6 +66,8 @@ class SlackChannel(Channel):
         self._allowed_users = _normalize_allowed_users(config.get("allowed_users", []))
         self._connection_repo = config.get("connection_repo")
         self._web_client_factory = config.get("web_client_factory")
+        configured_bot_user_id = config.get("bot_user_id")
+        self._bot_user_id = str(configured_bot_user_id).lstrip("@") if configured_bot_user_id else None
 
     async def start(self) -> None:
         if self._running:
@@ -83,6 +100,17 @@ class SlackChannel(Channel):
             return
 
         self._web_client = self._web_client_factory(token=bot_token)
+        if self._bot_user_id is None:
+            try:
+                auth_info = await asyncio.to_thread(self._web_client.auth_test)
+                user_id = auth_info.get("user_id") if isinstance(auth_info, dict) else None
+                if user_id is None:
+                    auth_get = getattr(auth_info, "get", None)
+                    user_id = auth_get("user_id") if callable(auth_get) else None
+                if isinstance(user_id, str) and user_id:
+                    self._bot_user_id = user_id
+            except Exception:
+                logger.warning("[Slack] failed to resolve bot user id; app mention text may include the bot mention", exc_info=True)
         self._socket_client = SocketModeClient(
             app_token=app_token,
             web_client=self._web_client,
@@ -243,6 +271,12 @@ class SlackChannel(Channel):
             if event_type != "events_api":
                 return
 
+            if self._bot_user_id is None:
+                authorization = next((item for item in req.payload.get("authorizations", []) if isinstance(item, dict)), None)
+                user_id = authorization.get("user_id") if authorization else None
+                if isinstance(user_id, str) and user_id:
+                    self._bot_user_id = user_id
+
             event = req.payload.get("event", {})
             etype = event.get("type", "")
 
@@ -266,13 +300,15 @@ class SlackChannel(Channel):
             return
 
         text = event.get("text", "").strip()
+        if event.get("type") == "app_mention":
+            text = _strip_leading_slack_bot_mention(text, self._bot_user_id)
         if not text:
             return
 
         channel_id = event.get("channel", "")
         thread_ts = event.get("thread_ts") or event.get("ts", "")
 
-        if text.startswith("/"):
+        if is_known_channel_command(text):
             msg_type = InboundMessageType.COMMAND
         else:
             msg_type = InboundMessageType.CHAT

backend/app/channels/telegram.py

@@ -61,12 +61,17 @@ class TelegramChannel(Channel):
 
         # Command handlers
         app.add_handler(CommandHandler("start", self._cmd_start))
+        app.add_handler(CommandHandler("bootstrap", self._cmd_generic))
         app.add_handler(CommandHandler("new", self._cmd_generic))
         app.add_handler(CommandHandler("status", self._cmd_generic))
         app.add_handler(CommandHandler("models", self._cmd_generic))
         app.add_handler(CommandHandler("memory", self._cmd_generic))
         app.add_handler(CommandHandler("help", self._cmd_generic))
 
+        # Slash skill commands are dynamic and cannot all be pre-registered
+        # with Telegram, so route unknown slash commands through chat handling.
+        app.add_handler(MessageHandler(filters.TEXT & filters.COMMAND, self._on_text))
+
         # General message handler
         app.add_handler(MessageHandler(filters.TEXT & ~filters.COMMAND, self._on_text))
 
@@ -306,6 +311,33 @@ class TelegramChannel(Channel):
         inbound.workspace_id = connection.get("workspace_id")
         return inbound
 
+    def _get_bot_username(self, context) -> str | None:
+        bot = getattr(context, "bot", None)
+        username = getattr(bot, "username", None)
+        if not username and self._application is not None:
+            username = getattr(getattr(self._application, "bot", None), "username", None)
+        return str(username) if username else None
+
+    @staticmethod
+    def _strip_bot_username_from_leading_command(text: str, bot_username: str | None) -> str:
+        username = (bot_username or "").lstrip("@").lower()
+        if not username or not text.startswith("/"):
+            return text
+
+        parts = text.split(maxsplit=1)
+        command_token = parts[0]
+        if "@" not in command_token:
+            return text
+
+        command_name, addressed_username = command_token[1:].rsplit("@", 1)
+        if not command_name or addressed_username.lower() != username:
+            return text
+
+        normalized = f"/{command_name}"
+        if len(parts) > 1:
+            normalized = f"{normalized} {parts[1]}"
+        return normalized
+
     async def _cmd_start(self, update, context) -> None:
         """Handle /start command."""
         if not self._check_user(update.effective_user.id):
@@ -326,7 +358,7 @@ class TelegramChannel(Channel):
         if not self._check_user(update.effective_user.id):
             return
 
-        text = update.message.text
+        text = self._strip_bot_username_from_leading_command(update.message.text.strip(), self._get_bot_username(context))
         chat_id = str(update.effective_chat.id)
         user_id = str(update.effective_user.id)
         msg_id = str(update.message.message_id)
@@ -363,7 +395,7 @@ class TelegramChannel(Channel):
         if not self._check_user(update.effective_user.id):
             return
 
-        text = update.message.text.strip()
+        text = self._strip_bot_username_from_leading_command(update.message.text.strip(), self._get_bot_username(context))
         if not text:
             return
 

backend/app/channels/wechat.py

@@ -22,6 +22,7 @@ from cryptography.hazmat.primitives import padding
 from cryptography.hazmat.primitives.ciphers import Cipher, algorithms, modes
 
 from app.channels.base import Channel
+from app.channels.commands import is_known_channel_command
 from app.channels.message_bus import InboundMessageType, MessageBus, OutboundMessage, ResolvedAttachment
 
 logger = logging.getLogger(__name__)
@@ -620,7 +621,7 @@ class WechatChannel(Channel):
             chat_id=chat_id,
             user_id=chat_id,
             text=text,
-            msg_type=InboundMessageType.COMMAND if text.startswith("/") else InboundMessageType.CHAT,
+            msg_type=InboundMessageType.COMMAND if is_known_channel_command(text) else InboundMessageType.CHAT,
             thread_ts=thread_ts,
             files=files,
             metadata={

backend/app/channels/wecom.py

@@ -8,6 +8,7 @@ from collections.abc import Awaitable, Callable
 from typing import Any, cast
 
 from app.channels.base import Channel
+from app.channels.commands import is_known_channel_command
 from app.channels.message_bus import (
     InboundMessageType,
     MessageBus,
@@ -270,7 +271,7 @@ class WeComChannel(Channel):
 
         user_id = (body.get("from") or {}).get("userid")
 
-        inbound_type = InboundMessageType.COMMAND if text.startswith("/") else InboundMessageType.CHAT
+        inbound_type = InboundMessageType.COMMAND if is_known_channel_command(text) else InboundMessageType.CHAT
         inbound = self._make_inbound(
             chat_id=user_id,  # keep user's conversation in memory
             user_id=user_id,

backend/app/gateway/app.py

@@ -6,6 +6,7 @@ from contextlib import asynccontextmanager
 from fastapi import FastAPI
 from fastapi.middleware.cors import CORSMiddleware
 
+from app.gateway.auth_disabled import warn_if_auth_disabled_enabled
 from app.gateway.auth_middleware import AuthMiddleware
 from app.gateway.config import get_gateway_config
 from app.gateway.csrf_middleware import CSRFMiddleware, get_configured_cors_origins
@@ -173,6 +174,7 @@ async def lifespan(app: FastAPI) -> AsyncGenerator[None, None]:
         startup_config = get_app_config()
         apply_logging_level(startup_config.log_level)
         logger.info("Configuration loaded successfully")
+        warn_if_auth_disabled_enabled()
     except Exception as e:
         error_msg = f"Failed to load configuration during gateway startup: {e}"
         logger.exception(error_msg)

backend/app/gateway/auth_disabled.py

@@ -0,0 +1,54 @@
+"""Shared helpers for local/E2E auth-disabled mode."""
+
+from __future__ import annotations
+
+import logging
+import os
+from types import SimpleNamespace
+
+AUTH_DISABLED_ENV_VAR = "DEER_FLOW_AUTH_DISABLED"
+AUTH_DISABLED_USER_ID = "e2e-user"
+AUTH_DISABLED_USER_EMAIL = "e2e@test.local"
+
+AUTH_SOURCE_SESSION = "session"
+AUTH_SOURCE_INTERNAL = "internal"
+AUTH_SOURCE_AUTH_DISABLED = "auth_disabled"
+
+_PRODUCTION_ENV_VARS: tuple[str, ...] = ("DEER_FLOW_ENV", "ENVIRONMENT")
+_PRODUCTION_ENV_VALUES: frozenset[str] = frozenset({"prod", "production"})
+
+logger = logging.getLogger(__name__)
+
+
+def is_explicit_production_environment() -> bool:
+    return any(os.environ.get(name, "").strip().lower() in _PRODUCTION_ENV_VALUES for name in _PRODUCTION_ENV_VARS)
+
+
+def is_auth_disabled_requested() -> bool:
+    return os.environ.get(AUTH_DISABLED_ENV_VAR) == "1"
+
+
+def is_auth_disabled() -> bool:
+    return is_auth_disabled_requested() and not is_explicit_production_environment()
+
+
+def warn_if_auth_disabled_enabled() -> None:
+    if not is_auth_disabled():
+        return
+
+    logger.warning(
+        "%s=1 is active: authentication is bypassed and anonymous requests run as synthetic admin user %r. Do not enable this in shared or production deployments.",
+        AUTH_DISABLED_ENV_VAR,
+        AUTH_DISABLED_USER_ID,
+    )
+
+
+def get_auth_disabled_user():
+    return SimpleNamespace(
+        id=AUTH_DISABLED_USER_ID,
+        email=AUTH_DISABLED_USER_EMAIL,
+        password_hash=None,
+        system_role="admin",
+        needs_setup=False,
+        token_version=0,
+    )

backend/app/gateway/auth_middleware.py

@@ -17,6 +17,13 @@ from starlette.responses import JSONResponse
 from starlette.types import ASGIApp
 
 from app.gateway.auth.errors import AuthErrorCode, AuthErrorResponse
+from app.gateway.auth_disabled import (
+    AUTH_SOURCE_AUTH_DISABLED,
+    AUTH_SOURCE_INTERNAL,
+    AUTH_SOURCE_SESSION,
+    get_auth_disabled_user,
+    is_auth_disabled,
+)
 from app.gateway.authz import _ALL_PERMISSIONS, AuthContext
 from app.gateway.internal_auth import INTERNAL_AUTH_HEADER_NAME, get_internal_user, is_valid_internal_auth_token
 from deerflow.runtime.user_context import reset_current_user, set_current_user
@@ -83,8 +90,38 @@ class AuthMiddleware(BaseHTTPMiddleware):
         if is_valid_internal_auth_token(request.headers.get(INTERNAL_AUTH_HEADER_NAME)):
             internal_user = get_internal_user()
 
+        auth_source = AUTH_SOURCE_SESSION
+        access_token = request.cookies.get("access_token")
+
         # Non-public path: require session cookie
-        if internal_user is None and not request.cookies.get("access_token"):
+        if internal_user is not None:
+            user = internal_user
+            auth_source = AUTH_SOURCE_INTERNAL
+        elif access_token:
+            # Strict JWT validation: reject junk/expired tokens with 401
+            # right here instead of silently passing through. This closes
+            # the "junk cookie bypass" gap (AUTH_TEST_PLAN test 7.5.8):
+            # without this, non-isolation routes like /api/models would
+            # accept any cookie-shaped string as authentication.
+            #
+            # We call the *strict* resolver so that fine-grained error
+            # codes (token_expired, token_invalid, user_not_found, …)
+            # propagate from AuthErrorCode, not get flattened into one
+            # generic code. BaseHTTPMiddleware doesn't let HTTPException
+            # bubble up, so we catch and render it as JSONResponse here.
+            from app.gateway.deps import get_current_user_from_request
+
+            try:
+                user = await get_current_user_from_request(request)
+            except HTTPException as exc:
+                if not is_auth_disabled():
+                    return JSONResponse(status_code=exc.status_code, content={"detail": exc.detail})
+                user = get_auth_disabled_user()
+                auth_source = AUTH_SOURCE_AUTH_DISABLED
+        elif is_auth_disabled():
+            user = get_auth_disabled_user()
+            auth_source = AUTH_SOURCE_AUTH_DISABLED
+        else:
             return JSONResponse(
                 status_code=401,
                 content={
@@ -95,32 +132,12 @@ class AuthMiddleware(BaseHTTPMiddleware):
                 },
             )
 
-        # Strict JWT validation: reject junk/expired tokens with 401
-        # right here instead of silently passing through. This closes
-        # the "junk cookie bypass" gap (AUTH_TEST_PLAN test 7.5.8):
-        # without this, non-isolation routes like /api/models would
-        # accept any cookie-shaped string as authentication.
-        #
-        # We call the *strict* resolver so that fine-grained error
-        # codes (token_expired, token_invalid, user_not_found, …)
-        # propagate from AuthErrorCode, not get flattened into one
-        # generic code. BaseHTTPMiddleware doesn't let HTTPException
-        # bubble up, so we catch and render it as JSONResponse here.
-        from app.gateway.deps import get_current_user_from_request
-
-        if internal_user is not None:
-            user = internal_user
-        else:
-            try:
-                user = await get_current_user_from_request(request)
-            except HTTPException as exc:
-                return JSONResponse(status_code=exc.status_code, content={"detail": exc.detail})
-
         # Stamp both request.state.user (for the contextvar pattern)
         # and request.state.auth (so @require_permission's "auth is
         # None" branch short-circuits instead of running the entire
         # JWT-decode + DB-lookup pipeline a second time per request).
         request.state.user = user
+        request.state.auth_source = auth_source
         request.state.auth = AuthContext(user=user, permissions=_ALL_PERMISSIONS)
         token = set_current_user(user)
         try:

backend/app/gateway/csrf_middleware.py

@@ -14,6 +14,8 @@ from starlette.middleware.base import BaseHTTPMiddleware
 from starlette.responses import JSONResponse
 from starlette.types import ASGIApp
 
+from app.gateway.auth_disabled import is_auth_disabled
+
 CSRF_COOKIE_NAME = "csrf_token"
 CSRF_HEADER_NAME = "X-CSRF-Token"
 CSRF_TOKEN_LENGTH = 64  # bytes
@@ -38,6 +40,9 @@ def should_check_csrf(request: Request) -> bool:
     if request.method not in ("POST", "PUT", "DELETE", "PATCH"):
         return False
 
+    if is_auth_disabled():
+        return False
+
     path = request.url.path.rstrip("/")
     if path.startswith("/api/channels/webhooks/"):
         return False

backend/app/gateway/deps.py

@@ -331,6 +331,17 @@ async def get_current_user_from_request(request: Request):
 
     Raises HTTPException 401 if not authenticated.
     """
+    state = getattr(request, "state", None)
+    state_user = getattr(state, "user", None)
+    from app.gateway.auth_disabled import AUTH_SOURCE_AUTH_DISABLED, AUTH_SOURCE_INTERNAL, AUTH_SOURCE_SESSION
+
+    if state_user is not None and getattr(state, "auth_source", None) in {
+        AUTH_SOURCE_SESSION,
+        AUTH_SOURCE_AUTH_DISABLED,
+        AUTH_SOURCE_INTERNAL,
+    }:
+        return state_user
+
     from app.gateway.auth import decode_token
     from app.gateway.auth.errors import AuthErrorCode, AuthErrorResponse, TokenError, token_error_to_code
 

backend/app/gateway/langgraph_auth.py

@@ -20,6 +20,7 @@ from langgraph_sdk import Auth
 
 from app.gateway.auth.errors import TokenError
 from app.gateway.auth.jwt import decode_token
+from app.gateway.auth_disabled import AUTH_DISABLED_USER_ID, is_auth_disabled
 from app.gateway.deps import get_local_provider
 
 auth = Auth()
@@ -38,6 +39,9 @@ def _check_csrf(request) -> None:
     if method.upper() not in _CSRF_METHODS:
         return
 
+    if is_auth_disabled():
+        return
+
     cookie_token = request.cookies.get("csrf_token")
     header_token = request.headers.get("x-csrf-token")
 
@@ -66,6 +70,9 @@ async def authenticate(request):
     # are rejected early, even if the cookie carries a valid JWT.
     _check_csrf(request)
 
+    if is_auth_disabled():
+        return AUTH_DISABLED_USER_ID
+
     token = request.cookies.get("access_token")
     if not token:
         raise Auth.exceptions.HTTPException(

backend/app/gateway/routers/agents.py

@@ -1,5 +1,6 @@
 """CRUD API for custom agents."""
 
+import asyncio
 import logging
 import re
 import shutil
@@ -213,48 +214,61 @@ async def create_agent_endpoint(request: AgentCreateRequest) -> AgentResponse:
     user_id = get_effective_user_id()
     paths = get_paths()
 
-    agent_dir = paths.user_agent_dir(user_id, normalized_name)
-    legacy_dir = paths.agent_dir(normalized_name)
+    def _create_agent() -> AgentResponse | None:
+        # Worker thread: base-dir resolution, existence checks, directory/file
+        # creation, read-back, and failure cleanup are all blocking filesystem
+        # IO that must stay off the event loop.
+        agent_dir = paths.user_agent_dir(user_id, normalized_name)
+        legacy_dir = paths.agent_dir(normalized_name)
 
-    if agent_dir.exists() or legacy_dir.exists():
-        raise HTTPException(status_code=409, detail=f"Agent '{normalized_name}' already exists")
+        if legacy_dir.exists():
+            return None  # signals 409 to the caller
+
+        try:
+            try:
+                agent_dir.mkdir(parents=True, exist_ok=False)
+            except FileExistsError:
+                return None  # signals 409 to the caller
+            # Write config.yaml
+            config_data: dict = {"name": normalized_name}
+            if request.description:
+                config_data["description"] = request.description
+            if request.model is not None:
+                config_data["model"] = request.model
+            if request.tool_groups is not None:
+                config_data["tool_groups"] = request.tool_groups
+            if request.skills is not None:
+                config_data["skills"] = request.skills
+
+            config_file = agent_dir / "config.yaml"
+            with open(config_file, "w", encoding="utf-8") as f:
+                yaml.dump(config_data, f, default_flow_style=False, allow_unicode=True)
+
+            # Write SOUL.md
+            soul_file = agent_dir / "SOUL.md"
+            soul_file.write_text(request.soul, encoding="utf-8")
+
+            logger.info(f"Created agent '{normalized_name}' at {agent_dir}")
+
+            agent_cfg = load_agent_config(normalized_name, user_id=user_id)
+            return _agent_config_to_response(agent_cfg, include_soul=True, user_id=user_id)
+        except Exception:
+            # Clean up partial state on failure before surfacing the error.
+            if agent_dir.exists():
+                shutil.rmtree(agent_dir)
+            raise
 
     try:
-        agent_dir.mkdir(parents=True, exist_ok=True)
-
-        # Write config.yaml
-        config_data: dict = {"name": normalized_name}
-        if request.description:
-            config_data["description"] = request.description
-        if request.model is not None:
-            config_data["model"] = request.model
-        if request.tool_groups is not None:
-            config_data["tool_groups"] = request.tool_groups
-        if request.skills is not None:
-            config_data["skills"] = request.skills
-
-        config_file = agent_dir / "config.yaml"
-        with open(config_file, "w", encoding="utf-8") as f:
-            yaml.dump(config_data, f, default_flow_style=False, allow_unicode=True)
-
-        # Write SOUL.md
-        soul_file = agent_dir / "SOUL.md"
-        soul_file.write_text(request.soul, encoding="utf-8")
-
-        logger.info(f"Created agent '{normalized_name}' at {agent_dir}")
-
-        agent_cfg = load_agent_config(normalized_name, user_id=user_id)
-        return _agent_config_to_response(agent_cfg, include_soul=True, user_id=user_id)
-
-    except HTTPException:
-        raise
+        response = await asyncio.to_thread(_create_agent)
     except Exception as e:
-        # Clean up on failure
-        if agent_dir.exists():
-            shutil.rmtree(agent_dir)
         logger.error(f"Failed to create agent '{request.name}': {e}", exc_info=True)
         raise HTTPException(status_code=500, detail=f"Failed to create agent: {str(e)}")
 
+    if response is None:
+        raise HTTPException(status_code=409, detail=f"Agent '{normalized_name}' already exists")
+
+    return response
+
 
 @router.put(
     "/agents/{name}",
@@ -428,19 +442,30 @@ async def delete_agent(name: str) -> None:
     name = _normalize_agent_name(name)
     user_id = get_effective_user_id()
     paths = get_paths()
-    agent_dir = paths.user_agent_dir(user_id, name)
 
-    if not agent_dir.exists():
-        if paths.agent_dir(name).exists():
-            raise HTTPException(
-                status_code=409,
-                detail=(f"Agent '{name}' only exists in the legacy shared layout and is not scoped to a user. Run scripts/migrate_user_isolation.py to move legacy agents into the per-user layout before deleting."),
-            )
-        raise HTTPException(status_code=404, detail=f"Agent '{name}' not found")
+    def _remove_agent_dir() -> tuple[str, str]:
+        # Runs in a worker thread: resolving the base dir, probing the directory
+        # (`exists`), and removing it (`rmtree`) are all blocking filesystem IO
+        # that must stay off the event loop.
+        agent_dir = paths.user_agent_dir(user_id, name)
+        if not agent_dir.exists():
+            outcome = "legacy" if paths.agent_dir(name).exists() else "missing"
+            return outcome, str(agent_dir)
+        shutil.rmtree(agent_dir)
+        return "deleted", str(agent_dir)
 
     try:
-        shutil.rmtree(agent_dir)
-        logger.info(f"Deleted agent '{name}' from {agent_dir}")
+        outcome, agent_dir = await asyncio.to_thread(_remove_agent_dir)
     except Exception as e:
         logger.error(f"Failed to delete agent '{name}': {e}", exc_info=True)
         raise HTTPException(status_code=500, detail=f"Failed to delete agent: {str(e)}")
+
+    if outcome == "legacy":
+        raise HTTPException(
+            status_code=409,
+            detail=(f"Agent '{name}' only exists in the legacy shared layout and is not scoped to a user. Run scripts/migrate_user_isolation.py to move legacy agents into the per-user layout before deleting."),
+        )
+    if outcome == "missing":
+        raise HTTPException(status_code=404, detail=f"Agent '{name}' not found")
+
+    logger.info(f"Deleted agent '{name}' from {agent_dir}")

backend/app/gateway/routers/auth.py

@@ -341,9 +341,19 @@ async def change_password(request: Request, response: Response, body: ChangePass
     - Re-issues session cookie with new token_version
     """
     from app.gateway.auth.password import hash_password_async, verify_password_async
+    from app.gateway.auth_disabled import AUTH_SOURCE_AUTH_DISABLED
 
     user = await get_current_user_from_request(request)
 
+    if getattr(request.state, "auth_source", None) == AUTH_SOURCE_AUTH_DISABLED:
+        raise HTTPException(
+            status_code=status.HTTP_400_BAD_REQUEST,
+            detail=AuthErrorResponse(
+                code=AuthErrorCode.INVALID_CREDENTIALS,
+                message="Password changes are not available when DEER_FLOW_AUTH_DISABLED=1.",
+            ).model_dump(),
+        )
+
     if user.password_hash is None:
         raise HTTPException(status_code=status.HTTP_400_BAD_REQUEST, detail=AuthErrorResponse(code=AuthErrorCode.INVALID_CREDENTIALS, message="OAuth users cannot change password").model_dump())
 

backend/docs/REPLAY_E2E.md

@@ -50,18 +50,22 @@ gateway's own run/event stores using the request's auth context, so the real
 ## How replay works
 
 `tests/replay_provider.py::ReplayChatModel` returns recorded assistant turns keyed
-by a **normalized hash of the conversation** (human / ai / tool messages — role,
-text, tool-call name+args; with `<system-reminder>`, dates, UUIDs, tmp paths
-stripped). A miss raises loudly rather than passing silently.
+by a **normalized hash of the model caller + conversation**. The conversation is
+human / ai / tool messages — role, text, tool-call name+args; with
+`<system-reminder>`, dates, UUIDs, tmp paths stripped. The caller is the stable
+source of the model call (`lead_agent`, `middleware:title`, `suggest_agent`,
+`subagent:*`, etc.). A miss raises loudly rather than passing silently.
 
 **The system prompt is excluded from the match key.** The lead-agent system
 prompt is a living, frequently-edited implementation detail — its wording changes
 across PRs (e.g. #3195 added a "File Editing Workflow" section). Hashing it would
 make every fixture go stale and red-fail unrelated PRs the moment anyone edits the
 prompt. The conversation flow (user input → tool calls → results → answer) is the
-stable contract that identifies a recorded turn. (This mirrors how open-design's
-mock picker keys on the user prompt, not the system internals.) Combined with
-pinning skills + extensions empty and disabling memory/summarization
+stable contract that identifies a recorded turn. The caller still stays in the
+key so two different model users with identical conversation text do not compete
+for the same replay bucket. (This mirrors how open-design's mock picker keys on
+the user prompt, not the system internals.) Combined with pinning skills +
+extensions empty and disabling memory/summarization
 (`tests/_replay_fixture.py::build_config_yaml`), a fixture replays the same across
 machines, days, prompt edits, and CI. Replaying needs **no API key**.
 

backend/packages/harness/deerflow/agents/lead_agent/agent.py

@@ -49,6 +49,8 @@ from deerflow.tracing import build_tracing_callbacks
 
 logger = logging.getLogger(__name__)
 
+_BOOTSTRAP_SKILL_NAMES = {"bootstrap"}
+
 
 def _get_runtime_config(config: RunnableConfig) -> dict:
     """Merge legacy configurable options with LangGraph runtime context."""
@@ -271,6 +273,7 @@ def build_middlewares(
     agent_name: str | None = None,
     custom_middlewares: list[AgentMiddleware] | None = None,
     *,
+    available_skills: set[str] | None = None,
     app_config: AppConfig | None = None,
     deferred_setup=None,
 ):
@@ -302,6 +305,13 @@ def build_middlewares(
 
     middlewares.append(DynamicContextMiddleware(agent_name=agent_name, app_config=resolved_app_config))
 
+    # Deterministically load a full SKILL.md when the user starts the turn with
+    # /skill-name. This keeps the base system prompt metadata-only while giving
+    # explicit user activation priority over model-side relevance guessing.
+    from deerflow.agents.middlewares.skill_activation_middleware import SkillActivationMiddleware
+
+    middlewares.append(SkillActivationMiddleware(available_skills=available_skills, app_config=resolved_app_config))
+
     # Add summarization middleware if enabled
     summarization_middleware = _create_summarization_middleware(app_config=resolved_app_config)
     if summarization_middleware is not None:
@@ -369,7 +379,7 @@ def build_middlewares(
 
 def _available_skill_names(agent_config, is_bootstrap: bool) -> set[str] | None:
     if is_bootstrap:
-        return {"bootstrap"}
+        return set(_BOOTSTRAP_SKILL_NAMES)
     if agent_config and agent_config.skills is not None:
         return set(agent_config.skills)
     return None
@@ -475,17 +485,25 @@ def _make_lead_agent(config: RunnableConfig, *, app_config: AppConfig):
 
     if is_bootstrap:
         # Special bootstrap agent with minimal prompt for initial custom agent creation flow
+        # Keep the bootstrap skill set intentionally narrow so agent creation
+        # remains deterministic before the custom agent's own config exists.
         raw_tools = get_available_tools(model_name=model_name, subagent_enabled=subagent_enabled, app_config=resolved_app_config) + [setup_agent]
         filtered = filter_tools_by_skill_allowed_tools(raw_tools, skills_for_tool_policy)
         final_tools, setup = assemble_deferred_tools(filtered, enabled=resolved_app_config.tool_search.enabled)
         return create_agent(
             model=create_chat_model(name=model_name, thinking_enabled=thinking_enabled, app_config=resolved_app_config, attach_tracing=False),
             tools=final_tools,
-            middleware=build_middlewares(config, model_name=model_name, app_config=resolved_app_config, deferred_setup=setup),
+            middleware=build_middlewares(
+                config,
+                model_name=model_name,
+                available_skills=set(_BOOTSTRAP_SKILL_NAMES),
+                app_config=resolved_app_config,
+                deferred_setup=setup,
+            ),
             system_prompt=apply_prompt_template(
                 subagent_enabled=subagent_enabled,
                 max_concurrent_subagents=max_concurrent_subagents,
-                available_skills=set(["bootstrap"]),
+                available_skills=set(_BOOTSTRAP_SKILL_NAMES),
                 app_config=resolved_app_config,
                 deferred_names=setup.deferred_names,
             ),
@@ -502,12 +520,19 @@ def _make_lead_agent(config: RunnableConfig, *, app_config: AppConfig):
     return create_agent(
         model=create_chat_model(name=model_name, thinking_enabled=thinking_enabled, reasoning_effort=reasoning_effort, app_config=resolved_app_config, attach_tracing=False),
         tools=final_tools,
-        middleware=build_middlewares(config, model_name=model_name, agent_name=agent_name, app_config=resolved_app_config, deferred_setup=setup),
+        middleware=build_middlewares(
+            config,
+            model_name=model_name,
+            agent_name=agent_name,
+            available_skills=available_skills,
+            app_config=resolved_app_config,
+            deferred_setup=setup,
+        ),
         system_prompt=apply_prompt_template(
             subagent_enabled=subagent_enabled,
             max_concurrent_subagents=max_concurrent_subagents,
             agent_name=agent_name,
-            available_skills=set(agent_config.skills) if agent_config and agent_config.skills is not None else None,
+            available_skills=available_skills,
             app_config=resolved_app_config,
             deferred_names=setup.deferred_names,
         ),

backend/packages/harness/deerflow/agents/lead_agent/prompt.py

@@ -625,6 +625,11 @@ You have access to skills that provide optimized workflows for specific tasks. E
 4. Load referenced resources only when needed during execution
 5. Follow the skill's instructions precisely
 
+**Explicit Slash Skill Activation:**
+- If the user starts a request with `/<skill-name>`, that skill was explicitly requested for the current turn.
+- Follow the activated skill before choosing a general workflow.
+- The runtime injects the activated skill content for explicit slash activations; do not call `read_file` for that SKILL.md again unless the injected skill references supporting resources you need.
+
 **Skills are located at:** {container_base_path}
 {skill_evolution_section}
 {skills_list}

backend/packages/harness/deerflow/agents/middlewares/skill_activation_middleware.py

@@ -0,0 +1,289 @@
+"""Middleware for explicit slash skill activation."""
+
+from __future__ import annotations
+
+import asyncio
+import hashlib
+import html
+import logging
+import uuid
+from collections.abc import Awaitable, Callable
+from dataclasses import dataclass
+from pathlib import Path
+from typing import TYPE_CHECKING, override
+
+from langchain.agents.middleware import AgentMiddleware
+from langchain.agents.middleware.types import ModelRequest, ModelResponse
+from langchain_core.messages import AIMessage, HumanMessage
+
+from deerflow.skills.slash import parse_slash_skill_reference, resolve_slash_skill
+from deerflow.skills.storage import get_or_new_skill_storage
+from deerflow.skills.storage.skill_storage import SkillStorage
+from deerflow.skills.types import SKILL_MD_FILE
+from deerflow.utils.messages import get_original_user_content_text
+
+if TYPE_CHECKING:
+    from deerflow.config.app_config import AppConfig
+
+logger = logging.getLogger(__name__)
+
+_SLASH_SKILL_ACTIVATION_KEY = "slash_skill_activation"
+_SLASH_SKILL_ACTIVATION_TARGET_ID_KEY = "slash_skill_activation_target_id"
+_SUMMARY_MESSAGE_NAME = "summary"
+
+
+@dataclass(frozen=True, slots=True)
+class _Activation:
+    skill_name: str
+    category: str
+    container_file_path: str
+    skill_content: str
+    content_hash: str
+    remaining_text: str
+
+
+@dataclass(frozen=True, slots=True)
+class _ActivationResolution:
+    activation: _Activation | None = None
+    failure_message: str | None = None
+
+
+def is_slash_skill_activation_reminder(message: object) -> bool:
+    """Return whether a message is hidden slash-skill activation context."""
+    return isinstance(message, HumanMessage) and bool(message.additional_kwargs.get(_SLASH_SKILL_ACTIVATION_KEY))
+
+
+def _is_user_activation_target(message: object) -> bool:
+    if not isinstance(message, HumanMessage):
+        return False
+    if message.name == _SUMMARY_MESSAGE_NAME:
+        return False
+    if message.additional_kwargs.get("hide_from_ui"):
+        return False
+    return True
+
+
+class SkillActivationMiddleware(AgentMiddleware):
+    """Inject full SKILL.md content when the user explicitly types /skill-name."""
+
+    def __init__(
+        self,
+        *,
+        available_skills: set[str] | None = None,
+        app_config: AppConfig | None = None,
+    ) -> None:
+        super().__init__()
+        self._available_skills = set(available_skills) if available_skills is not None else None
+        self._app_config = app_config
+
+    def _storage(self) -> SkillStorage:
+        if self._app_config is not None:
+            return get_or_new_skill_storage(app_config=self._app_config)
+        return get_or_new_skill_storage()
+
+    @staticmethod
+    def _read_skill_content(skill_file: Path, skills_root: Path) -> str:
+        if skill_file.name != SKILL_MD_FILE:
+            raise ValueError(f"Expected {SKILL_MD_FILE}, got {skill_file.name}")
+        resolved_root = skills_root.resolve()
+        resolved_file = skill_file.resolve()
+        try:
+            resolved_file.relative_to(resolved_root)
+        except ValueError as exc:
+            raise ValueError("Resolved skill file must stay within the configured skills root.") from exc
+        if not resolved_file.is_file():
+            raise FileNotFoundError(resolved_file)
+        return resolved_file.read_text(encoding="utf-8")
+
+    def _resolve_activation(self, text: str) -> _ActivationResolution | None:
+        reference = parse_slash_skill_reference(text)
+        if reference is None:
+            return None
+
+        storage = self._storage()
+        skills = storage.load_skills(enabled_only=False)
+        skill = next((candidate for candidate in skills if candidate.name == reference.name), None)
+        if skill is None:
+            return _ActivationResolution(failure_message=f"Skill `/{reference.name}` is not installed.")
+        if not skill.enabled:
+            return _ActivationResolution(failure_message=f"Skill `/{reference.name}` is installed but disabled. Enable it before using slash activation.")
+        if self._available_skills is not None and reference.name not in self._available_skills:
+            return _ActivationResolution(failure_message=f"Skill `/{reference.name}` is not available for this agent.")
+
+        resolved = resolve_slash_skill(
+            text,
+            skills,
+            available_skills=self._available_skills,
+            container_base_path=storage.get_container_root(),
+        )
+        if resolved is None:
+            return _ActivationResolution(failure_message=f"Skill `/{reference.name}` could not be resolved.")
+
+        try:
+            skill_content = self._read_skill_content(resolved.skill.skill_file, storage.get_skills_root_path())
+        except (OSError, ValueError):
+            logger.exception("Failed to read slash-activated skill %s", resolved.skill.name)
+            return _ActivationResolution(failure_message=f"Skill `/{reference.name}` could not be loaded safely. Please check the skill installation.")
+
+        content_hash = hashlib.sha256(skill_content.encode("utf-8")).hexdigest()
+        return _ActivationResolution(
+            activation=_Activation(
+                skill_name=resolved.skill.name,
+                category=str(resolved.skill.category),
+                container_file_path=resolved.container_file_path,
+                skill_content=skill_content,
+                content_hash=content_hash,
+                remaining_text=resolved.remaining_text,
+            )
+        )
+
+    @staticmethod
+    def _build_activation_reminder(activation: _Activation) -> str:
+        user_request = activation.remaining_text or ("No additional task text was provided after the slash skill command. Ask the user what they want to do with this skill if the next step is unclear.")
+        escaped_user_request = html.escape(user_request, quote=False)
+        escaped_skill_content = html.escape(activation.skill_content, quote=False)
+        escaped_skill_name = html.escape(activation.skill_name, quote=True)
+        escaped_category = html.escape(activation.category, quote=True)
+        escaped_path = html.escape(activation.container_file_path, quote=True)
+        escaped_content_hash = html.escape(activation.content_hash, quote=True)
+        return f"""<slash_skill_activation>
+The user explicitly activated the `{activation.skill_name}` skill for this turn.
+Treat the task text as:
+<user_request>
+{escaped_user_request}
+</user_request>
+
+Follow this skill before choosing a general workflow. Load supporting resources from the same skill directory only when needed.
+
+<skill name="{escaped_skill_name}" category="{escaped_category}" path="{escaped_path}" sha256="{escaped_content_hash}">
+<skill_content encoding="xml-escaped">
+{escaped_skill_content}
+</skill_content>
+</skill>
+</slash_skill_activation>"""
+
+    @staticmethod
+    def _has_existing_activation_for_target(messages: list, target_index: int, target: HumanMessage) -> bool:
+        if target_index <= 0:
+            return False
+
+        if target.id:
+            for previous in messages[:target_index]:
+                if not is_slash_skill_activation_reminder(previous):
+                    continue
+                target_id = previous.additional_kwargs.get(_SLASH_SKILL_ACTIVATION_TARGET_ID_KEY)
+                if target_id == target.id or previous.id == f"{target.id}__slash_activation":
+                    return True
+
+        previous = messages[target_index - 1]
+        return is_slash_skill_activation_reminder(previous)
+
+    def _find_activation_target(self, messages: list) -> tuple[int, HumanMessage, _ActivationResolution] | None:
+        if not messages:
+            return None
+
+        target_index = next((idx for idx in range(len(messages) - 1, -1, -1) if _is_user_activation_target(messages[idx])), None)
+        if target_index is None:
+            return None
+
+        target = messages[target_index]
+        if target is None:
+            return None
+        if self._has_existing_activation_for_target(messages, target_index, target):
+            return None
+
+        content = get_original_user_content_text(target.content, target.additional_kwargs)
+        resolution = self._resolve_activation(content)
+        if resolution is None:
+            return None
+        return target_index, target, resolution
+
+    @staticmethod
+    def _record_activation(request: ModelRequest, activation: _Activation, *, hook: str) -> None:
+        runtime = getattr(request, "runtime", None)
+        context = getattr(runtime, "context", None)
+        journal = context.get("__run_journal") if isinstance(context, dict) else None
+        if journal is None:
+            return
+        try:
+            journal.record_middleware(
+                "skill_activation",
+                name="SkillActivationMiddleware",
+                hook=hook,
+                action="activate",
+                changes={
+                    "skill_name": activation.skill_name,
+                    "category": activation.category,
+                    "path": activation.container_file_path,
+                    "content_hash": activation.content_hash,
+                },
+            )
+        except Exception:
+            logger.debug("Failed to record slash skill activation audit event", exc_info=True)
+
+    def _prepare_model_request(self, request: ModelRequest, *, hook: str) -> ModelRequest | AIMessage | None:
+        target_and_resolution = self._find_activation_target(list(request.messages))
+        if target_and_resolution is None:
+            return None
+
+        target_index, target, resolution = target_and_resolution
+        if resolution.failure_message:
+            return AIMessage(content=resolution.failure_message)
+
+        activation = resolution.activation
+        if activation is None:
+            return None
+
+        logger.info(
+            "SkillActivationMiddleware: activating slash skill %s category=%s path=%s hash=%s",
+            activation.skill_name,
+            activation.category,
+            activation.container_file_path,
+            activation.content_hash,
+        )
+        self._record_activation(request, activation, hook=hook)
+        activation_msg = self._make_activation_message(target, self._build_activation_reminder(activation))
+        messages = list(request.messages)
+        messages.insert(target_index, activation_msg)
+        return request.override(messages=messages)
+
+    @staticmethod
+    def _make_activation_message(target: HumanMessage, activation_content: str) -> HumanMessage:
+        stable_id = target.id or str(uuid.uuid4())
+        additional_kwargs = {
+            "hide_from_ui": True,
+            _SLASH_SKILL_ACTIVATION_KEY: True,
+        }
+        if target.id:
+            additional_kwargs[_SLASH_SKILL_ACTIVATION_TARGET_ID_KEY] = target.id
+        return HumanMessage(
+            content=activation_content,
+            id=f"{stable_id}__slash_activation",
+            additional_kwargs=additional_kwargs,
+        )
+
+    @override
+    def wrap_model_call(
+        self,
+        request: ModelRequest,
+        handler: Callable[[ModelRequest], ModelResponse],
+    ) -> ModelResponse | AIMessage:
+        prepared = self._prepare_model_request(request, hook="wrap_model_call")
+        if prepared is None:
+            return handler(request)
+        if isinstance(prepared, AIMessage):
+            return prepared
+        return handler(prepared)
+
+    @override
+    async def awrap_model_call(
+        self,
+        request: ModelRequest,
+        handler: Callable[[ModelRequest], Awaitable[ModelResponse]],
+    ) -> ModelResponse | AIMessage:
+        prepared = await asyncio.to_thread(self._prepare_model_request, request, hook="awrap_model_call")
+        if prepared is None:
+            return await handler(request)
+        if isinstance(prepared, AIMessage):
+            return prepared
+        return await handler(prepared)

backend/packages/harness/deerflow/agents/middlewares/uploads_middleware.py

@@ -13,6 +13,7 @@ from langgraph.runtime import Runtime
 from deerflow.config.paths import Paths, get_paths
 from deerflow.runtime.user_context import get_effective_user_id
 from deerflow.utils.file_conversion import extract_outline
+from deerflow.utils.messages import ORIGINAL_USER_CONTENT_KEY, message_content_to_text
 
 logger = logging.getLogger(__name__)
 
@@ -265,6 +266,8 @@ class UploadsMiddleware(AgentMiddleware[UploadsMiddlewareState]):
 
         # Extract original content - handle both string and list formats
         original_content = last_message.content
+        additional_kwargs = dict(last_message.additional_kwargs or {})
+        additional_kwargs.setdefault(ORIGINAL_USER_CONTENT_KEY, message_content_to_text(original_content))
         if isinstance(original_content, str):
             # Simple case: string content, just prepend files message
             updated_content = f"{files_message}\n\n{original_content}"
@@ -285,7 +288,7 @@ class UploadsMiddleware(AgentMiddleware[UploadsMiddlewareState]):
             content=updated_content,
             id=last_message.id,
             name=last_message.name,
-            additional_kwargs=last_message.additional_kwargs,
+            additional_kwargs=additional_kwargs,
         )
 
         messages[last_message_index] = updated_message

backend/packages/harness/deerflow/client.py

@@ -247,7 +247,15 @@ class DeerFlowClient:
             # Attaching them again on the model would emit duplicate spans.
             "model": create_chat_model(name=model_name, thinking_enabled=thinking_enabled, attach_tracing=False),
             "tools": final_tools,
-            "middleware": build_middlewares(config, model_name=model_name, agent_name=self._agent_name, custom_middlewares=self._middlewares, deferred_setup=deferred_setup),
+            "middleware": build_middlewares(
+                config,
+                model_name=model_name,
+                agent_name=self._agent_name,
+                available_skills=self._available_skills,
+                custom_middlewares=self._middlewares,
+                app_config=self._app_config,
+                deferred_setup=deferred_setup,
+            ),
             "system_prompt": apply_prompt_template(
                 subagent_enabled=subagent_enabled,
                 max_concurrent_subagents=max_concurrent_subagents,

backend/packages/harness/deerflow/config/app_config.py

@@ -7,7 +7,7 @@ from typing import Any, Self
 
 import yaml
 from dotenv import load_dotenv
-from pydantic import BaseModel, ConfigDict, Field
+from pydantic import BaseModel, ConfigDict, Field, field_validator
 
 from deerflow.config.acp_config import ACPAgentConfig, load_acp_config_from_dict
 from deerflow.config.agents_api_config import AgentsApiConfig, load_agents_api_config_from_dict
@@ -150,6 +150,21 @@ class AppConfig(BaseModel):
         ),
     )
 
+    @field_validator("models", "tools", "tool_groups", mode="before")
+    @classmethod
+    def _coerce_null_list_sections(cls, value: Any) -> Any:
+        """Treat a present-but-empty config section as an empty list.
+
+        Commenting out every entry under a top-level YAML key — e.g. ``models:``
+        with only comments beneath it, exactly as shipped in
+        ``config.example.yaml`` — makes PyYAML parse the value as ``None``.
+        Without this, the documented ``cp config.example.yaml config.yaml``
+        first-run flow crashes with an opaque ``Input should be a valid list``
+        pydantic error. Coercing ``None`` to ``[]`` keeps that flow working and
+        matches the field's own ``default_factory=list``.
+        """
+        return [] if value is None else value
+
     @classmethod
     def resolve_config_path(cls, config_path: str | None = None) -> Path:
         """Resolve the config file path.
@@ -211,6 +226,11 @@ class AppConfig(BaseModel):
         config_data["extensions"] = extensions_config.model_dump()
 
         result = cls.model_validate(config_data)
+        if not result.models:
+            logger.warning(
+                "No models are configured in %s. Add at least one entry under `models:` (see the commented examples in config.example.yaml) or run `make setup`.",
+                resolved_path,
+            )
         acp_agents = cls._validate_acp_agents(config_data.get("acp_agents", {}))
         cls._apply_singleton_configs(result, acp_agents)
         return result

backend/packages/harness/deerflow/config/sandbox_config.py

@@ -4,7 +4,20 @@ from pydantic import BaseModel, ConfigDict, Field
 class VolumeMountConfig(BaseModel):
     """Configuration for a volume mount."""
 
-    host_path: str = Field(..., description="Path on the host machine")
+    host_path: str = Field(
+        ...,
+        description=(
+            "Source path for the mount. Resolution depends on the active provider: "
+            "``LocalSandboxProvider`` checks this path from the gateway process — in "
+            "``make dev`` that is the host machine, but in Docker deployments "
+            "(``make up`` / docker-compose) it is the path *inside* the "
+            "``deer-flow-gateway`` container, so the host directory must also be "
+            "bind-mounted into the gateway service for the mount to take effect. "
+            "``AioSandboxProvider`` (DooD) passes this value straight to ``docker -v`` "
+            "for the sandbox container, where it is resolved by the host Docker daemon "
+            "from the host machine's perspective."
+        ),
+    )
     container_path: str = Field(..., description="Path inside the container")
     read_only: bool = Field(default=False, description="Whether the mount is read-only")
 

backend/packages/harness/deerflow/models/patched_stepfun.py

@@ -0,0 +1,175 @@
+"""Patched ChatOpenAI adapter for StepFun reasoning models.
+
+StepFun returns ``reasoning`` (or ``reasoning_content`` with deepseek-style) in
+both streaming deltas and non-streaming responses. Standard ``ChatOpenAI``
+ignores these non-standard fields, so reasoning content is silently dropped.
+This adapter captures reasoning from all response paths and replays it on
+historical assistant messages for multi-turn tool-call conversations.
+"""
+
+from __future__ import annotations
+
+from collections.abc import Mapping
+from typing import Any
+
+from langchain_core.language_models import LanguageModelInput
+from langchain_core.messages import AIMessage, AIMessageChunk
+from langchain_core.outputs import ChatGeneration, ChatGenerationChunk, ChatResult
+from langchain_openai import ChatOpenAI
+
+from deerflow.models.assistant_payload_replay import (
+    restore_assistant_payloads,
+    restore_reasoning_content,
+)
+
+_MISSING = object()
+
+
+def _extract_reasoning(value: Any) -> str | object:
+    """Return reasoning content from a dict/Pydantic object.
+
+    StepFun may return reasoning via ``reasoning`` (default) or
+    ``reasoning_content`` (deepseek-style). Check both fields.
+    """
+    if isinstance(value, Mapping):
+        # Check reasoning_content first (deepseek-style), then reasoning (default)
+        for field in ("reasoning_content", "reasoning"):
+            if field in value and value[field] is not None:
+                return value[field]
+        return _MISSING
+
+    # Pydantic / SDK object attributes
+    for field in ("reasoning_content", "reasoning"):
+        attr = getattr(value, field, _MISSING)
+        if attr is not _MISSING and attr is not None:
+            return attr
+
+    # Some SDK versions store extra fields in model_extra
+    model_extra = getattr(value, "model_extra", None)
+    if isinstance(model_extra, Mapping):
+        for field in ("reasoning_content", "reasoning"):
+            if field in model_extra and model_extra[field] is not None:
+                return model_extra[field]
+
+    return _MISSING
+
+
+def _with_reasoning_content(message: AIMessage | AIMessageChunk, reasoning: str) -> AIMessage | AIMessageChunk:
+    """Return a copy of *message* with reasoning_content stored in additional_kwargs."""
+    additional_kwargs = dict(message.additional_kwargs)
+    if additional_kwargs.get("reasoning_content") != reasoning:
+        additional_kwargs["reasoning_content"] = reasoning
+    return message.model_copy(update={"additional_kwargs": additional_kwargs})
+
+
+def _get_typed_choice_message(response: Any, index: int) -> Any:
+    """Extract the SDK-typed choice message at *index*, if available."""
+    choices = getattr(response, "choices", None)
+    if choices is None:
+        return None
+    try:
+        return choices[index].message
+    except (AttributeError, IndexError, TypeError):
+        return None
+
+
+class PatchedChatStepFun(ChatOpenAI):
+    """ChatOpenAI with full reasoning support for StepFun models.
+
+    Captures ``reasoning`` / ``reasoning_content`` from both streaming and
+    non-streaming responses and replays it on historical assistant messages in
+    multi-turn tool-call conversations.
+    """
+
+    @classmethod
+    def is_lc_serializable(cls) -> bool:
+        return True
+
+    @property
+    def lc_secrets(self) -> dict[str, str]:
+        return {"api_key": "STEPFUN_API_KEY", "openai_api_key": "STEPFUN_API_KEY"}
+
+    # --- Request payload replay ---
+
+    def _get_request_payload(
+        self,
+        input_: LanguageModelInput,
+        *,
+        stop: list[str] | None = None,
+        **kwargs: Any,
+    ) -> dict:
+        """Restore ``reasoning_content`` on historical assistant messages."""
+        original_messages = self._convert_input(input_).to_messages()
+        payload = super()._get_request_payload(input_, stop=stop, **kwargs)
+
+        restore_assistant_payloads(
+            payload.get("messages", []),
+            original_messages,
+            restore_reasoning_content,
+        )
+
+        return payload
+
+    # --- Streaming reasoning capture ---
+
+    def _convert_chunk_to_generation_chunk(
+        self,
+        chunk: dict,
+        default_chunk_class: type,
+        base_generation_info: dict | None,
+    ) -> ChatGenerationChunk | None:
+        """Capture ``reasoning`` / ``reasoning_content`` from streaming deltas."""
+        generation_chunk = super()._convert_chunk_to_generation_chunk(
+            chunk,
+            default_chunk_class,
+            base_generation_info,
+        )
+        if generation_chunk is None:
+            return None
+
+        choices = chunk.get("choices", [])
+        if choices:
+            delta = choices[0].get("delta") or {}
+            reasoning = _extract_reasoning(delta)
+            if reasoning is not _MISSING and isinstance(generation_chunk.message, AIMessageChunk):
+                generation_chunk = ChatGenerationChunk(
+                    message=_with_reasoning_content(generation_chunk.message, reasoning),
+                    generation_info=generation_chunk.generation_info,
+                )
+
+        return generation_chunk
+
+    # --- Non-streaming reasoning capture ---
+
+    def _create_chat_result(
+        self,
+        response: dict | Any,
+        generation_info: dict | None = None,
+    ) -> ChatResult:
+        """Extract ``reasoning`` / ``reasoning_content`` from non-streaming responses."""
+        result = super()._create_chat_result(response, generation_info)
+        response_dict = response if isinstance(response, dict) else response.model_dump()
+        choices = response_dict.get("choices", [])
+
+        patched_generations: list[ChatGeneration] | None = None
+        for index, generation in enumerate(result.generations):
+            choice = choices[index] if index < len(choices) else {}
+            choice_message = choice.get("message", {}) if isinstance(choice, Mapping) else {}
+            reasoning = _extract_reasoning(choice_message)
+
+            if reasoning is _MISSING and not isinstance(response, dict):
+                reasoning = _extract_reasoning(_get_typed_choice_message(response, index))
+
+            message = generation.message
+            if reasoning is not _MISSING and isinstance(message, AIMessage):
+                if patched_generations is None:
+                    patched_generations = list(result.generations)
+                patched_generations[index] = ChatGeneration(
+                    message=_with_reasoning_content(message, reasoning),
+                    generation_info=generation.generation_info,
+                )
+
+        return ChatResult(
+            generations=patched_generations or result.generations,
+            llm_output=result.llm_output,
+        )

backend/packages/harness/deerflow/runtime/journal.py

@@ -164,7 +164,18 @@ class RunJournal(BaseCallbackHandler):
                 metadata={"caller": caller, **(metadata or {})},
             )
 
-    def on_chain_end(self, outputs: Any, *, run_id: UUID, **kwargs: Any) -> None:
+    def on_chain_end(
+        self,
+        outputs: Any,
+        *,
+        run_id: UUID,
+        parent_run_id: UUID | None = None,
+        **kwargs: Any,
+    ) -> None:
+        # Nested chain ends fire for internal graph nodes; only the root chain
+        # represents the user-visible run lifecycle.
+        if parent_run_id is not None:
+            return
         self._put(event_type="run.end", category="outputs", content=outputs, metadata={"status": "success"})
         self._flush_sync()
 

backend/packages/harness/deerflow/sandbox/local/local_sandbox_provider.py

@@ -147,7 +147,17 @@ class LocalSandboxProvider(SandboxProvider):
                             mount.container_path,
                         )
                         continue
-                    # Ensure the host path exists before adding mapping
+                    # Ensure the host path exists before adding mapping.
+                    #
+                    # ``host_path`` is resolved against the filesystem of the
+                    # process running this provider — for ``make dev`` that is
+                    # the host machine, but for ``make up`` it is the
+                    # ``deer-flow-gateway`` container, so any host path that
+                    # isn't bind-mounted into the gateway image will be missing
+                    # here. Skipping silently makes this a high-cost-to-debug
+                    # silent failure (sandbox skill / tool reads an empty dir
+                    # instead of the configured mount), so escalate to ERROR
+                    # and include actionable guidance. See #3244.
                     if host_path.exists():
                         mappings.append(
                             PathMapping(
@@ -157,10 +167,16 @@ class LocalSandboxProvider(SandboxProvider):
                             )
                         )
                     else:
-                        logger.warning(
-                            "Mount host_path does not exist, skipping: %s -> %s",
+                        logger.error(
+                            "sandbox.mounts entry %s -> %s ignored: host_path %s does not exist from the "
+                            "perspective of the gateway process. In Docker deployments (make up / docker-compose), "
+                            "this path must also be bind-mounted into the gateway container — add a matching "
+                            "volume entry under services.gateway.volumes in docker/docker-compose.yaml (and use "
+                            "the in-container path here), or run in local mode (make dev) where the gateway sees "
+                            "the host filesystem directly.",
                             mount.host_path,
                             mount.container_path,
+                            mount.host_path,
                         )
         except Exception as e:
             # Log but don't fail if config loading fails

backend/packages/harness/deerflow/skills/slash.py

@@ -0,0 +1,65 @@
+from __future__ import annotations
+
+import re
+from dataclasses import dataclass
+
+from deerflow.skills.types import Skill
+
+RESERVED_SLASH_SKILL_NAMES = frozenset({"bootstrap", "help", "memory", "models", "new", "status"})
+_SLASH_SKILL_RE = re.compile(r"^/([a-z0-9]+(?:-[a-z0-9]+)*)(?:\s+|$)")
+
+
+@dataclass(frozen=True, slots=True)
+class SlashSkillReference:
+    """Parsed slash-skill command with the skill name and remaining task text."""
+
+    name: str
+    remaining_text: str
+
+
+@dataclass(frozen=True, slots=True)
+class ResolvedSlashSkill:
+    """Slash-skill activation resolved against enabled runtime-visible skills."""
+
+    skill: Skill
+    remaining_text: str
+    container_file_path: str
+
+
+def parse_slash_skill_reference(text: str) -> SlashSkillReference | None:
+    """Parse strict `/skill-name task` syntax, ignoring reserved control commands."""
+    match = _SLASH_SKILL_RE.match(text)
+    if not match:
+        return None
+    name = match.group(1)
+    if name in RESERVED_SLASH_SKILL_NAMES:
+        return None
+    return SlashSkillReference(
+        name=name,
+        remaining_text=text[match.end() :].lstrip(),
+    )
+
+
+def resolve_slash_skill(
+    text: str,
+    skills: list[Skill],
+    *,
+    available_skills: set[str] | None = None,
+    container_base_path: str = "/mnt/skills",
+) -> ResolvedSlashSkill | None:
+    """Resolve text into an enabled, whitelisted skill activation if possible."""
+    reference = parse_slash_skill_reference(text)
+    if reference is None:
+        return None
+    if available_skills is not None and reference.name not in available_skills:
+        return None
+
+    skill = next((candidate for candidate in skills if candidate.name == reference.name and candidate.enabled), None)
+    if skill is None:
+        return None
+
+    return ResolvedSlashSkill(
+        skill=skill,
+        remaining_text=reference.remaining_text,
+        container_file_path=skill.get_container_file_path(container_base_path),
+    )

backend/packages/harness/deerflow/utils/messages.py

@@ -0,0 +1,31 @@
+from __future__ import annotations
+
+from collections.abc import Mapping
+from typing import Any
+
+ORIGINAL_USER_CONTENT_KEY = "original_user_content"
+
+
+def message_content_to_text(content: Any) -> str:
+    """Extract text from LangChain message content shapes."""
+    if isinstance(content, str):
+        return content
+    if isinstance(content, list):
+        parts: list[str] = []
+        for item in content:
+            if isinstance(item, str):
+                parts.append(item)
+            elif isinstance(item, dict):
+                text = item.get("text")
+                if isinstance(text, str):
+                    parts.append(text)
+        return "\n".join(part for part in parts if part)
+    return str(content)
+
+
+def get_original_user_content_text(content: Any, additional_kwargs: Mapping[str, Any] | None) -> str:
+    """Return pre-middleware user text when available, otherwise content text."""
+    original_content = (additional_kwargs or {}).get(ORIGINAL_USER_CONTENT_KEY)
+    if isinstance(original_content, str):
+        return original_content
+    return message_content_to_text(content)

backend/scripts/build_fixture_from_jsonl.py

@@ -36,7 +36,8 @@ def main() -> int:
     for index, turn in enumerate(turns):
         data = turn["output"].get("data", {})
         tool_calls = [tc.get("name") for tc in (data.get("tool_calls") or [])]
-        print(f"  turn {index}: hash={turn['input_hash'][:12]} tool_calls={tool_calls} content={str(data.get('content'))[:50]!r}")
+        caller = turn.get("caller", "legacy")
+        print(f"  turn {index}: caller={caller} hash={turn['input_hash'][:12]} tool_calls={tool_calls} content={str(data.get('content'))[:50]!r}")
     return 0
 
 

backend/scripts/record_gateway.py

@@ -28,27 +28,45 @@ sys.path.insert(0, str(_BACKEND / "tests"))
 def _install_capture(out_path: Path) -> None:
     from langchain_core.callbacks import BaseCallbackHandler
     from langchain_core.messages import messages_to_dict
-    from replay_provider import hash_messages
+    from replay_provider import caller_identity, hash_messages, hash_replay_input
 
     import deerflow.models.factory as factory_mod
 
     class Capture(BaseCallbackHandler):
         def __init__(self) -> None:
-            self.inputs: dict[str, list] = {}
+            self.inputs: dict[str, tuple[list, str]] = {}
 
-        def on_chat_model_start(self, serialized, messages, *, run_id=None, **kwargs):  # noqa: ANN001
-            self.inputs[str(run_id)] = messages[0] if messages else []
+        def on_chat_model_start(  # noqa: ANN001
+            self,
+            serialized,
+            messages,
+            *,
+            run_id=None,
+            tags=None,
+            name=None,
+            **kwargs,
+        ):
+            self.inputs[str(run_id)] = (
+                messages[0] if messages else [],
+                caller_identity(name=name, tags=tags),
+            )
 
         def on_llm_end(self, response, *, run_id=None, **kwargs):  # noqa: ANN001
-            inp = self.inputs.pop(str(run_id), None)
-            if inp is None:
+            captured = self.inputs.pop(str(run_id), None)
+            if captured is None:
                 return
+            inp, caller = captured
             for batch in response.generations:
                 for gen in batch:
                     message = getattr(gen, "message", None)
                     if message is None:
                         continue
-                    record = {"input_hash": hash_messages(inp), "output": messages_to_dict([message])[0]}
+                    record = {
+                        "caller": caller,
+                        "conversation_hash": hash_messages(inp),
+                        "input_hash": hash_replay_input(inp, caller=caller),
+                        "output": messages_to_dict([message])[0],
+                    }
                     with open(out_path, "a", encoding="utf-8") as handle:
                         handle.write(json.dumps(record, ensure_ascii=False) + "\n")
                         handle.flush()

backend/sitecustomize.py

@@ -0,0 +1,26 @@
+"""Process-wide Python startup customizations for backend entrypoints.
+
+When ``backend/`` is on ``sys.path``, Python imports this module during
+interpreter startup. Keep changes here suitable for all gateway, script,
+migration, and test entrypoints that run in that environment.
+"""
+
+from __future__ import annotations
+
+import asyncio
+import sys
+
+
+def _configure_windows_event_loop_policy() -> None:
+    if sys.platform != "win32":
+        return
+
+    selector_policy = getattr(asyncio, "WindowsSelectorEventLoopPolicy", None)
+    if selector_policy is None:
+        return
+
+    if not isinstance(asyncio.get_event_loop_policy(), selector_policy):
+        asyncio.set_event_loop_policy(selector_policy())
+
+
+_configure_windows_event_loop_policy()

backend/tests/_replay_fixture.py

@@ -32,7 +32,8 @@ REPLAY_MODEL_BLOCK = """\
   - name: scenario-model
     display_name: Scenario Model
     use: replay_provider:ReplayChatModel
-    model: replay"""
+    model: replay
+    supports_thinking: true"""
 
 
 def real_model_block(model: str) -> str:

backend/tests/blocking_io/test_agents_router.py

@@ -0,0 +1,64 @@
+"""Regression anchors: the custom-agent router must not block the event loop.
+
+``app.gateway.routers.agents.create_agent_endpoint`` and ``delete_agent`` are
+async route handlers that resolve the agent directory (``Paths.base_dir`` calls
+``Path.resolve``), probe it (``Path.exists``), and create/remove it (``mkdir``,
+config/SOUL writes, ``shutil.rmtree``) — all blocking IO. Both offload that work
+via ``asyncio.to_thread``; if any of it regresses back onto the event loop, the
+strict Blockbuster gate raises ``BlockingError`` and these tests fail.
+
+Imports live at module scope so the one-time FastAPI app construction (which
+reads files while building OpenAPI schemas) happens at collection time, not on
+the event loop under test. Test-side path resolution is itself offloaded with
+``asyncio.to_thread`` (matching ``test_uploads_middleware``) so only the
+handlers' own filesystem access is exercised on the loop.
+"""
+
+from __future__ import annotations
+
+import asyncio
+from pathlib import Path
+
+import pytest
+
+from app.gateway.routers.agents import AgentCreateRequest, create_agent_endpoint, delete_agent
+from deerflow.config.agents_api_config import load_agents_api_config_from_dict
+from deerflow.config.paths import get_paths
+from deerflow.runtime.user_context import get_effective_user_id
+
+pytestmark = pytest.mark.asyncio
+
+
+async def test_create_agent_does_not_block_event_loop(tmp_path: Path, monkeypatch) -> None:
+    monkeypatch.setenv("DEER_FLOW_HOME", str(tmp_path))
+    monkeypatch.setattr("deerflow.config.paths._paths", None)
+    load_agents_api_config_from_dict({"enabled": True})
+    try:
+        response = await create_agent_endpoint(AgentCreateRequest(name="loop-make-agent", soul="You are a test agent."))
+        assert response is not None
+
+        user_id = get_effective_user_id()
+        # test-side check (resolution offloaded; not exercised on the loop)
+        agent_dir = await asyncio.to_thread(get_paths().user_agent_dir, user_id, "loop-make-agent")
+        assert await asyncio.to_thread((agent_dir / "config.yaml").exists)
+    finally:
+        load_agents_api_config_from_dict({})
+
+
+async def test_delete_agent_does_not_block_event_loop(tmp_path: Path, monkeypatch) -> None:
+    monkeypatch.setenv("DEER_FLOW_HOME", str(tmp_path))
+    monkeypatch.setattr("deerflow.config.paths._paths", None)
+    load_agents_api_config_from_dict({"enabled": True})
+    try:
+        user_id = get_effective_user_id()
+        user_id = get_effective_user_id()
+        # test-side seeding (resolution offloaded; not exercised on the loop)
+        agent_dir = await asyncio.to_thread(get_paths().user_agent_dir, user_id, "loop-test-agent")
+        await asyncio.to_thread(agent_dir.mkdir, parents=True, exist_ok=True)
+        await asyncio.to_thread((agent_dir / "config.yaml").write_text, "name: loop-test-agent\n", encoding="utf-8")
+
+        await delete_agent("loop-test-agent")
+
+        assert not await asyncio.to_thread(agent_dir.exists)
+    finally:
+        load_agents_api_config_from_dict({})

backend/tests/fixtures/replay/write_read_file.ultra.json

@@ -12,7 +12,9 @@
   },
   "turns": [
     {
-      "input_hash": "9c50eda6ab7e8593dabccbdeadc70a4a7bf778b2c0c3f275f1f96cf2c8ab58db",
+      "caller": "lead_agent",
+      "conversation_hash": "9c50eda6ab7e8593dabccbdeadc70a4a7bf778b2c0c3f275f1f96cf2c8ab58db",
+      "input_hash": "27aeb4c11bff2c3ebc182fe52a06556823c21928620a400c7f26be9733c31f3f",
       "output": {
         "type": "ai",
         "data": {
@@ -56,7 +58,9 @@
       }
     },
     {
-      "input_hash": "3598aeb87e221ca8f554e4d61ce6d5e8801754606fa5c95a89c38bd6cb623045",
+      "caller": "middleware:title",
+      "conversation_hash": "3598aeb87e221ca8f554e4d61ce6d5e8801754606fa5c95a89c38bd6cb623045",
+      "input_hash": "75101f9faa453b1a35deff920b1e3c1a9f0b013a7627fbbaa03436752776b953",
       "output": {
         "type": "ai",
         "data": {
@@ -89,7 +93,9 @@
       }
     },
     {
-      "input_hash": "6af134379b2a9efa01b4f63032f88211d5f38f459f8bed621eb6c65e8e05c1f9",
+      "caller": "lead_agent",
+      "conversation_hash": "6af134379b2a9efa01b4f63032f88211d5f38f459f8bed621eb6c65e8e05c1f9",
+      "input_hash": "f7468603a43d301fcc0167c2f7cd10e53137bfc584f1b3d776614b7a612ed7a6",
       "output": {
         "type": "ai",
         "data": {
@@ -132,7 +138,9 @@
       }
     },
     {
-      "input_hash": "04751c4f7b0107b78b5c97d417063883fd586f5ebcbc4acf79be6cb3c0cdaec1",
+      "caller": "lead_agent",
+      "conversation_hash": "04751c4f7b0107b78b5c97d417063883fd586f5ebcbc4acf79be6cb3c0cdaec1",
+      "input_hash": "218645dabc6926a1dbdf45dd20fba8a41e1e690cef78d7752566db3acf5a36ce",
       "output": {
         "type": "ai",
         "data": {
@@ -165,7 +173,9 @@
       }
     },
     {
-      "input_hash": "8b98ebdbb53e88f000556c4753adede8eaa076ff6fd7b8a1285bfd18aee8144d",
+      "caller": "suggest_agent",
+      "conversation_hash": "8b98ebdbb53e88f000556c4753adede8eaa076ff6fd7b8a1285bfd18aee8144d",
+      "input_hash": "dcd855d389d7179a1e4bc7074fa9ba7ce697570af8947225d6bacb538f14a0cb",
       "output": {
         "type": "ai",
         "data": {
@@ -230,4 +240,4 @@
       }
     }
   ]
-}
+}

backend/tests/replay_provider.py

@@ -2,14 +2,19 @@
 record/replay e2e (mirrors open-design's ``mocks/`` golden traces).
 
 A fixture is a JSON file capturing the *real* model calls of one scenario,
-keyed by a normalized hash of the **input** each call received::
+keyed by a normalized hash of the **caller + input** each call received::
 
     {
       "scenario": "write_read_file",
       "mode": "ultra",
       "model": "gpt-5.5",
       "turns": [
-        {"input_hash": "<sha256>", "input_preview": "...", "output": <message dict>},
+        {
+          "caller": "lead_agent",
+          "conversation_hash": "<sha256>",
+          "input_hash": "<sha256>",
+          "output": <message dict>,
+        },
         ...
       ]
     }
@@ -21,8 +26,11 @@ A real run makes model calls from several callers — the lead agent's own turns
 and their count/order is not something we want a replay to depend on. Matching by
 a normalized hash of the *input messages* means each call gets back exactly the
 output that was recorded for that input, regardless of order or which middleware
-issued it. That keeps the in-graph, deterministic title call part of the
-recording; memory/summarization, by contrast, are disabled in the replay config
+issued it. The caller name (``lead_agent``, ``middleware:title``,
+``suggest_agent``, ``subagent:*``, ...) is included so two different model
+callers with the same conversation text do not compete for the same replay
+bucket. That keeps the in-graph, deterministic title call part of the recording;
+memory/summarization, by contrast, are disabled in the replay config
 (``_replay_fixture.py``) because their background, debounced timing is not
 reproducible across runs.
 
@@ -67,7 +75,7 @@ from collections import deque
 from collections.abc import Iterator
 from typing import Any
 
-from langchain_core.callbacks import CallbackManagerForLLMRun
+from langchain_core.callbacks import BaseCallbackHandler, CallbackManagerForLLMRun
 from langchain_core.language_models.chat_models import BaseChatModel
 from langchain_core.messages import AIMessage, AIMessageChunk, BaseMessage, messages_from_dict
 from langchain_core.outputs import ChatGeneration, ChatGenerationChunk, ChatResult
@@ -75,6 +83,14 @@ from langchain_core.runnables import Runnable
 from pydantic import PrivateAttr
 
 _FIXTURE_ENV = "DEERFLOW_REPLAY_FIXTURE"
+_DEFAULT_CALLER = "lead_agent"
+_CALLER_TAG_PREFIXES = ("middleware:", "subagent:")
+_CALLER_NAME_ALIASES = {
+    # TitleMiddleware uses this run_name and tags the call as middleware:title.
+    # Some execution paths do not preserve the tag down to the model callback,
+    # so keep the run_name and tag in the same replay namespace.
+    "title_agent": "middleware:title",
+}
 
 # Process-wide record of replay misses. A miss raises inside the model, but the
 # gateway's LLMErrorHandlingMiddleware swallows it into a normal assistant error
@@ -94,6 +110,30 @@ def reset_replay_misses() -> None:
     _replay_misses.clear()
 
 
+def _normalize_caller(caller: str | None) -> str:
+    value = _normalize_text(str(caller or "").strip())
+    if not value:
+        return _DEFAULT_CALLER
+    return _CALLER_NAME_ALIASES.get(value, value)
+
+
+def _caller_from_tags(tags: list[str] | None) -> str | None:
+    for tag in tags or []:
+        if isinstance(tag, str) and (tag == _DEFAULT_CALLER or tag.startswith(_CALLER_TAG_PREFIXES)):
+            return tag
+    return None
+
+
+def caller_identity(*, name: str | None = None, tags: list[str] | None = None) -> str:
+    """Stable model-caller identity shared by record and replay.
+
+    Tags win because graph middleware and subagents already use them as the
+    explicit caller marker. ``run_name`` is exposed to callbacks as ``name`` and
+    covers route-level callers such as ``suggest_agent``.
+    """
+    return _normalize_caller(_caller_from_tags(tags) or name)
+
+
 # Volatile substrings that differ between a recording run and a replay run but
 # carry no semantic weight for matching. Normalized to stable placeholders
 # before hashing so the same logical input hashes identically across processes.
@@ -172,10 +212,30 @@ def _canonical_messages(messages: list[BaseMessage]) -> str:
 
 
 def hash_messages(messages: list[BaseMessage]) -> str:
-    """Stable hash of a model call's input. Shared by recorder and replayer."""
+    """Legacy stable hash of only a model call's conversation input."""
     return hashlib.sha256(_canonical_messages(messages).encode("utf-8")).hexdigest()
 
 
+def hash_replay_input(messages: list[BaseMessage], *, caller: str | None) -> str:
+    """Stable replay key for a caller-specific model input."""
+    return hash_input_key(hash_messages(messages), caller=caller)
+
+
+def hash_input_key(conversation_hash: str, *, caller: str | None) -> str:
+    """Namespace a conversation hash by caller identity.
+
+    Keeping this as ``hash(caller + legacy_conversation_hash)`` lets existing
+    fixtures migrate without a live-model re-record: their old ``input_hash`` is
+    exactly the conversation hash.
+    """
+    payload = json.dumps(
+        {"caller": _normalize_caller(caller), "conversation_hash": conversation_hash},
+        sort_keys=True,
+        ensure_ascii=False,
+    )
+    return hashlib.sha256(payload.encode("utf-8")).hexdigest()
+
+
 def _load_fixture(fixture_path: str) -> dict[str, deque[AIMessage]]:
     with open(fixture_path, encoding="utf-8") as handle:
         payload = json.load(handle)
@@ -199,24 +259,54 @@ class ReplayChatModel(BaseChatModel):
 
     _table: dict[str, deque] = PrivateAttr(default_factory=dict)
     _fixture_path: str = PrivateAttr(default="")
+    _run_callers: dict[str, str] = PrivateAttr(default_factory=dict)
 
     def __init__(self, **kwargs: Any) -> None:
         # Ignore provider noise the factory forwards from config (model, api_key,
         # base_url, ...). Fixture path comes from the ``fixture`` kwarg or env.
         fixture_path = kwargs.pop("fixture", None) or os.environ.get(_FIXTURE_ENV)
-        super().__init__()
+        callbacks = kwargs.pop("callbacks", None)
+        super().__init__(callbacks=callbacks)
         if not fixture_path:
             raise ValueError(f"ReplayChatModel needs a fixture path via the ``fixture`` kwarg or ${_FIXTURE_ENV}")
         self._fixture_path = fixture_path
         self._table = _load_fixture(fixture_path)
+        self.callbacks = [*(self.callbacks or []), _ReplayCallerCapture(self._run_callers)]
 
     @property
     def _llm_type(self) -> str:
         return "deerflow-replay"
 
-    def _match(self, messages: list[BaseMessage]) -> AIMessage:
-        key = hash_messages(messages)
+    def _caller_from_run_manager(self, run_manager: CallbackManagerForLLMRun | None) -> str:
+        if run_manager is None:
+            if len(self._run_callers) == 1:
+                # Some async LangGraph paths fire on_chat_model_start with the
+                # caller metadata but invoke the model implementation without a
+                # run_manager. When there is only one pending start event, it is
+                # the current call; use it so record/replay share the same
+                # caller key.
+                return self._run_callers.pop(next(iter(self._run_callers)))
+            return _DEFAULT_CALLER
+        run_id = str(getattr(run_manager, "run_id", ""))
+        caller = self._run_callers.pop(run_id, None)
+        if caller:
+            return caller
+        return caller_identity(
+            name=getattr(run_manager, "run_name", None) or getattr(run_manager, "name", None),
+            tags=getattr(run_manager, "tags", None),
+        )
+
+    def _match(self, messages: list[BaseMessage], run_manager: CallbackManagerForLLMRun | None = None) -> AIMessage:
+        caller = self._caller_from_run_manager(run_manager)
+        key = hash_replay_input(messages, caller=caller)
         bucket = self._table.get(key)
+        if not bucket:
+            # Backward compatibility for fixtures recorded before caller-aware
+            # keys. New recordings write caller-aware ``input_hash`` values.
+            legacy_key = hash_messages(messages)
+            bucket = self._table.get(legacy_key)
+            if bucket:
+                key = legacy_key
         if not bucket:
             _replay_misses.append(key)
             preview = _canonical_messages(messages)
@@ -224,6 +314,7 @@ class ReplayChatModel(BaseChatModel):
                 f"replay miss: no recorded output for input hash {key} in {self._fixture_path!r}. "
                 "The replayed run diverged from the recording (graph changed, a non-deterministic tool result "
                 "altered a downstream input, or a volatile field slipped past normalization). "
+                f"Caller: {caller!r}. "
                 f"Known hashes: {sorted(self._table)}. "
                 f"Normalized input (first 800 chars): {preview[:800]!r}"
             )
@@ -236,7 +327,7 @@ class ReplayChatModel(BaseChatModel):
         run_manager: CallbackManagerForLLMRun | None = None,
         **kwargs: Any,
     ) -> ChatResult:
-        return ChatResult(generations=[ChatGeneration(message=self._match(messages))])
+        return ChatResult(generations=[ChatGeneration(message=self._match(messages, run_manager))])
 
     def _stream(
         self,
@@ -245,9 +336,16 @@ class ReplayChatModel(BaseChatModel):
         run_manager: CallbackManagerForLLMRun | None = None,
         **kwargs: Any,
     ) -> Iterator[ChatGenerationChunk]:
-        turn = self._match(messages)
+        turn = self._match(messages, run_manager)
         text = turn.content if isinstance(turn.content, str) else ""
-        chunk = ChatGenerationChunk(message=AIMessageChunk(content=turn.content, tool_calls=turn.tool_calls, additional_kwargs=turn.additional_kwargs, id=turn.id))
+        chunk = ChatGenerationChunk(
+            message=AIMessageChunk(
+                content=turn.content,
+                tool_calls=turn.tool_calls,
+                additional_kwargs=turn.additional_kwargs,
+                id=turn.id,
+            )
+        )
         if run_manager is not None and text:
             run_manager.on_llm_new_token(text, chunk=chunk)
         yield chunk
@@ -256,5 +354,31 @@ class ReplayChatModel(BaseChatModel):
         return self
 
 
+class _ReplayCallerCapture(BaseCallbackHandler):
+    def __init__(self, run_callers: dict[str, str]) -> None:
+        self._run_callers = run_callers
+
+    def on_chat_model_start(
+        self,
+        serialized: dict,
+        messages: list[list[BaseMessage]],
+        *,
+        run_id: Any = None,
+        tags: list[str] | None = None,
+        name: str | None = None,
+        **kwargs: Any,
+    ) -> None:
+        if run_id is not None:
+            self._run_callers[str(run_id)] = caller_identity(name=name, tags=tags)
+
+
 # Re-export so the recorder shares the exact hashing logic.
-__all__ = ["ReplayChatModel", "hash_messages", "replay_misses", "reset_replay_misses"]
+__all__ = [
+    "ReplayChatModel",
+    "caller_identity",
+    "hash_input_key",
+    "hash_messages",
+    "hash_replay_input",
+    "replay_misses",
+    "reset_replay_misses",
+]

backend/tests/test_app_config_reload.py

@@ -140,6 +140,57 @@ def test_app_config_defaults_empty_database_to_sqlite(tmp_path, monkeypatch):
     assert config.database.sqlite_dir == ".deer-flow/data"
 
 
+def test_app_config_coerces_commented_out_list_sections(tmp_path, monkeypatch):
+    """Commenting out every entry under a list key makes PyYAML parse it as None.
+
+    Regression for the documented ``cp config.example.yaml config.yaml`` flow
+    (issue #1444): such a config must load with empty lists instead of raising
+    ``Input should be a valid list``.
+    """
+    config_path = tmp_path / "config.yaml"
+    extensions_path = tmp_path / "extensions_config.json"
+    _write_extensions_config(extensions_path)
+    config_path.write_text(
+        yaml.safe_dump(
+            {
+                "sandbox": {"use": "deerflow.sandbox.local:LocalSandboxProvider"},
+                "models": None,
+                "tools": None,
+                "tool_groups": None,
+            }
+        ),
+        encoding="utf-8",
+    )
+    monkeypatch.setenv("DEER_FLOW_EXTENSIONS_CONFIG_PATH", str(extensions_path))
+
+    config = AppConfig.from_file(str(config_path))
+
+    assert config.models == []
+    assert config.tools == []
+    assert config.tool_groups == []
+
+
+def test_app_config_warns_when_no_models_configured(tmp_path, monkeypatch, caplog):
+    config_path = tmp_path / "config.yaml"
+    extensions_path = tmp_path / "extensions_config.json"
+    _write_extensions_config(extensions_path)
+    config_path.write_text(
+        yaml.safe_dump(
+            {
+                "sandbox": {"use": "deerflow.sandbox.local:LocalSandboxProvider"},
+                "models": None,
+            }
+        ),
+        encoding="utf-8",
+    )
+    monkeypatch.setenv("DEER_FLOW_EXTENSIONS_CONFIG_PATH", str(extensions_path))
+
+    with caplog.at_level("WARNING", logger="deerflow.config.app_config"):
+        AppConfig.from_file(str(config_path))
+
+    assert "No models are configured" in caplog.text
+
+
 def test_get_app_config_reloads_when_file_changes(tmp_path, monkeypatch):
     config_path = tmp_path / "config.yaml"
     extensions_path = tmp_path / "extensions_config.json"

backend/tests/test_auth_middleware.py

@@ -4,6 +4,7 @@ import pytest
 from starlette.testclient import TestClient
 
 from app.gateway.auth_middleware import AuthMiddleware, _is_public
+from app.gateway.csrf_middleware import CSRFMiddleware
 
 # ── _is_public unit tests ─────────────────────────────────────────────────
 
@@ -92,7 +93,9 @@ def test_unknown_api_path_is_protected():
 
 def _make_app():
     """Create a minimal FastAPI app with AuthMiddleware for testing."""
-    from fastapi import FastAPI
+    from fastapi import FastAPI, Request
+
+    from deerflow.runtime.user_context import get_effective_user_id
 
     app = FastAPI()
     app.add_middleware(AuthMiddleware)
@@ -102,8 +105,16 @@ def _make_app():
         return {"status": "ok"}
 
     @app.get("/api/v1/auth/me")
-    async def auth_me():
-        return {"id": "1", "email": "test@test.com"}
+    async def auth_me(request: Request):
+        from app.gateway.deps import get_current_user_from_request
+
+        user = await get_current_user_from_request(request)
+        return {
+            "id": str(user.id),
+            "email": user.email,
+            "system_role": user.system_role,
+            "needs_setup": user.needs_setup,
+        }
 
     @app.get("/api/v1/auth/setup-status")
     async def setup_status():
@@ -113,6 +124,29 @@ def _make_app():
     async def models_get():
         return {"models": []}
 
+    @app.get("/api/whoami")
+    async def whoami(request: Request):
+        user = request.state.user
+        return {
+            "id": str(user.id),
+            "email": getattr(user, "email", None),
+            "system_role": getattr(user, "system_role", None),
+            "context_user_id": get_effective_user_id(),
+        }
+
+    @app.get("/api/current-user-from-dep")
+    async def current_user_from_dep(request: Request):
+        from app.gateway.deps import get_current_user_from_request
+
+        user = await get_current_user_from_request(request)
+        state_user = request.state.user
+        return {
+            "id": str(user.id),
+            "state_id": str(state_user.id),
+            "auth_source": request.state.auth_source,
+            "context_user_id": get_effective_user_id(),
+        }
+
     @app.put("/api/mcp/config")
     async def mcp_put():
         return {"ok": True}
@@ -136,8 +170,24 @@ def _make_app():
     return app
 
 
+def _make_auth_csrf_app():
+    """Create a minimal app with production middleware ordering."""
+    from fastapi import FastAPI
+
+    app = FastAPI()
+    app.add_middleware(AuthMiddleware)
+    app.add_middleware(CSRFMiddleware)
+
+    @app.post("/api/threads/abc/runs/stream")
+    async def protected_mutation():
+        return {"ok": True}
+
+    return app
+
+
 @pytest.fixture
-def client():
+def client(monkeypatch):
+    monkeypatch.delenv("DEER_FLOW_AUTH_DISABLED", raising=False)
     return TestClient(_make_app())
 
 
@@ -165,6 +215,139 @@ def test_protected_path_no_cookie_returns_401(client):
     assert body["detail"]["code"] == "not_authenticated"
 
 
+def test_auth_disabled_allows_protected_path_without_cookie(monkeypatch):
+    monkeypatch.setenv("DEER_FLOW_AUTH_DISABLED", "1")
+    client = TestClient(_make_app())
+
+    res = client.get("/api/models")
+
+    assert res.status_code == 200
+    assert res.json() == {"models": []}
+
+
+def test_auth_disabled_stamps_e2e_admin_user_without_cookie(monkeypatch):
+    monkeypatch.setenv("DEER_FLOW_AUTH_DISABLED", "1")
+    client = TestClient(_make_app())
+
+    res = client.get("/api/whoami")
+
+    assert res.status_code == 200
+    assert res.json() == {
+        "id": "e2e-user",
+        "email": "e2e@test.local",
+        "system_role": "admin",
+        "context_user_id": "e2e-user",
+    }
+
+
+def test_auth_disabled_auth_me_reuses_middleware_user_without_cookie(monkeypatch):
+    monkeypatch.setenv("DEER_FLOW_AUTH_DISABLED", "1")
+    client = TestClient(_make_app())
+
+    res = client.get("/api/v1/auth/me")
+
+    assert res.status_code == 200
+    assert res.json() == {
+        "id": "e2e-user",
+        "email": "e2e@test.local",
+        "system_role": "admin",
+        "needs_setup": False,
+    }
+
+
+def test_auth_disabled_does_not_clobber_valid_session_cookie(monkeypatch):
+    from types import SimpleNamespace
+
+    async def fake_current_user(request):
+        return SimpleNamespace(
+            id="session-user",
+            email="session@test.local",
+            system_role="user",
+            needs_setup=False,
+        )
+
+    monkeypatch.setenv("DEER_FLOW_AUTH_DISABLED", "1")
+    monkeypatch.setattr("app.gateway.deps.get_current_user_from_request", fake_current_user)
+    client = TestClient(_make_app())
+
+    res = client.get("/api/whoami", cookies={"access_token": "valid-session"})
+
+    assert res.status_code == 200
+    assert res.json() == {
+        "id": "session-user",
+        "email": "session@test.local",
+        "system_role": "user",
+        "context_user_id": "session-user",
+    }
+
+
+def test_auth_disabled_does_not_clobber_internal_auth_identity(monkeypatch):
+    from app.gateway.internal_auth import create_internal_auth_headers
+    from deerflow.runtime.user_context import DEFAULT_USER_ID
+
+    monkeypatch.setenv("DEER_FLOW_AUTH_DISABLED", "1")
+    client = TestClient(_make_app())
+
+    res = client.get(
+        "/api/current-user-from-dep",
+        headers=create_internal_auth_headers(),
+    )
+
+    assert res.status_code == 200
+    assert res.json() == {
+        "id": DEFAULT_USER_ID,
+        "state_id": DEFAULT_USER_ID,
+        "auth_source": "internal",
+        "context_user_id": DEFAULT_USER_ID,
+    }
+
+
+def test_auth_disabled_skips_csrf_for_state_changing_requests(monkeypatch):
+    monkeypatch.setenv("DEER_FLOW_AUTH_DISABLED", "1")
+    client = TestClient(_make_auth_csrf_app())
+
+    res = client.post("/api/threads/abc/runs/stream")
+
+    assert res.status_code == 200
+    assert res.json() == {"ok": True}
+
+
+def test_auth_disabled_is_ignored_in_explicit_production_env(monkeypatch):
+    monkeypatch.setenv("DEER_FLOW_AUTH_DISABLED", "1")
+    monkeypatch.setenv("DEER_FLOW_ENV", "production")
+    client = TestClient(_make_app())
+
+    res = client.get("/api/models")
+
+    assert res.status_code == 401
+
+
+def test_auth_disabled_startup_warning_when_effective(monkeypatch, caplog):
+    from app.gateway.auth_disabled import warn_if_auth_disabled_enabled
+
+    monkeypatch.setenv("DEER_FLOW_AUTH_DISABLED", "1")
+    monkeypatch.delenv("DEER_FLOW_ENV", raising=False)
+    monkeypatch.delenv("ENVIRONMENT", raising=False)
+
+    with caplog.at_level("WARNING", logger="app.gateway.auth_disabled"):
+        warn_if_auth_disabled_enabled()
+
+    assert "authentication is bypassed" in caplog.text
+    assert "e2e-user" in caplog.text
+
+
+def test_auth_disabled_startup_warning_suppressed_in_explicit_production_env(monkeypatch, caplog):
+    from app.gateway.auth_disabled import warn_if_auth_disabled_enabled
+
+    monkeypatch.setenv("DEER_FLOW_AUTH_DISABLED", "1")
+    monkeypatch.setenv("ENVIRONMENT", "production")
+
+    with caplog.at_level("WARNING", logger="app.gateway.auth_disabled"):
+        warn_if_auth_disabled_enabled()
+
+    assert "authentication is bypassed" not in caplog.text
+
+
 def test_protected_path_with_junk_cookie_rejected(client):
     """Junk cookie → 401. Middleware strictly validates the JWT now
     (AUTH_TEST_PLAN test 7.5.8); it no longer silently passes bad

backend/tests/test_channels.py

@@ -21,6 +21,42 @@ from app.channels.message_bus import (
     ResolvedAttachment,
 )
 from app.channels.store import ChannelStore
+from deerflow.skills.types import Skill, SkillCategory
+from deerflow.utils.messages import ORIGINAL_USER_CONTENT_KEY
+
+
+def test_known_channel_command_detection_only_matches_control_commands():
+    from app.channels.commands import is_known_channel_command
+
+    assert is_known_channel_command("/new")
+    assert is_known_channel_command("/HELP now")
+    assert not is_known_channel_command("/mnt/user-data/uploads/report.pdf")
+    assert not is_known_channel_command("/data-analysis analyze uploads/foo.csv")
+    assert not is_known_channel_command(" /new")
+
+
+def _make_channel_skill(tmp_path: Path, name: str, *, enabled: bool = True) -> Skill:
+    skill_dir = tmp_path / name
+    skill_dir.mkdir(parents=True, exist_ok=True)
+    skill_file = skill_dir / "SKILL.md"
+    skill_file.write_text(f"# {name}\n", encoding="utf-8")
+    return Skill(
+        name=name,
+        description=f"Description for {name}",
+        license="MIT",
+        skill_dir=skill_dir,
+        skill_file=skill_file,
+        relative_path=Path(name),
+        category=SkillCategory.CUSTOM,
+        enabled=enabled,
+    )
+
+
+def _make_channel_skill_storage(skills: list[Skill]):
+    return SimpleNamespace(
+        load_skills=lambda *, enabled_only: [skill for skill in skills if skill.enabled] if enabled_only else skills,
+        get_container_root=lambda: "/mnt/skills",
+    )
 
 
 def _run(coro):
@@ -1345,6 +1381,496 @@ class TestChannelManager:
 
         _run(go())
 
+    def test_handle_command_blank_text_is_reported_without_running_agent(self):
+        from app.channels.manager import ChannelManager
+
+        async def go():
+            bus = MessageBus()
+            store = ChannelStore(path=Path(tempfile.mkdtemp()) / "store.json")
+            manager = ChannelManager(bus=bus, store=store)
+
+            mock_client = _make_mock_langgraph_client()
+            manager._client = mock_client
+
+            outbound_received = []
+
+            async def capture_outbound(msg):
+                outbound_received.append(msg)
+
+            bus.subscribe_outbound(capture_outbound)
+            await manager.start()
+
+            inbound = InboundMessage(
+                channel_name="test",
+                chat_id="chat1",
+                user_id="user1",
+                text="   ",
+                msg_type=InboundMessageType.COMMAND,
+            )
+            await bus.publish_inbound(inbound)
+            await _wait_for(lambda: len(outbound_received) >= 1)
+            await manager.stop()
+
+            mock_client.runs.wait.assert_not_called()
+            assert outbound_received[0].text.startswith("Unknown command.")
+
+        _run(go())
+
+    def test_handle_command_rejects_multi_slash_control_command(self):
+        from app.channels.manager import ChannelManager
+
+        async def go():
+            bus = MessageBus()
+            store = ChannelStore(path=Path(tempfile.mkdtemp()) / "store.json")
+            manager = ChannelManager(bus=bus, store=store)
+
+            mock_client = _make_mock_langgraph_client()
+            manager._client = mock_client
+
+            outbound_received = []
+
+            async def capture_outbound(msg):
+                outbound_received.append(msg)
+
+            bus.subscribe_outbound(capture_outbound)
+            await manager.start()
+
+            inbound = InboundMessage(
+                channel_name="test",
+                chat_id="chat1",
+                user_id="user1",
+                text="//help",
+                msg_type=InboundMessageType.COMMAND,
+            )
+            await bus.publish_inbound(inbound)
+            await _wait_for(lambda: len(outbound_received) >= 1)
+            await manager.stop()
+
+            mock_client.runs.wait.assert_not_called()
+            assert outbound_received[0].text.startswith("Unknown command: //help.")
+
+        _run(go())
+
+    def test_handle_command_requires_control_command_at_start(self):
+        from app.channels.manager import ChannelManager
+
+        async def go():
+            bus = MessageBus()
+            store = ChannelStore(path=Path(tempfile.mkdtemp()) / "store.json")
+            manager = ChannelManager(bus=bus, store=store)
+
+            mock_client = _make_mock_langgraph_client(thread_id="new-thread-456")
+            manager._client = mock_client
+
+            outbound_received = []
+
+            async def capture_outbound(msg):
+                outbound_received.append(msg)
+
+            bus.subscribe_outbound(capture_outbound)
+            await manager.start()
+
+            inbound = InboundMessage(
+                channel_name="test",
+                chat_id="chat1",
+                user_id="user1",
+                text=" /new",
+                msg_type=InboundMessageType.COMMAND,
+            )
+            await bus.publish_inbound(inbound)
+            await _wait_for(lambda: len(outbound_received) >= 1)
+            await manager.stop()
+
+            mock_client.threads.create.assert_not_called()
+            assert store.get_thread_id("test", "chat1") is None
+            assert outbound_received[0].text.startswith("Unknown command: /new.")
+
+        _run(go())
+
+    def test_handle_command_outbound_thread_id_uses_topic_thread(self):
+        from app.channels.manager import ChannelManager
+
+        async def go():
+            bus = MessageBus()
+            store = ChannelStore(path=Path(tempfile.mkdtemp()) / "store.json")
+            manager = ChannelManager(bus=bus, store=store)
+            store.set_thread_id("test", "chat1", "base-thread")
+            store.set_thread_id("test", "chat1", "topic-thread", topic_id="topic-1")
+
+            outbound_received = []
+
+            async def capture_outbound(msg):
+                outbound_received.append(msg)
+
+            bus.subscribe_outbound(capture_outbound)
+            await manager.start()
+
+            inbound = InboundMessage(
+                channel_name="test",
+                chat_id="chat1",
+                user_id="user1",
+                text="/status",
+                msg_type=InboundMessageType.COMMAND,
+                topic_id="topic-1",
+            )
+            await bus.publish_inbound(inbound)
+            await _wait_for(lambda: len(outbound_received) >= 1)
+            await manager.stop()
+
+            assert outbound_received[0].text == "Active thread: topic-thread"
+            assert outbound_received[0].thread_id == "topic-thread"
+
+        _run(go())
+
+    def test_handle_command_slash_skill_routes_to_chat(self, tmp_path):
+        from app.channels.manager import ChannelManager
+
+        async def go():
+            bus = MessageBus()
+            store = ChannelStore(path=Path(tempfile.mkdtemp()) / "store.json")
+            manager = ChannelManager(bus=bus, store=store)
+            manager._skill_storage = _make_channel_skill_storage([_make_channel_skill(tmp_path, "data-analysis")])
+
+            mock_client = _make_mock_langgraph_client()
+            manager._client = mock_client
+
+            outbound_received = []
+
+            async def capture_outbound(msg):
+                outbound_received.append(msg)
+
+            bus.subscribe_outbound(capture_outbound)
+            await manager.start()
+
+            inbound = InboundMessage(
+                channel_name="test",
+                chat_id="chat1",
+                user_id="user1",
+                text="/data-analysis analyze uploads/foo.csv",
+                msg_type=InboundMessageType.COMMAND,
+            )
+            await bus.publish_inbound(inbound)
+            await _wait_for(lambda: len(outbound_received) >= 1)
+            await manager.stop()
+
+            mock_client.runs.wait.assert_called_once()
+            call_args = mock_client.runs.wait.call_args
+            assert call_args[1]["input"]["messages"][0]["content"] == "/data-analysis analyze uploads/foo.csv"
+            assert outbound_received[0].text == "Hello from agent!"
+
+        _run(go())
+
+    def test_handle_command_slash_skill_with_attachment_preserves_original_content(self, monkeypatch, tmp_path):
+        from app.channels.manager import ChannelManager
+
+        async def fake_ingest(thread_id, msg):
+            return [
+                {
+                    "filename": "report.pdf",
+                    "size": 12,
+                    "path": "/mnt/user-data/uploads/report.pdf",
+                    "is_image": False,
+                }
+            ]
+
+        monkeypatch.setattr("app.channels.manager._ingest_inbound_files", fake_ingest)
+
+        async def go():
+            bus = MessageBus()
+            store = ChannelStore(path=Path(tempfile.mkdtemp()) / "store.json")
+            manager = ChannelManager(bus=bus, store=store)
+            manager._skill_storage = _make_channel_skill_storage([_make_channel_skill(tmp_path, "data-analysis")])
+
+            mock_client = _make_mock_langgraph_client()
+            manager._client = mock_client
+
+            outbound_received = []
+
+            async def capture_outbound(msg):
+                outbound_received.append(msg)
+
+            bus.subscribe_outbound(capture_outbound)
+            await manager.start()
+
+            original_text = "/data-analysis analyze report.pdf"
+            inbound = InboundMessage(
+                channel_name="test",
+                chat_id="chat1",
+                user_id="user1",
+                text=original_text,
+                files=[{"filename": "report.pdf"}],
+                msg_type=InboundMessageType.COMMAND,
+            )
+            await bus.publish_inbound(inbound)
+            await _wait_for(lambda: len(outbound_received) >= 1)
+            await manager.stop()
+
+            mock_client.runs.wait.assert_called_once()
+            human_message = mock_client.runs.wait.call_args[1]["input"]["messages"][0]
+            assert human_message["content"].startswith("<uploaded_files>")
+            assert original_text in human_message["content"]
+            assert human_message["additional_kwargs"][ORIGINAL_USER_CONTENT_KEY] == original_text
+            assert outbound_received[0].text == "Hello from agent!"
+
+        _run(go())
+
+    def test_streaming_slash_skill_with_attachment_preserves_original_content(self, monkeypatch, tmp_path):
+        from app.channels.manager import ChannelManager
+
+        async def fake_ingest(thread_id, msg):
+            return [
+                {
+                    "filename": "report.pdf",
+                    "size": 12,
+                    "path": "/mnt/user-data/uploads/report.pdf",
+                    "is_image": False,
+                }
+            ]
+
+        monkeypatch.setattr("app.channels.manager._ingest_inbound_files", fake_ingest)
+
+        async def go():
+            bus = MessageBus()
+            store = ChannelStore(path=Path(tempfile.mkdtemp()) / "store.json")
+            manager = ChannelManager(bus=bus, store=store)
+            manager._skill_storage = _make_channel_skill_storage([_make_channel_skill(tmp_path, "data-analysis")])
+
+            mock_client = _make_mock_langgraph_client()
+            mock_client.runs.stream = MagicMock(
+                return_value=_make_async_iterator(
+                    [
+                        _make_stream_part(
+                            "values",
+                            {"messages": [{"type": "ai", "content": "streamed response"}]},
+                        )
+                    ]
+                )
+            )
+            manager._client = mock_client
+
+            outbound_received = []
+
+            async def capture_outbound(msg):
+                outbound_received.append(msg)
+
+            bus.subscribe_outbound(capture_outbound)
+            await manager.start()
+
+            original_text = "/data-analysis analyze report.pdf"
+            inbound = InboundMessage(
+                channel_name="feishu",
+                chat_id="chat1",
+                user_id="user1",
+                text=original_text,
+                files=[{"filename": "report.pdf"}],
+                msg_type=InboundMessageType.COMMAND,
+            )
+            await bus.publish_inbound(inbound)
+            await _wait_for(lambda: any(message.is_final for message in outbound_received))
+            await manager.stop()
+
+            mock_client.runs.stream.assert_called_once()
+            human_message = mock_client.runs.stream.call_args[1]["input"]["messages"][0]
+            assert human_message["content"].startswith("<uploaded_files>")
+            assert original_text in human_message["content"]
+            assert human_message["additional_kwargs"][ORIGINAL_USER_CONTENT_KEY] == original_text
+
+        _run(go())
+
+    def test_handle_command_slash_skill_requires_command_at_start(self, tmp_path):
+        from app.channels.manager import ChannelManager
+
+        async def go():
+            bus = MessageBus()
+            store = ChannelStore(path=Path(tempfile.mkdtemp()) / "store.json")
+            manager = ChannelManager(bus=bus, store=store)
+            manager._skill_storage = _make_channel_skill_storage([_make_channel_skill(tmp_path, "data-analysis")])
+
+            mock_client = _make_mock_langgraph_client()
+            manager._client = mock_client
+
+            outbound_received = []
+
+            async def capture_outbound(msg):
+                outbound_received.append(msg)
+
+            bus.subscribe_outbound(capture_outbound)
+            await manager.start()
+
+            inbound = InboundMessage(
+                channel_name="test",
+                chat_id="chat1",
+                user_id="user1",
+                text="  /data-analysis analyze uploads/foo.csv",
+                msg_type=InboundMessageType.COMMAND,
+            )
+            await bus.publish_inbound(inbound)
+            await _wait_for(lambda: len(outbound_received) >= 1)
+            await manager.stop()
+
+            mock_client.runs.wait.assert_not_called()
+            assert outbound_received[0].text.startswith("Unknown command: /data-analysis.")
+
+        _run(go())
+
+    def test_handle_command_slash_skill_respects_custom_agent_skill_whitelist(self, monkeypatch, tmp_path):
+        from app.channels.manager import ChannelManager
+
+        monkeypatch.setattr("app.channels.manager.load_agent_config", lambda name: SimpleNamespace(skills=["frontend-design"]))
+
+        async def go():
+            bus = MessageBus()
+            store = ChannelStore(path=Path(tempfile.mkdtemp()) / "store.json")
+            manager = ChannelManager(
+                bus=bus,
+                store=store,
+                default_session={"assistant_id": "analyst-agent"},
+            )
+            manager._skill_storage = _make_channel_skill_storage([_make_channel_skill(tmp_path, "data-analysis")])
+
+            mock_client = _make_mock_langgraph_client()
+            manager._client = mock_client
+
+            outbound_received = []
+
+            async def capture_outbound(msg):
+                outbound_received.append(msg)
+
+            bus.subscribe_outbound(capture_outbound)
+            await manager.start()
+
+            inbound = InboundMessage(
+                channel_name="test",
+                chat_id="chat1",
+                user_id="user1",
+                text="/data-analysis analyze uploads/foo.csv",
+                msg_type=InboundMessageType.COMMAND,
+            )
+            await bus.publish_inbound(inbound)
+            await _wait_for(lambda: len(outbound_received) >= 1)
+            await manager.stop()
+
+            mock_client.runs.wait.assert_not_called()
+            assert outbound_received[0].text == "Skill `/data-analysis` is not available for this agent."
+
+        _run(go())
+
+    def test_handle_command_slash_skill_reports_disabled_skill(self, tmp_path):
+        from app.channels.manager import ChannelManager
+
+        async def go():
+            bus = MessageBus()
+            store = ChannelStore(path=Path(tempfile.mkdtemp()) / "store.json")
+            manager = ChannelManager(bus=bus, store=store)
+            manager._skill_storage = _make_channel_skill_storage([_make_channel_skill(tmp_path, "data-analysis", enabled=False)])
+
+            mock_client = _make_mock_langgraph_client()
+            manager._client = mock_client
+
+            outbound_received = []
+
+            async def capture_outbound(msg):
+                outbound_received.append(msg)
+
+            bus.subscribe_outbound(capture_outbound)
+            await manager.start()
+
+            inbound = InboundMessage(
+                channel_name="test",
+                chat_id="chat1",
+                user_id="user1",
+                text="/data-analysis analyze uploads/foo.csv",
+                msg_type=InboundMessageType.COMMAND,
+            )
+            await bus.publish_inbound(inbound)
+            await _wait_for(lambda: len(outbound_received) >= 1)
+            await manager.stop()
+
+            mock_client.runs.wait.assert_not_called()
+            assert outbound_received[0].text == "Skill `/data-analysis` is installed but disabled. Enable it before using slash activation."
+
+        _run(go())
+
+    def test_handle_command_uninstalled_slash_skill_stays_unknown_command(self, tmp_path):
+        from app.channels.manager import ChannelManager
+
+        async def go():
+            bus = MessageBus()
+            store = ChannelStore(path=Path(tempfile.mkdtemp()) / "store.json")
+            manager = ChannelManager(bus=bus, store=store)
+            manager._skill_storage = _make_channel_skill_storage([_make_channel_skill(tmp_path, "frontend-design")])
+
+            mock_client = _make_mock_langgraph_client()
+            manager._client = mock_client
+
+            outbound_received = []
+
+            async def capture_outbound(msg):
+                outbound_received.append(msg)
+
+            bus.subscribe_outbound(capture_outbound)
+            await manager.start()
+
+            inbound = InboundMessage(
+                channel_name="test",
+                chat_id="chat1",
+                user_id="user1",
+                text="/data-analysis analyze uploads/foo.csv",
+                msg_type=InboundMessageType.COMMAND,
+            )
+            await bus.publish_inbound(inbound)
+            await _wait_for(lambda: len(outbound_received) >= 1)
+            await manager.stop()
+
+            mock_client.runs.wait.assert_not_called()
+            assert outbound_received[0].text.startswith("Unknown command: /data-analysis.")
+
+        _run(go())
+
+    def test_handle_command_slash_skill_resolution_error_is_reported(self, monkeypatch):
+        from app.channels.manager import ChannelManager, SlashSkillCommandResolutionError
+
+        def fail_resolution(text, available_skills=None, storage=None):
+            raise SlashSkillCommandResolutionError("Failed to resolve slash skill command. Please check the skill configuration.")
+
+        monkeypatch.setattr("app.channels.manager._resolve_slash_skill_command", fail_resolution)
+
+        async def go():
+            bus = MessageBus()
+            store = ChannelStore(path=Path(tempfile.mkdtemp()) / "store.json")
+            manager = ChannelManager(bus=bus, store=store)
+            store.set_thread_id("test", "chat1", "base-thread")
+            store.set_thread_id("test", "chat1", "topic-thread", topic_id="topic-1")
+
+            mock_client = _make_mock_langgraph_client()
+            manager._client = mock_client
+
+            outbound_received = []
+
+            async def capture_outbound(msg):
+                outbound_received.append(msg)
+
+            bus.subscribe_outbound(capture_outbound)
+            await manager.start()
+
+            inbound = InboundMessage(
+                channel_name="test",
+                chat_id="chat1",
+                user_id="user1",
+                text="/data-analysis analyze uploads/foo.csv",
+                msg_type=InboundMessageType.COMMAND,
+                topic_id="topic-1",
+            )
+            await bus.publish_inbound(inbound)
+            await _wait_for(lambda: len(outbound_received) >= 1)
+            await manager.stop()
+
+            mock_client.runs.wait.assert_not_called()
+            assert outbound_received[0].text == "Failed to resolve slash skill command. Please check the skill configuration."
+            assert outbound_received[0].thread_id == "topic-thread"
+
+        _run(go())
+
     def test_handle_command_new(self):
         from app.channels.manager import ChannelManager
 
@@ -2541,6 +3067,36 @@ class TestWeComChannel:
 
         _run(go())
 
+    def test_publish_ws_inbound_treats_slash_prefixed_paths_as_chat(self, monkeypatch):
+        from app.channels.wecom import WeComChannel
+
+        async def go():
+            bus = MessageBus()
+            bus.publish_inbound = AsyncMock()
+            channel = WeComChannel(bus, config={})
+            channel._ws_client = SimpleNamespace(reply_stream=AsyncMock())
+
+            monkeypatch.setitem(
+                __import__("sys").modules,
+                "aibot",
+                SimpleNamespace(generate_req_id=lambda prefix: "stream-1"),
+            )
+
+            frame = {
+                "body": {
+                    "msgid": "msg-1",
+                    "from": {"userid": "user-1"},
+                }
+            }
+
+            await channel._publish_ws_inbound(frame, "/mnt/user-data/uploads/report.pdf")
+
+            inbound = bus.publish_inbound.await_args.args[0]
+            assert inbound.text == "/mnt/user-data/uploads/report.pdf"
+            assert inbound.msg_type == InboundMessageType.CHAT
+
+        _run(go())
+
     def test_on_outbound_sends_attachment_before_clearing_context(self, tmp_path):
         from app.channels.wecom import WeComChannel
 
@@ -2976,6 +3532,219 @@ class TestSlackAllowedUsers:
         assert inbound.chat_id == "C123"
         assert inbound.text == "hello from slack"
 
+    def test_app_mention_strips_leading_bot_mention_before_command_detection(self):
+        from app.channels.slack import SlackChannel
+
+        bus = MessageBus()
+        bus.publish_inbound = AsyncMock()
+        channel = SlackChannel(bus=bus, config={"bot_user_id": "UBOT"})
+        channel._loop = MagicMock()
+        channel._loop.is_running.return_value = True
+        channel._add_reaction = MagicMock()
+        channel._send_running_reply = MagicMock()
+
+        event = {
+            "type": "app_mention",
+            "user": "U123456",
+            "text": "<@UBOT> /help",
+            "channel": "C123",
+            "ts": "1710000000.000100",
+        }
+
+        with patch(
+            "app.channels.slack.asyncio.run_coroutine_threadsafe",
+            side_effect=self._submit_coro,
+        ):
+            channel._handle_message_event(event)
+
+        inbound = bus.publish_inbound.call_args.args[0]
+        assert inbound.text == "/help"
+        assert inbound.msg_type == InboundMessageType.COMMAND
+
+    def test_app_mention_strips_labelled_leading_bot_mention(self):
+        from app.channels.slack import SlackChannel
+
+        bus = MessageBus()
+        bus.publish_inbound = AsyncMock()
+        channel = SlackChannel(bus=bus, config={"bot_user_id": "UBOT"})
+        channel._loop = MagicMock()
+        channel._loop.is_running.return_value = True
+        channel._add_reaction = MagicMock()
+        channel._send_running_reply = MagicMock()
+
+        event = {
+            "type": "app_mention",
+            "user": "U123456",
+            "text": "<@UBOT|deerflow> /help",
+            "channel": "C123",
+            "ts": "1710000000.000100",
+        }
+
+        with patch(
+            "app.channels.slack.asyncio.run_coroutine_threadsafe",
+            side_effect=self._submit_coro,
+        ):
+            channel._handle_message_event(event)
+
+        inbound = bus.publish_inbound.call_args.args[0]
+        assert inbound.text == "/help"
+        assert inbound.msg_type == InboundMessageType.COMMAND
+
+    def test_app_mention_strips_leading_bot_mention_before_slash_skill(self):
+        from app.channels.slack import SlackChannel
+
+        bus = MessageBus()
+        bus.publish_inbound = AsyncMock()
+        channel = SlackChannel(bus=bus, config={"bot_user_id": "UBOT"})
+        channel._loop = MagicMock()
+        channel._loop.is_running.return_value = True
+        channel._add_reaction = MagicMock()
+        channel._send_running_reply = MagicMock()
+
+        event = {
+            "type": "app_mention",
+            "user": "U123456",
+            "text": "<@UBOT> /data-analysis analyze uploads/foo.csv",
+            "channel": "C123",
+            "ts": "1710000000.000100",
+        }
+
+        with patch(
+            "app.channels.slack.asyncio.run_coroutine_threadsafe",
+            side_effect=self._submit_coro,
+        ):
+            channel._handle_message_event(event)
+
+        inbound = bus.publish_inbound.call_args.args[0]
+        assert inbound.text == "/data-analysis analyze uploads/foo.csv"
+        assert inbound.msg_type == InboundMessageType.CHAT
+
+    def test_app_mention_preserves_following_user_mention(self):
+        from app.channels.slack import SlackChannel
+
+        bus = MessageBus()
+        bus.publish_inbound = AsyncMock()
+        channel = SlackChannel(bus=bus, config={"bot_user_id": "UBOT"})
+        channel._loop = MagicMock()
+        channel._loop.is_running.return_value = True
+        channel._add_reaction = MagicMock()
+        channel._send_running_reply = MagicMock()
+
+        event = {
+            "type": "app_mention",
+            "user": "U123456",
+            "text": "<@UBOT> <@UASSIGNEE> please review this",
+            "channel": "C123",
+            "ts": "1710000000.000100",
+        }
+
+        with patch(
+            "app.channels.slack.asyncio.run_coroutine_threadsafe",
+            side_effect=self._submit_coro,
+        ):
+            channel._handle_message_event(event)
+
+        inbound = bus.publish_inbound.call_args.args[0]
+        assert inbound.text == "<@UASSIGNEE> please review this"
+        assert inbound.msg_type == InboundMessageType.CHAT
+
+    def test_app_mention_preserves_leading_non_bot_mention_when_bot_id_known(self):
+        from app.channels.slack import SlackChannel
+
+        bus = MessageBus()
+        bus.publish_inbound = AsyncMock()
+        channel = SlackChannel(bus=bus, config={"bot_user_id": "UBOT"})
+        channel._loop = MagicMock()
+        channel._loop.is_running.return_value = True
+        channel._add_reaction = MagicMock()
+        channel._send_running_reply = MagicMock()
+
+        event = {
+            "type": "app_mention",
+            "user": "U123456",
+            "text": "<@UASSIGNEE> <@UBOT> please review this",
+            "channel": "C123",
+            "ts": "1710000000.000100",
+        }
+
+        with patch(
+            "app.channels.slack.asyncio.run_coroutine_threadsafe",
+            side_effect=self._submit_coro,
+        ):
+            channel._handle_message_event(event)
+
+        inbound = bus.publish_inbound.call_args.args[0]
+        assert inbound.text == "<@UASSIGNEE> <@UBOT> please review this"
+        assert inbound.msg_type == InboundMessageType.CHAT
+
+    def test_app_mention_preserves_leading_non_bot_mention_when_bot_id_unknown(self):
+        from app.channels.slack import SlackChannel
+
+        bus = MessageBus()
+        bus.publish_inbound = AsyncMock()
+        channel = SlackChannel(bus=bus, config={})
+        channel._loop = MagicMock()
+        channel._loop.is_running.return_value = True
+        channel._add_reaction = MagicMock()
+        channel._send_running_reply = MagicMock()
+
+        event = {
+            "type": "app_mention",
+            "user": "U123456",
+            "text": "<@UASSIGNEE> /help <@UBOT>",
+            "channel": "C123",
+            "ts": "1710000000.000100",
+        }
+
+        with patch(
+            "app.channels.slack.asyncio.run_coroutine_threadsafe",
+            side_effect=self._submit_coro,
+        ):
+            channel._handle_message_event(event)
+
+        inbound = bus.publish_inbound.call_args.args[0]
+        assert inbound.text == "<@UASSIGNEE> /help <@UBOT>"
+        assert inbound.msg_type == InboundMessageType.CHAT
+
+    def test_socket_event_resolves_bot_user_id_before_app_mention_command_detection(self):
+        from app.channels.slack import SlackChannel
+
+        bus = MessageBus()
+        bus.publish_inbound = AsyncMock()
+        channel = SlackChannel(bus=bus, config={})
+        channel._SocketModeResponse = lambda envelope_id: SimpleNamespace(envelope_id=envelope_id)
+        channel._loop = MagicMock()
+        channel._loop.is_running.return_value = True
+        channel._add_reaction = MagicMock()
+        channel._send_running_reply = MagicMock()
+
+        client = SimpleNamespace(send_socket_mode_response=MagicMock())
+        req = SimpleNamespace(
+            envelope_id="env-1",
+            type="events_api",
+            payload={
+                "authorizations": [{"user_id": "UBOT"}],
+                "event": {
+                    "type": "app_mention",
+                    "user": "U123456",
+                    "text": "<@UBOT> /help",
+                    "channel": "C123",
+                    "ts": "1710000000.000100",
+                },
+            },
+        )
+
+        with patch(
+            "app.channels.slack.asyncio.run_coroutine_threadsafe",
+            side_effect=self._submit_coro,
+        ):
+            channel._on_socket_event(client, req)
+
+        inbound = bus.publish_inbound.call_args.args[0]
+        assert channel._bot_user_id == "UBOT"
+        assert inbound.text == "/help"
+        assert inbound.msg_type == InboundMessageType.COMMAND
+
     def test_scalar_allowed_users_warns_and_matches_stringified_event_user_id(self, caplog):
         from app.channels.slack import SlackChannel
 
@@ -3049,6 +3818,86 @@ class TestSlackAllowedUsers:
 
 
 class TestTelegramSendRetry:
+    def test_start_registers_known_channel_commands(self, monkeypatch):
+        import sys
+        from types import ModuleType
+
+        from app.channels.commands import KNOWN_CHANNEL_COMMANDS
+        from app.channels.telegram import TelegramChannel
+
+        class FakeFilter:
+            def __init__(self, expr: str):
+                self.expr = expr
+
+            def __and__(self, other):
+                return FakeFilter(f"{self.expr}&{other.expr}")
+
+            def __invert__(self):
+                return FakeFilter(f"~{self.expr}")
+
+        class FakeApplication:
+            def __init__(self):
+                self.handlers = []
+
+            def add_handler(self, handler):
+                self.handlers.append(handler)
+
+        fake_app = FakeApplication()
+
+        class FakeApplicationBuilder:
+            def token(self, token):
+                assert token == "test-token"
+                return self
+
+            def build(self):
+                return fake_app
+
+        def fake_command_handler(command, callback):
+            return SimpleNamespace(kind="command", command=command, callback=callback)
+
+        def fake_message_handler(filter_expr, callback):
+            return SimpleNamespace(kind="message", filter_expr=filter_expr, callback=callback)
+
+        telegram_mod = ModuleType("telegram")
+        telegram_ext_mod = ModuleType("telegram.ext")
+        telegram_ext_mod.ApplicationBuilder = FakeApplicationBuilder
+        telegram_ext_mod.CommandHandler = fake_command_handler
+        telegram_ext_mod.MessageHandler = fake_message_handler
+        telegram_ext_mod.filters = SimpleNamespace(TEXT=FakeFilter("TEXT"), COMMAND=FakeFilter("COMMAND"))
+        telegram_mod.ext = telegram_ext_mod
+        monkeypatch.setitem(sys.modules, "telegram", telegram_mod)
+        monkeypatch.setitem(sys.modules, "telegram.ext", telegram_ext_mod)
+
+        class FakeThread:
+            def __init__(self, *, target, daemon):
+                self.target = target
+                self.daemon = daemon
+
+            def start(self):
+                return None
+
+            def join(self, timeout=None):
+                return None
+
+        monkeypatch.setattr("app.channels.telegram.threading.Thread", FakeThread)
+
+        async def go():
+            bus = MessageBus()
+            ch = TelegramChannel(bus=bus, config={"bot_token": "test-token"})
+
+            await ch.start()
+            try:
+                registered_commands = {handler.command for handler in fake_app.handlers if handler.kind == "command"}
+                expected_commands = {command.removeprefix("/") for command in KNOWN_CHANNEL_COMMANDS}
+                assert expected_commands <= registered_commands
+                assert "start" in registered_commands
+                message_filters = {handler.filter_expr.expr for handler in fake_app.handlers if handler.kind == "message"}
+                assert {"TEXT&COMMAND", "TEXT&~COMMAND"} <= message_filters
+            finally:
+                await ch.stop()
+
+        _run(go())
+
     def test_retries_on_failure_then_succeeds(self):
         from app.channels.telegram import TelegramChannel
 
@@ -3172,6 +4021,47 @@ class TestTelegramPrivateChatThread:
 
         _run(go())
 
+    def test_private_chat_slash_skill_text_routes_as_chat(self):
+        from app.channels.telegram import TelegramChannel
+
+        async def go():
+            bus = MessageBus()
+            ch = TelegramChannel(bus=bus, config={"bot_token": "test-token"})
+            ch._main_loop = asyncio.get_event_loop()
+
+            update = _make_telegram_update("private", message_id=12, text="/data-analysis analyze uploads/foo.csv")
+            await ch._on_text(update, None)
+
+            msg = await asyncio.wait_for(bus.get_inbound(), timeout=2)
+            assert msg.text == "/data-analysis analyze uploads/foo.csv"
+            assert msg.msg_type == InboundMessageType.CHAT
+            assert msg.topic_id is None
+
+        _run(go())
+
+    def test_slash_skill_addressed_to_telegram_bot_strips_username(self):
+        from app.channels.telegram import TelegramChannel
+
+        async def go():
+            bus = MessageBus()
+            ch = TelegramChannel(bus=bus, config={"bot_token": "test-token"})
+            ch._main_loop = asyncio.get_event_loop()
+
+            update = _make_telegram_update(
+                "group",
+                message_id=13,
+                text="/data-analysis@DeerFlowBot analyze uploads/foo.csv",
+            )
+            context = SimpleNamespace(bot=SimpleNamespace(username="DeerFlowBot"))
+            await ch._on_text(update, context)
+
+            msg = await asyncio.wait_for(bus.get_inbound(), timeout=2)
+            assert msg.text == "/data-analysis analyze uploads/foo.csv"
+            assert msg.msg_type == InboundMessageType.CHAT
+            assert msg.topic_id == "13"
+
+        _run(go())
+
     def test_private_chat_with_reply_still_uses_none_topic(self):
         from app.channels.telegram import TelegramChannel
 
@@ -3287,6 +4177,25 @@ class TestTelegramPrivateChatThread:
 
         _run(go())
 
+    def test_cmd_generic_strips_addressed_telegram_bot_username(self):
+        from app.channels.telegram import TelegramChannel
+
+        async def go():
+            bus = MessageBus()
+            ch = TelegramChannel(bus=bus, config={"bot_token": "test-token"})
+            ch._main_loop = asyncio.get_event_loop()
+
+            update = _make_telegram_update("group", message_id=33, text="/status@DeerFlowBot")
+            context = SimpleNamespace(bot=SimpleNamespace(username="DeerFlowBot"))
+            await ch._cmd_generic(update, context)
+
+            msg = await asyncio.wait_for(bus.get_inbound(), timeout=2)
+            assert msg.text == "/status"
+            assert msg.topic_id == "33"
+            assert msg.msg_type == InboundMessageType.COMMAND
+
+        _run(go())
+
 
 class TestTelegramProcessingOrder:
     """Ensure 'working on it...' is sent before inbound is published."""

backend/tests/test_dev_entrypoint.py

@@ -44,7 +44,8 @@ def test_entrypoint_excludes_runtime_state_from_uvicorn_reload():
     content = ENTRYPOINT.read_text(encoding="utf-8")
 
     assert ': "${DEER_FLOW_HOME:=/app/backend/.deer-flow}"' in content
-    assert 'mkdir -p "$DEER_FLOW_HOME" /app/backend/.deer-flow' in content
+    # sandbox must be created too, not just .deer-flow (#3459 / #3454).
+    assert 'mkdir -p "$DEER_FLOW_HOME" /app/backend/.deer-flow /app/backend/sandbox' in content
     assert "--reload-include='*.yaml .env'" not in content
     assert "--reload-include='*.yaml'" in content
     assert "--reload-include='.env'" in content

backend/tests/test_discord_channel.py

@@ -2,9 +2,13 @@
 
 from __future__ import annotations
 
+from types import SimpleNamespace
+
+import pytest
+
 from app.channels.discord import DiscordChannel
 from app.channels.manager import CHANNEL_CAPABILITIES
-from app.channels.message_bus import MessageBus
+from app.channels.message_bus import InboundMessageType, MessageBus
 from app.channels.service import _CHANNEL_REGISTRY
 
 
@@ -21,3 +25,64 @@ def test_discord_channel_init() -> None:
     channel = DiscordChannel(bus=bus, config={"bot_token": "token"})
 
     assert channel.name == "discord"
+
+
+def _make_discord_message(text: str):
+    return SimpleNamespace(
+        id=111,
+        content=text,
+        author=SimpleNamespace(id=123, bot=False, display_name="alice"),
+        guild=SimpleNamespace(id=321),
+        channel=SimpleNamespace(id=456),
+        add_reaction=lambda _emoji: None,
+    )
+
+
+@pytest.mark.asyncio
+async def test_discord_bot_mention_slash_skill_routes_as_chat() -> None:
+    bus = MessageBus()
+    channel = DiscordChannel(bus=bus, config={"bot_token": "token"})
+    captured = []
+    channel._running = True
+    channel._client = SimpleNamespace(user=SimpleNamespace(id=999, mention="<@999>"))
+    channel._discord_module = SimpleNamespace(Thread=type("FakeThread", (), {}))
+    channel._publish = captured.append
+
+    async def noop(*_args, **_kwargs):
+        return None
+
+    channel._start_typing = noop
+    channel._add_reaction = noop
+
+    await channel._on_message(_make_discord_message("<@999> /data-analysis analyze uploads/foo.csv"))
+
+    assert len(captured) == 1
+    inbound = captured[0]
+    assert inbound.text == "/data-analysis analyze uploads/foo.csv"
+    assert inbound.msg_type == InboundMessageType.CHAT
+    assert inbound.topic_id == "456"
+
+
+@pytest.mark.asyncio
+async def test_discord_bot_mention_known_command_routes_as_command() -> None:
+    bus = MessageBus()
+    channel = DiscordChannel(bus=bus, config={"bot_token": "token"})
+    captured = []
+    channel._running = True
+    channel._client = SimpleNamespace(user=SimpleNamespace(id=999, mention="<@999>"))
+    channel._discord_module = SimpleNamespace(Thread=type("FakeThread", (), {}))
+    channel._publish = captured.append
+
+    async def noop(*_args, **_kwargs):
+        return None
+
+    channel._start_typing = noop
+    channel._add_reaction = noop
+
+    await channel._on_message(_make_discord_message("<@999> /help"))
+
+    assert len(captured) == 1
+    inbound = captured[0]
+    assert inbound.text == "/help"
+    assert inbound.msg_type == InboundMessageType.COMMAND
+    assert inbound.topic_id == "456"

backend/tests/test_gateway_runtime_cleanup.py

@@ -49,7 +49,9 @@ def test_local_dev_gateway_reload_excludes_runtime_state_with_absolute_dirs():
     assert 'export DEER_FLOW_PROJECT_ROOT="$REPO_ROOT"' in serve_sh
     assert 'BACKEND_RUNTIME_HOME="$REPO_ROOT/backend/.deer-flow"' in serve_sh
     assert 'export DEER_FLOW_HOME="$BACKEND_RUNTIME_HOME"' in serve_sh
-    assert 'mkdir -p "$DEER_FLOW_HOME" "$BACKEND_RUNTIME_HOME"' in serve_sh
+    # Every absolute reload-exclude must be pre-created, including backend/sandbox
+    # (#3459 / #3454) — see test_uvicorn_reload_exclude.py for the mechanism.
+    assert 'mkdir -p "$DEER_FLOW_HOME" "$BACKEND_RUNTIME_HOME" "$REPO_ROOT/backend/sandbox"' in serve_sh
     assert "--reload-exclude='$DEER_FLOW_HOME'" in serve_sh
     assert "--reload-exclude='$BACKEND_RUNTIME_HOME'" in serve_sh
     assert "--reload-exclude='sandbox/'" not in serve_sh

backend/tests/test_langgraph_auth.py

@@ -21,6 +21,7 @@ from langgraph_sdk import Auth
 from app.gateway.auth.config import AuthConfig, set_auth_config
 from app.gateway.auth.jwt import create_access_token, decode_token
 from app.gateway.auth.models import User
+from app.gateway.auth_disabled import AUTH_DISABLED_USER_ID
 from app.gateway.langgraph_auth import add_owner_filter, authenticate
 
 # ── Helpers ───────────────────────────────────────────────────────────────
@@ -59,6 +60,14 @@ def test_no_cookie_raises_401():
     assert "Not authenticated" in str(exc.value.detail)
 
 
+def test_auth_disabled_skips_csrf_and_authenticates_e2e_user(monkeypatch):
+    monkeypatch.setenv("DEER_FLOW_AUTH_DISABLED", "1")
+
+    identity = asyncio.run(authenticate(_req(method="POST")))
+
+    assert identity == AUTH_DISABLED_USER_ID
+
+
 def test_invalid_jwt_raises_401():
     with pytest.raises(Auth.exceptions.HTTPException) as exc:
         asyncio.run(authenticate(_req({"access_token": "garbage"})))

backend/tests/test_lead_agent_skills.py

@@ -60,6 +60,17 @@ def test_get_skills_prompt_section_returns_all_when_available_skills_is_none(mon
     assert "skill2" in result
 
 
+def test_get_skills_prompt_section_includes_slash_activation_guidance(monkeypatch):
+    skills = [_make_skill("data-analysis")]
+    monkeypatch.setattr("deerflow.agents.lead_agent.prompt._get_enabled_skills", lambda: skills)
+
+    result = get_skills_prompt_section(available_skills={"data-analysis"})
+
+    assert "Explicit Slash Skill Activation" in result
+    assert "The runtime injects the activated skill content" in result
+    assert "do not call `read_file` for that SKILL.md again" in result
+
+
 def test_get_skills_prompt_section_includes_self_evolution_rules(monkeypatch):
     skills = [_make_skill("skill1")]
     monkeypatch.setattr("deerflow.agents.lead_agent.prompt._get_enabled_skills", lambda: skills)

backend/tests/test_local_sandbox_provider_mounts.py

@@ -612,6 +612,54 @@ class TestLocalSandboxProviderMounts:
 
         assert [m.container_path for m in provider._path_mappings] == ["/mnt/skills"]
 
+    def test_setup_path_mappings_logs_actionable_error_for_missing_host_path(self, tmp_path, caplog):
+        """Regression for #3244.
+
+        When ``sandbox.mounts[].host_path`` is absent from the gateway process's
+        filesystem (the typical symptom in Docker production mode: host_path is a
+        host machine path that is not bind-mounted into the gateway container),
+        the mount is still skipped — but the failure must be a hard-to-miss ERROR
+        log with explicit, actionable guidance about Docker bind mounts, not the
+        old DEBUG/WARNING that buried the silent failure.
+        """
+        skills_dir = tmp_path / "skills"
+        skills_dir.mkdir()
+        missing_host_path = tmp_path / "does-not-exist"
+
+        from deerflow.config.sandbox_config import SandboxConfig, VolumeMountConfig
+
+        sandbox_config = SandboxConfig(
+            use="deerflow.sandbox.local:LocalSandboxProvider",
+            mounts=[
+                VolumeMountConfig(host_path=str(missing_host_path), container_path="/mnt/knowledge", read_only=True),
+            ],
+        )
+        config = SimpleNamespace(
+            skills=SimpleNamespace(container_path="/mnt/skills", get_skills_path=lambda: skills_dir, use="deerflow.skills.storage.local_skill_storage:LocalSkillStorage"),
+            sandbox=sandbox_config,
+        )
+
+        with caplog.at_level("ERROR", logger="deerflow.sandbox.local.local_sandbox_provider"):
+            with patch("deerflow.config.get_app_config", return_value=config):
+                provider = LocalSandboxProvider()
+
+        # Silent-skip behaviour is preserved (no breaking change for existing deployments).
+        assert [m.container_path for m in provider._path_mappings] == ["/mnt/skills"]
+
+        # The failure must be observable at ERROR level and reference the offending paths.
+        error_records = [r for r in caplog.records if r.levelname == "ERROR"]
+        assert error_records, "expected an ERROR log when host_path is missing"
+        message = "\n".join(r.getMessage() for r in error_records)
+        assert str(missing_host_path) in message
+        assert "/mnt/knowledge" in message
+
+        # And it must include actionable Docker guidance so users don't lose hours
+        # to a silent empty-mount failure in production.
+        lowered = message.lower()
+        assert "docker" in lowered
+        assert "gateway" in lowered
+        assert "docker-compose" in lowered
+
     def test_write_file_resolves_container_paths_in_content(self, tmp_path):
         """write_file should replace container paths in file content with local paths."""
         data_dir = tmp_path / "data"

backend/tests/test_patched_stepfun.py

@@ -0,0 +1,305 @@
+"""Tests for deerflow.models.patched_stepfun.PatchedChatStepFun."""
+
+from __future__ import annotations
+
+from unittest.mock import MagicMock, patch
+
+from langchain_core.messages import AIMessage, AIMessageChunk, HumanMessage
+
+
+def _make_model(**kwargs):
+    from deerflow.models.patched_stepfun import PatchedChatStepFun
+
+    return PatchedChatStepFun(
+        model="step-3.7-flash",
+        api_key="test-key",
+        base_url="https://api.stepfun.com/v1",
+        **kwargs,
+    )
+
+
+# ---------------------------------------------------------------------------
+# Basic properties
+# ---------------------------------------------------------------------------
+
+
+def test_is_lc_serializable_returns_true():
+    from deerflow.models.patched_stepfun import PatchedChatStepFun
+
+    assert PatchedChatStepFun.is_lc_serializable() is True
+
+
+def test_lc_secrets_contains_stepfun_api_key_mapping():
+    model = _make_model()
+    assert model.lc_secrets["api_key"] == "STEPFUN_API_KEY"
+    assert model.lc_secrets["openai_api_key"] == "STEPFUN_API_KEY"
+
+
+# ---------------------------------------------------------------------------
+# _extract_reasoning helper
+# ---------------------------------------------------------------------------
+
+
+def test_extract_reasoning_from_dict_with_reasoning():
+    from deerflow.models.patched_stepfun import _extract_reasoning
+
+    assert _extract_reasoning({"reasoning": "thinking..."}) == "thinking..."
+
+
+def test_extract_reasoning_from_dict_with_reasoning_content():
+    from deerflow.models.patched_stepfun import _extract_reasoning
+
+    assert _extract_reasoning({"reasoning_content": "thinking..."}) == "thinking..."
+
+
+def test_extract_reasoning_prefers_reasoning_content_over_reasoning():
+    from deerflow.models.patched_stepfun import _extract_reasoning
+
+    result = _extract_reasoning({"reasoning_content": "deepseek", "reasoning": "native"})
+    assert result == "deepseek"
+
+
+def test_extract_reasoning_missing_returns_sentinel():
+    from deerflow.models.patched_stepfun import _MISSING, _extract_reasoning
+
+    assert _extract_reasoning({}) is _MISSING
+    assert _extract_reasoning({"reasoning": None}) is _MISSING
+
+
+# ---------------------------------------------------------------------------
+# Request payload replay (_get_request_payload)
+# ---------------------------------------------------------------------------
+
+
+def test_reasoning_content_injected_into_assistant_tool_call_message():
+    model = _make_model()
+
+    human = HumanMessage(content="Check Beijing weather.")
+    ai = AIMessage(
+        content="",
+        additional_kwargs={"reasoning_content": "I need to call the weather tool."},
+    )
+    payload_message = {
+        "role": "assistant",
+        "content": "",
+        "tool_calls": [
+            {
+                "id": "call_weather",
+                "type": "function",
+                "function": {"name": "get_weather", "arguments": '{"location":"Beijing"}'},
+            }
+        ],
+    }
+    base_payload = {
+        "messages": [
+            {"role": "user", "content": "Check Beijing weather."},
+            payload_message,
+        ]
+    }
+
+    with patch.object(type(model).__bases__[0], "_get_request_payload", return_value=base_payload):
+        with patch.object(model, "_convert_input") as mock_convert:
+            mock_convert.return_value = MagicMock(to_messages=lambda: [human, ai])
+            payload = model._get_request_payload([human, ai])
+
+    assert payload["messages"][1]["reasoning_content"] == "I need to call the weather tool."
+
+
+def test_reasoning_content_is_noop_when_missing():
+    model = _make_model()
+
+    human = HumanMessage(content="hello")
+    ai = AIMessage(content="hi", additional_kwargs={})
+    base_payload = {
+        "messages": [
+            {"role": "user", "content": "hello"},
+            {"role": "assistant", "content": "hi"},
+        ]
+    }
+
+    with patch.object(type(model).__bases__[0], "_get_request_payload", return_value=base_payload):
+        with patch.object(model, "_convert_input") as mock_convert:
+            mock_convert.return_value = MagicMock(to_messages=lambda: [human, ai])
+            payload = model._get_request_payload([human, ai])
+
+    assert "reasoning_content" not in payload["messages"][1]
+
+
+# ---------------------------------------------------------------------------
+# Streaming reasoning capture (_convert_chunk_to_generation_chunk)
+# ---------------------------------------------------------------------------
+
+
+def test_convert_chunk_captures_reasoning_field():
+    """StepFun default format: delta.reasoning."""
+    model = _make_model()
+
+    chunk = model._convert_chunk_to_generation_chunk(
+        {"choices": [{"delta": {"role": "assistant", "reasoning": "I need "}}]},
+        AIMessageChunk,
+        {},
+    )
+
+    assert chunk is not None
+    assert chunk.message.additional_kwargs["reasoning_content"] == "I need "
+
+
+def test_convert_chunk_captures_reasoning_content_field():
+    """StepFun deepseek-style format: delta.reasoning_content."""
+    model = _make_model()
+
+    chunk = model._convert_chunk_to_generation_chunk(
+        {"choices": [{"delta": {"role": "assistant", "reasoning_content": "I need "}}]},
+        AIMessageChunk,
+        {},
+    )
+
+    assert chunk is not None
+    assert chunk.message.additional_kwargs["reasoning_content"] == "I need "
+
+
+def test_convert_chunk_streams_reasoning_then_content():
+    """Full streaming flow: reasoning deltas followed by content."""
+    model = _make_model()
+
+    first = model._convert_chunk_to_generation_chunk(
+        {"choices": [{"delta": {"role": "assistant", "reasoning": "I need "}}]},
+        AIMessageChunk,
+        {},
+    )
+    second = model._convert_chunk_to_generation_chunk(
+        {"choices": [{"delta": {"reasoning": "a tool."}}]},
+        AIMessageChunk,
+        {},
+    )
+    answer = model._convert_chunk_to_generation_chunk(
+        {"choices": [{"delta": {"content": "Done."}, "finish_reason": "stop"}], "model": "step-3.7-flash"},
+        AIMessageChunk,
+        {},
+    )
+
+    assert first is not None
+    assert second is not None
+    assert answer is not None
+
+    combined = first.message + second.message + answer.message
+    assert combined.additional_kwargs["reasoning_content"] == "I need a tool."
+    assert combined.content == "Done."
+
+
+def test_convert_chunk_noop_when_no_reasoning():
+    model = _make_model()
+
+    chunk = model._convert_chunk_to_generation_chunk(
+        {"choices": [{"delta": {"content": "Hello."}, "finish_reason": "stop"}], "model": "step-3.7-flash"},
+        AIMessageChunk,
+        {},
+    )
+
+    assert chunk is not None
+    assert "reasoning_content" not in chunk.message.additional_kwargs
+
+
+# ---------------------------------------------------------------------------
+# Non-streaming reasoning capture (_create_chat_result)
+# ---------------------------------------------------------------------------
+
+
+def test_create_chat_result_extracts_reasoning_field():
+    """StepFun default format: message.reasoning."""
+    model = _make_model()
+    response = {
+        "choices": [
+            {
+                "message": {
+                    "role": "assistant",
+                    "content": "The weather is sunny.",
+                    "reasoning": "The tool returned sunny weather.",
+                },
+                "finish_reason": "stop",
+            }
+        ],
+        "model": "step-3.7-flash",
+    }
+
+    result = model._create_chat_result(response)
+    message = result.generations[0].message
+
+    assert message.content == "The weather is sunny."
+    assert message.additional_kwargs["reasoning_content"] == "The tool returned sunny weather."
+
+
+def test_create_chat_result_extracts_reasoning_content_field():
+    """StepFun deepseek-style format: message.reasoning_content."""
+    model = _make_model()
+    response = {
+        "choices": [
+            {
+                "message": {
+                    "role": "assistant",
+                    "content": "The weather is sunny.",
+                    "reasoning_content": "The tool returned sunny weather.",
+                },
+                "finish_reason": "stop",
+            }
+        ],
+        "model": "step-3.7-flash",
+    }
+
+    result = model._create_chat_result(response)
+    message = result.generations[0].message
+
+    assert message.content == "The weather is sunny."
+    assert message.additional_kwargs["reasoning_content"] == "The tool returned sunny weather."
+
+
+def test_create_chat_result_reads_reasoning_from_sdk_object():
+    """When the response is a Pydantic model, reasoning is an attribute."""
+    model = _make_model()
+
+    class FakeMessage:
+        reasoning = "Reasoning stored on the SDK message object."
+        reasoning_content = None
+        model_extra = None
+
+    class FakeChoice:
+        message = FakeMessage()
+
+    class FakeResponse:
+        choices = [FakeChoice()]
+
+        def model_dump(self, **kwargs):
+            return {
+                "choices": [
+                    {
+                        "message": {
+                            "role": "assistant",
+                            "content": "Answer.",
+                        },
+                        "finish_reason": "stop",
+                    }
+                ],
+                "model": "step-3.7-flash",
+            }
+
+    result = model._create_chat_result(FakeResponse())
+    assert result.generations[0].message.additional_kwargs["reasoning_content"] == "Reasoning stored on the SDK message object."
+
+
+def test_create_chat_result_noop_when_no_reasoning():
+    model = _make_model()
+    response = {
+        "choices": [
+            {
+                "message": {
+                    "role": "assistant",
+                    "content": "Hello!",
+                },
+                "finish_reason": "stop",
+            }
+        ],
+        "model": "step-3.7-flash",
+    }
+
+    result = model._create_chat_result(response)
+    assert "reasoning_content" not in result.generations[0].message.additional_kwargs

backend/tests/test_replay_provider.py

@@ -0,0 +1,116 @@
+from __future__ import annotations
+
+import json
+from pathlib import Path
+
+from langchain_core.messages import AIMessage, HumanMessage, messages_to_dict
+from replay_provider import ReplayChatModel, caller_identity, hash_messages, hash_replay_input
+
+
+def _write_fixture(path: Path, turns: list[dict]) -> None:
+    path.write_text(
+        json.dumps(
+            {
+                "scenario": "unit",
+                "mode": "unit",
+                "model": "replay",
+                "prompt": "unit",
+                "context": {},
+                "turns": turns,
+            }
+        ),
+        encoding="utf-8",
+    )
+
+
+def test_replay_key_includes_caller_identity(tmp_path: Path):
+    messages = [HumanMessage(content="same conversation")]
+    lead_output = AIMessage(content="lead")
+    suggest_output = AIMessage(content="suggest")
+    fixture_path = tmp_path / "fixture.json"
+
+    _write_fixture(
+        fixture_path,
+        [
+            {
+                "caller": "lead_agent",
+                "conversation_hash": hash_messages(messages),
+                "input_hash": hash_replay_input(messages, caller="lead_agent"),
+                "output": messages_to_dict([lead_output])[0],
+            },
+            {
+                "caller": "suggest_agent",
+                "conversation_hash": hash_messages(messages),
+                "input_hash": hash_replay_input(messages, caller="suggest_agent"),
+                "output": messages_to_dict([suggest_output])[0],
+            },
+        ],
+    )
+
+    model = ReplayChatModel(fixture=str(fixture_path))
+
+    assert model.invoke(messages, config={"run_name": "suggest_agent"}).content == "suggest"
+    assert model.invoke(messages, config={"run_name": "lead_agent"}).content == "lead"
+
+
+def test_replay_supports_legacy_conversation_only_fixture(tmp_path: Path):
+    messages = [HumanMessage(content="legacy conversation")]
+    fixture_path = tmp_path / "legacy.json"
+
+    _write_fixture(
+        fixture_path,
+        [
+            {
+                "input_hash": hash_messages(messages),
+                "output": messages_to_dict([AIMessage(content="legacy")])[0],
+            }
+        ],
+    )
+
+    model = ReplayChatModel(fixture=str(fixture_path))
+
+    assert model.invoke(messages, config={"run_name": "suggest_agent"}).content == "legacy"
+
+
+def test_title_run_name_uses_middleware_caller_namespace(tmp_path: Path):
+    messages = [HumanMessage(content="title prompt")]
+    fixture_path = tmp_path / "fixture.json"
+
+    _write_fixture(
+        fixture_path,
+        [
+            {
+                "caller": "middleware:title",
+                "conversation_hash": hash_messages(messages),
+                "input_hash": hash_replay_input(messages, caller="middleware:title"),
+                "output": messages_to_dict([AIMessage(content="generated title")])[0],
+            }
+        ],
+    )
+
+    model = ReplayChatModel(fixture=str(fixture_path))
+
+    assert caller_identity(name="title_agent") == "middleware:title"
+    assert model.invoke(messages, config={"run_name": "title_agent"}).content == "generated title"
+
+
+def test_replay_uses_single_pending_capture_when_run_manager_is_missing(tmp_path: Path):
+    messages = [HumanMessage(content="title prompt")]
+    fixture_path = tmp_path / "fixture.json"
+
+    _write_fixture(
+        fixture_path,
+        [
+            {
+                "caller": "middleware:title",
+                "conversation_hash": hash_messages(messages),
+                "input_hash": hash_replay_input(messages, caller="middleware:title"),
+                "output": messages_to_dict([AIMessage(content="generated title")])[0],
+            }
+        ],
+    )
+
+    model = ReplayChatModel(fixture=str(fixture_path))
+    model._run_callers["captured-run"] = caller_identity(name="title_agent", tags=["middleware:title"])
+
+    assert model._match(messages, run_manager=None).content == "generated title"

backend/tests/test_run_journal.py

@@ -179,15 +179,16 @@ class TestLifecycleCallbacks:
         assert "run.end" in types
 
     @pytest.mark.anyio
-    async def test_nested_chain_no_run_start(self, journal_setup):
-        """Nested chains (parent_run_id set) should NOT produce run.start."""
+    async def test_nested_chain_no_run_lifecycle_events(self, journal_setup):
+        """Nested chains (parent_run_id set) should NOT produce root run lifecycle events."""
         j, store = journal_setup
         parent_id = uuid4()
         j.on_chain_start({}, {}, run_id=uuid4(), parent_run_id=parent_id)
-        j.on_chain_end({}, run_id=uuid4())
+        j.on_chain_end({}, run_id=uuid4(), parent_run_id=parent_id)
         await j.flush()
         events = await store.list_events("t1", "r1")
         assert not any(e["event_type"] == "run.start" for e in events)
+        assert not any(e["event_type"] == "run.end" for e in events)
 
 
 class TestToolCallbacks:

backend/tests/test_slash_skills.py

@@ -0,0 +1,557 @@
+import asyncio
+import hashlib
+from pathlib import Path
+from types import SimpleNamespace
+
+from langchain.agents.middleware.types import ModelRequest
+from langchain_core.messages import AIMessage, HumanMessage
+
+from app.channels.commands import KNOWN_CHANNEL_COMMANDS
+from deerflow.agents.middlewares import skill_activation_middleware as middleware_module
+from deerflow.agents.middlewares.skill_activation_middleware import SkillActivationMiddleware, is_slash_skill_activation_reminder
+from deerflow.skills.slash import RESERVED_SLASH_SKILL_NAMES, parse_slash_skill_reference, resolve_slash_skill
+from deerflow.skills.types import Skill, SkillCategory
+from deerflow.utils.messages import ORIGINAL_USER_CONTENT_KEY
+
+
+def _make_skill(tmp_path: Path, name: str, content: str = "skill body") -> Skill:
+    skill_dir = tmp_path / name
+    skill_dir.mkdir()
+    skill_file = skill_dir / "SKILL.md"
+    skill_file.write_text(content, encoding="utf-8")
+    return Skill(
+        name=name,
+        description=f"Description for {name}",
+        license="MIT",
+        skill_dir=skill_dir,
+        skill_file=skill_file,
+        relative_path=Path(name),
+        category=SkillCategory.CUSTOM,
+        enabled=True,
+    )
+
+
+def _make_storage(tmp_path: Path, skills: list[Skill]):
+    return SimpleNamespace(
+        load_skills=lambda *, enabled_only: [skill for skill in skills if skill.enabled] if enabled_only else skills,
+        get_container_root=lambda: "/mnt/skills",
+        get_skills_root_path=lambda: tmp_path,
+    )
+
+
+def _make_model_request(messages: list[HumanMessage], *, runtime=None) -> ModelRequest:
+    return ModelRequest(
+        model=object(),
+        messages=messages,
+        state={"messages": list(messages)},
+        runtime=runtime,
+    )
+
+
+def test_parse_slash_skill_reference_extracts_name_and_remaining_text():
+    parsed = parse_slash_skill_reference("/data-analysis analyze uploads/foo.csv")
+
+    assert parsed is not None
+    assert parsed.name == "data-analysis"
+    assert parsed.remaining_text == "analyze uploads/foo.csv"
+
+
+def test_parse_slash_skill_reference_accepts_skill_name_without_task():
+    parsed = parse_slash_skill_reference("/data-analysis")
+
+    assert parsed is not None
+    assert parsed.name == "data-analysis"
+    assert parsed.remaining_text == ""
+
+
+def test_parse_slash_skill_reference_rejects_invalid_names():
+    assert parse_slash_skill_reference("/DataAnalysis run") is None
+    assert parse_slash_skill_reference("/data_analysis run") is None
+    assert parse_slash_skill_reference("please use /data-analysis") is None
+    assert parse_slash_skill_reference("  /data-analysis run") is None
+    assert parse_slash_skill_reference("/data-analysis分析这个文档") is None
+
+
+def test_resolve_slash_skill_ignores_reserved_control_commands(tmp_path):
+    for command in ["bootstrap", "help", "memory", "models", "new", "status"]:
+        skill = _make_skill(tmp_path, command)
+
+        assert resolve_slash_skill(f"/{command} create an agent", [skill]) is None
+
+
+def test_reserved_slash_skill_names_match_channel_commands():
+    assert RESERVED_SLASH_SKILL_NAMES == {command.removeprefix("/") for command in KNOWN_CHANNEL_COMMANDS}
+
+
+def test_resolve_slash_skill_respects_available_skill_whitelist(tmp_path):
+    skill = _make_skill(tmp_path, "data-analysis")
+
+    assert resolve_slash_skill("/data-analysis run", [skill], available_skills=set()) is None
+
+    resolved = resolve_slash_skill("/data-analysis run", [skill], available_skills={"data-analysis"})
+    assert resolved is not None
+    assert resolved.skill.name == "data-analysis"
+    assert resolved.remaining_text == "run"
+    assert resolved.container_file_path == "/mnt/skills/custom/data-analysis/SKILL.md"
+
+
+def test_resolve_slash_skill_rejects_disabled_skills(tmp_path):
+    skill = _make_skill(tmp_path, "data-analysis")
+    skill.enabled = False
+
+    assert resolve_slash_skill("/data-analysis run", [skill]) is None
+
+
+def test_skill_activation_middleware_injects_hidden_human_context_for_model_call(monkeypatch, tmp_path):
+    skill = _make_skill(tmp_path, "data-analysis", content="# Data Analysis\nUse pandas.")
+    monkeypatch.setattr(middleware_module, "get_or_new_skill_storage", lambda **kwargs: _make_storage(tmp_path, [skill]))
+
+    middleware = SkillActivationMiddleware()
+    original = HumanMessage(content="/data-analysis analyze uploads/foo.csv", id="msg-1")
+    request = _make_model_request([original])
+    captured = {}
+
+    def handler(model_request: ModelRequest):
+        captured["messages"] = model_request.messages
+        return AIMessage(content="ok")
+
+    result = middleware.wrap_model_call(request, handler)
+
+    assert isinstance(result, AIMessage)
+    assert result.content == "ok"
+    activation_msg, user_msg = captured["messages"]
+    assert is_slash_skill_activation_reminder(activation_msg)
+    assert activation_msg.additional_kwargs["hide_from_ui"] is True
+    assert "Use pandas." in activation_msg.content
+    assert "<user_request>\nanalyze uploads/foo.csv\n</user_request>" in activation_msg.content
+    assert user_msg.content == original.content
+    assert request.state["messages"] == [original]
+
+
+def test_skill_activation_middleware_does_not_duplicate_existing_activation(monkeypatch, tmp_path):
+    skill = _make_skill(tmp_path, "data-analysis", content="# Data Analysis\nUse pandas.")
+    monkeypatch.setattr(middleware_module, "get_or_new_skill_storage", lambda **kwargs: _make_storage(tmp_path, [skill]))
+
+    middleware = SkillActivationMiddleware()
+    original = HumanMessage(content="/data-analysis analyze uploads/foo.csv", id="msg-1")
+    first_capture = {}
+
+    def first_handler(model_request: ModelRequest):
+        first_capture["messages"] = model_request.messages
+        return AIMessage(content="ok")
+
+    first_result = middleware.wrap_model_call(_make_model_request([original]), first_handler)
+
+    assert isinstance(first_result, AIMessage)
+    activation_msg, user_msg = first_capture["messages"]
+    assert is_slash_skill_activation_reminder(activation_msg)
+
+    second_capture = {}
+
+    def second_handler(model_request: ModelRequest):
+        second_capture["messages"] = model_request.messages
+        return AIMessage(content="ok")
+
+    second_result = middleware.wrap_model_call(_make_model_request([activation_msg, user_msg]), second_handler)
+
+    assert isinstance(second_result, AIMessage)
+    assert second_capture["messages"] == [activation_msg, user_msg]
+    assert sum(is_slash_skill_activation_reminder(message) for message in second_capture["messages"]) == 1
+
+
+def test_skill_activation_middleware_does_not_duplicate_activation_separated_by_hidden_context(monkeypatch, tmp_path):
+    skill = _make_skill(tmp_path, "data-analysis", content="# Data Analysis\nUse pandas.")
+    monkeypatch.setattr(middleware_module, "get_or_new_skill_storage", lambda **kwargs: _make_storage(tmp_path, [skill]))
+
+    middleware = SkillActivationMiddleware()
+    original = HumanMessage(content="/data-analysis analyze uploads/foo.csv", id="msg-1")
+    first_capture = {}
+
+    def first_handler(model_request: ModelRequest):
+        first_capture["messages"] = model_request.messages
+        return AIMessage(content="ok")
+
+    middleware.wrap_model_call(_make_model_request([original]), first_handler)
+    activation_msg, user_msg = first_capture["messages"]
+    hidden_context = HumanMessage(content="dynamic context", additional_kwargs={"hide_from_ui": True})
+    second_capture = {}
+
+    def second_handler(model_request: ModelRequest):
+        second_capture["messages"] = model_request.messages
+        return AIMessage(content="ok")
+
+    second_result = middleware.wrap_model_call(_make_model_request([activation_msg, hidden_context, user_msg]), second_handler)
+
+    assert isinstance(second_result, AIMessage)
+    assert second_capture["messages"] == [activation_msg, hidden_context, user_msg]
+    assert sum(is_slash_skill_activation_reminder(message) for message in second_capture["messages"]) == 1
+
+
+def test_skill_activation_middleware_dedupes_immediately_previous_activation_without_target_id(monkeypatch, tmp_path):
+    skill = _make_skill(tmp_path, "data-analysis", content="# Data Analysis\nUse pandas.")
+    monkeypatch.setattr(middleware_module, "get_or_new_skill_storage", lambda **kwargs: _make_storage(tmp_path, [skill]))
+
+    middleware = SkillActivationMiddleware()
+    legacy_activation_msg = SkillActivationMiddleware._make_activation_message(
+        HumanMessage(content="/data-analysis analyze uploads/foo.csv"),
+        "existing activation context",
+    )
+    target = HumanMessage(content="/data-analysis analyze uploads/foo.csv", id="msg-1")
+    captured = {}
+
+    def handler(model_request: ModelRequest):
+        captured["messages"] = model_request.messages
+        return AIMessage(content="ok")
+
+    result = middleware.wrap_model_call(_make_model_request([legacy_activation_msg, target]), handler)
+
+    assert isinstance(result, AIMessage)
+    assert captured["messages"] == [legacy_activation_msg, target]
+    assert sum(is_slash_skill_activation_reminder(message) for message in captured["messages"]) == 1
+
+
+def test_skill_activation_middleware_async_injects_hidden_human_context_for_model_call(monkeypatch, tmp_path):
+    skill = _make_skill(tmp_path, "data-analysis", content="# Data Analysis\nUse pandas.")
+    monkeypatch.setattr(middleware_module, "get_or_new_skill_storage", lambda **kwargs: _make_storage(tmp_path, [skill]))
+
+    middleware = SkillActivationMiddleware()
+    original = HumanMessage(content="/data-analysis analyze uploads/foo.csv", id="msg-1")
+    request = _make_model_request([original])
+    captured = {}
+
+    async def handler(model_request: ModelRequest):
+        captured["messages"] = model_request.messages
+        return AIMessage(content="ok")
+
+    result = asyncio.run(middleware.awrap_model_call(request, handler))
+
+    assert isinstance(result, AIMessage)
+    assert result.content == "ok"
+    activation_msg, user_msg = captured["messages"]
+    assert is_slash_skill_activation_reminder(activation_msg)
+    assert activation_msg.additional_kwargs["hide_from_ui"] is True
+    assert "Use pandas." in activation_msg.content
+    assert "<user_request>\nanalyze uploads/foo.csv\n</user_request>" in activation_msg.content
+    assert user_msg.content == original.content
+    assert request.state["messages"] == [original]
+
+
+def test_skill_activation_middleware_uses_fallback_when_task_text_is_empty(monkeypatch, tmp_path):
+    skill = _make_skill(tmp_path, "data-analysis", content="# Data Analysis\nUse pandas.")
+    monkeypatch.setattr(middleware_module, "get_or_new_skill_storage", lambda **kwargs: _make_storage(tmp_path, [skill]))
+
+    middleware = SkillActivationMiddleware()
+    original = HumanMessage(content="/data-analysis", id="msg-1")
+    captured = {}
+
+    def handler(model_request: ModelRequest):
+        captured["messages"] = model_request.messages
+        return AIMessage(content="ok")
+
+    result = middleware.wrap_model_call(_make_model_request([original]), handler)
+
+    assert isinstance(result, AIMessage)
+    activation_msg = captured["messages"][0]
+    assert "No additional task text was provided after the slash skill command." in activation_msg.content
+
+
+def test_skill_activation_middleware_uses_original_user_content_when_uploads_are_injected(monkeypatch, tmp_path):
+    skill = _make_skill(tmp_path, "data-analysis", content="# Data Analysis\nUse pandas.")
+    monkeypatch.setattr(middleware_module, "get_or_new_skill_storage", lambda **kwargs: _make_storage(tmp_path, [skill]))
+
+    middleware = SkillActivationMiddleware()
+    original = HumanMessage(
+        content="<uploaded_files>\n- report.pdf\n</uploaded_files>\n\n/data-analysis 分析这个文档",
+        id="msg-1",
+        additional_kwargs={ORIGINAL_USER_CONTENT_KEY: "/data-analysis 分析这个文档"},
+    )
+    captured = {}
+
+    def handler(model_request: ModelRequest):
+        captured["messages"] = model_request.messages
+        return AIMessage(content="ok")
+
+    result = middleware.wrap_model_call(_make_model_request([original]), handler)
+
+    assert isinstance(result, AIMessage)
+    assert result.content == "ok"
+    activation_msg, user_msg = captured["messages"]
+    assert is_slash_skill_activation_reminder(activation_msg)
+    assert "Use pandas." in activation_msg.content
+    assert "<user_request>\n分析这个文档\n</user_request>" in activation_msg.content
+    assert user_msg.content == original.content
+    assert user_msg.additional_kwargs[ORIGINAL_USER_CONTENT_KEY] == "/data-analysis 分析这个文档"
+
+
+def test_skill_activation_middleware_activates_from_list_content(monkeypatch, tmp_path):
+    skill = _make_skill(tmp_path, "data-analysis", content="# Data Analysis\nUse pandas.")
+    monkeypatch.setattr(middleware_module, "get_or_new_skill_storage", lambda **kwargs: _make_storage(tmp_path, [skill]))
+
+    middleware = SkillActivationMiddleware()
+    original = HumanMessage(content=[{"type": "text", "text": "/data-analysis analyze uploads/foo.csv"}], id="msg-1")
+    captured = {}
+
+    def handler(model_request: ModelRequest):
+        captured["messages"] = model_request.messages
+        return AIMessage(content="ok")
+
+    result = middleware.wrap_model_call(_make_model_request([original]), handler)
+
+    assert isinstance(result, AIMessage)
+    activation_msg, user_msg = captured["messages"]
+    assert is_slash_skill_activation_reminder(activation_msg)
+    assert "<user_request>\nanalyze uploads/foo.csv\n</user_request>" in activation_msg.content
+    assert user_msg.content == original.content
+
+
+def test_skill_activation_middleware_records_activation_audit_event(monkeypatch, tmp_path):
+    skill = _make_skill(tmp_path, "data-analysis", content="# Data Analysis\nUse pandas.")
+    monkeypatch.setattr(middleware_module, "get_or_new_skill_storage", lambda **kwargs: _make_storage(tmp_path, [skill]))
+
+    recorded = []
+    journal = SimpleNamespace(record_middleware=lambda *args, **kwargs: recorded.append((args, kwargs)))
+    runtime = SimpleNamespace(context={"__run_journal": journal})
+    middleware = SkillActivationMiddleware()
+    original = HumanMessage(content="/data-analysis analyze uploads/foo.csv", id="msg-1")
+
+    def handler(model_request: ModelRequest):
+        return AIMessage(content="ok")
+
+    result = middleware.wrap_model_call(_make_model_request([original], runtime=runtime), handler)
+
+    assert isinstance(result, AIMessage)
+    assert len(recorded) == 1
+    args, kwargs = recorded[0]
+    assert args == ("skill_activation",)
+    assert kwargs["name"] == "SkillActivationMiddleware"
+    assert kwargs["hook"] == "wrap_model_call"
+    assert kwargs["action"] == "activate"
+    assert kwargs["changes"] == {
+        "skill_name": "data-analysis",
+        "category": "custom",
+        "path": "/mnt/skills/custom/data-analysis/SKILL.md",
+        "content_hash": hashlib.sha256(b"# Data Analysis\nUse pandas.").hexdigest(),
+    }
+
+
+def test_skill_activation_middleware_async_records_activation_audit_event(monkeypatch, tmp_path):
+    skill = _make_skill(tmp_path, "data-analysis", content="# Data Analysis\nUse pandas.")
+    monkeypatch.setattr(middleware_module, "get_or_new_skill_storage", lambda **kwargs: _make_storage(tmp_path, [skill]))
+
+    recorded = []
+    journal = SimpleNamespace(record_middleware=lambda *args, **kwargs: recorded.append((args, kwargs)))
+    runtime = SimpleNamespace(context={"__run_journal": journal})
+    middleware = SkillActivationMiddleware()
+    original = HumanMessage(content="/data-analysis analyze uploads/foo.csv", id="msg-1")
+
+    async def handler(model_request: ModelRequest):
+        return AIMessage(content="ok")
+
+    result = asyncio.run(middleware.awrap_model_call(_make_model_request([original], runtime=runtime), handler))
+
+    assert isinstance(result, AIMessage)
+    assert len(recorded) == 1
+    args, kwargs = recorded[0]
+    assert args == ("skill_activation",)
+    assert kwargs["hook"] == "awrap_model_call"
+    assert kwargs["changes"]["skill_name"] == "data-analysis"
+    assert kwargs["changes"]["content_hash"] == hashlib.sha256(b"# Data Analysis\nUse pandas.").hexdigest()
+
+
+def test_skill_activation_middleware_ignores_activation_audit_errors(monkeypatch, tmp_path):
+    skill = _make_skill(tmp_path, "data-analysis", content="# Data Analysis\nUse pandas.")
+    monkeypatch.setattr(middleware_module, "get_or_new_skill_storage", lambda **kwargs: _make_storage(tmp_path, [skill]))
+
+    journal = SimpleNamespace(record_middleware=lambda *args, **kwargs: (_ for _ in ()).throw(RuntimeError("db down")))
+    runtime = SimpleNamespace(context={"__run_journal": journal})
+    middleware = SkillActivationMiddleware()
+    original = HumanMessage(content="/data-analysis analyze uploads/foo.csv", id="msg-1")
+
+    def handler(model_request: ModelRequest):
+        return AIMessage(content="ok")
+
+    result = middleware.wrap_model_call(_make_model_request([original], runtime=runtime), handler)
+
+    assert isinstance(result, AIMessage)
+    assert result.content == "ok"
+
+
+def test_skill_activation_middleware_activates_only_latest_real_user_message(monkeypatch, tmp_path):
+    skill = _make_skill(tmp_path, "data-analysis", content="# Data Analysis\nUse pandas.")
+    monkeypatch.setattr(middleware_module, "get_or_new_skill_storage", lambda **kwargs: _make_storage(tmp_path, [skill]))
+
+    middleware = SkillActivationMiddleware()
+    old_slash = HumanMessage(content="/data-analysis old request", id="msg-1")
+    latest_user = HumanMessage(content="continue normally", id="msg-2")
+    request = _make_model_request([old_slash, AIMessage(content="done"), latest_user])
+    captured = {}
+
+    def handler(model_request: ModelRequest):
+        captured["messages"] = model_request.messages
+        return AIMessage(content="ok")
+
+    result = middleware.wrap_model_call(request, handler)
+
+    assert isinstance(result, AIMessage)
+    assert captured["messages"] == request.messages
+    assert not any(is_slash_skill_activation_reminder(message) for message in captured["messages"])
+
+
+def test_skill_activation_middleware_ignores_hidden_and_summary_user_messages(monkeypatch, tmp_path):
+    skill = _make_skill(tmp_path, "data-analysis", content="# Data Analysis\nUse pandas.")
+    monkeypatch.setattr(middleware_module, "get_or_new_skill_storage", lambda **kwargs: _make_storage(tmp_path, [skill]))
+
+    middleware = SkillActivationMiddleware()
+    real_user = HumanMessage(content="continue normally", id="msg-1")
+    hidden_slash = HumanMessage(content="/data-analysis hidden request", id="msg-2", additional_kwargs={"hide_from_ui": True})
+    summary_slash = HumanMessage(content="/data-analysis summary request", id="msg-3", name="summary")
+    request = _make_model_request([real_user, hidden_slash, summary_slash])
+    captured = {}
+
+    def handler(model_request: ModelRequest):
+        captured["messages"] = model_request.messages
+        return AIMessage(content="ok")
+
+    result = middleware.wrap_model_call(request, handler)
+
+    assert isinstance(result, AIMessage)
+    assert captured["messages"] == request.messages
+    assert not any(is_slash_skill_activation_reminder(message) for message in captured["messages"])
+
+
+def test_skill_activation_middleware_returns_clear_error_for_disallowed_skill(monkeypatch, tmp_path):
+    skill = _make_skill(tmp_path, "data-analysis")
+    monkeypatch.setattr(middleware_module, "get_or_new_skill_storage", lambda **kwargs: _make_storage(tmp_path, [skill]))
+
+    middleware = SkillActivationMiddleware(available_skills={"frontend-design"})
+    original = HumanMessage(content="/data-analysis run")
+
+    def handler(model_request: ModelRequest):
+        raise AssertionError("handler should not be called for invalid slash skills")
+
+    result = middleware.wrap_model_call(_make_model_request([original]), handler)
+
+    assert isinstance(result, AIMessage)
+    assert "not available for this agent" in result.content
+
+
+def test_skill_activation_middleware_returns_clear_error_for_missing_skill(monkeypatch, tmp_path):
+    monkeypatch.setattr(middleware_module, "get_or_new_skill_storage", lambda **kwargs: _make_storage(tmp_path, []))
+
+    middleware = SkillActivationMiddleware()
+    original = HumanMessage(content="/data-analysis run")
+
+    def handler(model_request: ModelRequest):
+        raise AssertionError("handler should not be called for missing slash skills")
+
+    result = middleware.wrap_model_call(_make_model_request([original]), handler)
+
+    assert isinstance(result, AIMessage)
+    assert "not installed" in result.content
+
+
+def test_skill_activation_middleware_returns_clear_error_for_disabled_skill(monkeypatch, tmp_path):
+    skill = _make_skill(tmp_path, "data-analysis")
+    skill.enabled = False
+    monkeypatch.setattr(middleware_module, "get_or_new_skill_storage", lambda **kwargs: _make_storage(tmp_path, [skill]))
+
+    middleware = SkillActivationMiddleware()
+    original = HumanMessage(content="/data-analysis run")
+
+    def handler(model_request: ModelRequest):
+        raise AssertionError("handler should not be called for disabled slash skills")
+
+    result = middleware.wrap_model_call(_make_model_request([original]), handler)
+
+    assert isinstance(result, AIMessage)
+    assert "installed but disabled" in result.content
+
+
+def test_skill_activation_middleware_escapes_activation_content(monkeypatch, tmp_path):
+    skill = _make_skill(
+        tmp_path,
+        "data-analysis",
+        content="# Data Analysis\nUse <xml> & avoid </skill> collisions.\n----- END SKILL.md -----",
+    )
+    monkeypatch.setattr(middleware_module, "get_or_new_skill_storage", lambda **kwargs: _make_storage(tmp_path, [skill]))
+
+    middleware = SkillActivationMiddleware()
+    original = HumanMessage(content="/data-analysis analyze </user_request>")
+    captured = {}
+
+    def handler(model_request: ModelRequest):
+        captured["messages"] = model_request.messages
+        return AIMessage(content="ok")
+
+    result = middleware.wrap_model_call(_make_model_request([original]), handler)
+
+    assert isinstance(result, AIMessage)
+    activation_msg = captured["messages"][0]
+    assert '<skill_content encoding="xml-escaped">' in activation_msg.content
+    assert "analyze &lt;/user_request&gt;" in activation_msg.content
+    assert "Use &lt;xml&gt; &amp; avoid &lt;/skill&gt; collisions." in activation_msg.content
+    assert "----- BEGIN SKILL.md -----" not in activation_msg.content
+
+
+def test_skill_activation_middleware_rejects_skill_file_outside_skills_root(monkeypatch, tmp_path):
+    skills_root = tmp_path / "skills"
+    skill_dir = skills_root / "custom" / "data-analysis"
+    skill_dir.mkdir(parents=True)
+    outside_dir = tmp_path / "outside"
+    outside_dir.mkdir()
+    outside_file = outside_dir / "SKILL.md"
+    outside_file.write_text("# Leaked\nDo not read me.", encoding="utf-8")
+    (skill_dir / "SKILL.md").symlink_to(outside_file)
+    skill = Skill(
+        name="data-analysis",
+        description="Description for data-analysis",
+        license="MIT",
+        skill_dir=skill_dir,
+        skill_file=skill_dir / "SKILL.md",
+        relative_path=Path("data-analysis"),
+        category=SkillCategory.CUSTOM,
+        enabled=True,
+    )
+    monkeypatch.setattr(middleware_module, "get_or_new_skill_storage", lambda **kwargs: _make_storage(skills_root, [skill]))
+
+    middleware = SkillActivationMiddleware()
+
+    def handler(model_request: ModelRequest):
+        raise AssertionError("handler should not be called when SKILL.md fails safety checks")
+
+    result = middleware.wrap_model_call(_make_model_request([HumanMessage(content="/data-analysis run")]), handler)
+
+    assert isinstance(result, AIMessage)
+    assert "could not be loaded safely" in result.content
+
+
+def test_skill_activation_middleware_reports_missing_skill_file_safely(monkeypatch, tmp_path):
+    skill = _make_skill(tmp_path, "data-analysis")
+    skill.skill_file.unlink()
+    monkeypatch.setattr(middleware_module, "get_or_new_skill_storage", lambda **kwargs: _make_storage(tmp_path, [skill]))
+
+    middleware = SkillActivationMiddleware()
+
+    def handler(model_request: ModelRequest):
+        raise AssertionError("handler should not be called when SKILL.md is missing")
+
+    result = middleware.wrap_model_call(_make_model_request([HumanMessage(content="/data-analysis run")]), handler)
+
+    assert isinstance(result, AIMessage)
+    assert "could not be loaded safely" in result.content
+
+
+def test_skill_activation_middleware_reports_invalid_utf8_skill_file_safely(monkeypatch, tmp_path):
+    skill = _make_skill(tmp_path, "data-analysis")
+    skill.skill_file.write_bytes(b"\xff\xfe\x00")
+    monkeypatch.setattr(middleware_module, "get_or_new_skill_storage", lambda **kwargs: _make_storage(tmp_path, [skill]))
+
+    middleware = SkillActivationMiddleware()
+
+    def handler(model_request: ModelRequest):
+        raise AssertionError("handler should not be called when SKILL.md is not valid UTF-8")
+
+    result = middleware.wrap_model_call(_make_model_request([HumanMessage(content="/data-analysis run")]), handler)
+
+    assert isinstance(result, AIMessage)
+    assert "could not be loaded safely" in result.content

backend/tests/test_uploads_middleware_core_logic.py

@@ -14,6 +14,7 @@ from langchain_core.messages import AIMessage, HumanMessage
 
 from deerflow.agents.middlewares.uploads_middleware import UploadsMiddleware
 from deerflow.config.paths import Paths
+from deerflow.utils.messages import ORIGINAL_USER_CONTENT_KEY
 
 THREAD_ID = "thread-abc123"
 
@@ -263,6 +264,22 @@ class TestBeforeAgent:
         assert "<uploaded_files>" in combined_text
         assert "analyse this" in combined_text
 
+    def test_list_content_preserves_original_slash_skill_text(self, tmp_path):
+        mw = _middleware(tmp_path)
+        uploads_dir = _uploads_dir(tmp_path)
+        (uploads_dir / "data.csv").write_bytes(b"a,b")
+
+        msg = _human(
+            [{"type": "text", "text": "/data-analysis analyze data.csv"}],
+            files=[{"filename": "data.csv", "size": 3, "path": "/mnt/user-data/uploads/data.csv"}],
+        )
+        result = mw.before_agent(self._state(msg), _runtime())
+
+        assert result is not None
+        updated_msg = result["messages"][-1]
+        assert isinstance(updated_msg.content, list)
+        assert updated_msg.additional_kwargs[ORIGINAL_USER_CONTENT_KEY] == "/data-analysis analyze data.csv"
+
     def test_preserves_additional_kwargs_on_updated_message(self, tmp_path):
         mw = _middleware(tmp_path)
         uploads_dir = _uploads_dir(tmp_path)
@@ -278,6 +295,37 @@ class TestBeforeAgent:
         assert updated_kwargs.get("files") == files_meta
         assert updated_kwargs.get("element") == "task"
 
+    def test_preserves_original_user_content_before_upload_context(self, tmp_path):
+        mw = _middleware(tmp_path)
+        uploads_dir = _uploads_dir(tmp_path)
+        (uploads_dir / "report.pdf").write_bytes(b"pdf")
+
+        msg = _human(
+            "/data-analysis 分析这个文档",
+            files=[{"filename": "report.pdf", "size": 3, "path": "/mnt/user-data/uploads/report.pdf"}],
+        )
+        result = mw.before_agent(self._state(msg), _runtime())
+
+        assert result is not None
+        updated_msg = result["messages"][-1]
+        assert updated_msg.content.startswith("<uploaded_files>")
+        assert updated_msg.additional_kwargs[ORIGINAL_USER_CONTENT_KEY] == "/data-analysis 分析这个文档"
+
+    def test_preserves_existing_original_user_content_marker(self, tmp_path):
+        mw = _middleware(tmp_path)
+        uploads_dir = _uploads_dir(tmp_path)
+        (uploads_dir / "report.pdf").write_bytes(b"pdf")
+
+        msg = _human(
+            "<uploaded_files>\nold\n</uploaded_files>\n\n/data-analysis run",
+            files=[{"filename": "report.pdf", "size": 3, "path": "/mnt/user-data/uploads/report.pdf"}],
+            **{ORIGINAL_USER_CONTENT_KEY: "/data-analysis run"},
+        )
+        result = mw.before_agent(self._state(msg), _runtime())
+
+        assert result is not None
+        assert result["messages"][-1].additional_kwargs[ORIGINAL_USER_CONTENT_KEY] == "/data-analysis run"
+
     def test_uploaded_files_returned_in_state_update(self, tmp_path):
         mw = _middleware(tmp_path)
         uploads_dir = _uploads_dir(tmp_path)

backend/tests/test_uvicorn_reload_exclude.py

@@ -0,0 +1,185 @@
+"""Regression for #3459 / #3454 — dev gateway reload-exclude must not crash.
+
+#3426 switched the dev gateway's ``--reload-exclude`` patterns from relative
+(``sandbox/``) to absolute (``$REPO_ROOT/backend/sandbox``). uvicorn only
+excludes such a path directly when it already exists as a directory; otherwise
+it falls back to ``Path.cwd().glob(pattern)``, and on **Python 3.12**
+``pathlib.Path.glob()`` raises ``NotImplementedError: Non-relative patterns are
+unsupported`` for an absolute pattern. ``serve.sh`` created the ``.deer-flow``
+excludes but not ``backend/sandbox``, so a fresh checkout crashed ``make dev``
+on startup.
+
+Two layers of coverage:
+
+* ``test_*_resolve_*`` exercises uvicorn's real ``resolve_reload_patterns`` to
+  pin the failure mode and the fix's mechanism.
+* ``test_launcher_precreates_every_absolute_reload_exclude`` enforces the actual
+  invariant on both launchers: every absolute exclude dir is ``mkdir -p``'d
+  before uvicorn starts. This encodes the root cause, so any future absolute
+  exclude that forgets its ``mkdir`` fails here.
+"""
+
+from __future__ import annotations
+
+import re
+import shlex
+import subprocess
+import sys
+from pathlib import Path
+
+import pytest
+from uvicorn.config import resolve_reload_patterns
+
+REPO_ROOT = Path(__file__).resolve().parents[2]
+
+LAUNCHERS = {
+    "scripts/serve.sh": REPO_ROOT / "scripts" / "serve.sh",
+    "docker/dev-entrypoint.sh": REPO_ROOT / "docker" / "dev-entrypoint.sh",
+}
+
+# Shell terminators / redirects that end a simple command's argument list.
+_CMD_BOUNDARY = re.compile(r"[;&|<>]")
+
+
+def _logical_lines(script: str) -> list[str]:
+    """Fold ``\\``-continuations and drop comment lines, yielding logical lines.
+
+    A ``mkdir`` or ``--reload-exclude`` list split across lines with a trailing
+    backslash becomes one line here, so an argument on a continuation line can't
+    be silently dropped by per-line scanning.
+    """
+    folded = script.replace("\\\n", " ")
+    return [line for line in folded.splitlines() if not line.lstrip().startswith("#")]
+
+
+def _shlex(fragment: str) -> list[str]:
+    """Tokenize a shell fragment (quotes stripped, ``$VAR`` kept literal,
+    trailing ``# comment`` honored); tolerate pathological quoting."""
+    try:
+        return shlex.split(fragment, comments=True)
+    except ValueError:
+        return fragment.split()
+
+
+# ``--reload-exclude`` followed by ``=`` or whitespace, then a value that is a
+# single-quoted group, a double-quoted group, or a bare token. The quoted
+# alternatives match a *balanced* pair first, so serve.sh's surrounding
+# ``GATEWAY_EXTRA_FLAGS="..."`` closing quote is never swallowed into the value.
+_RELOAD_EXCLUDE = re.compile(r"""--reload-exclude[=\s]+('[^']*'|"[^"]*"|[^\s'"]+)""")
+
+
+def _reload_exclude_values(script: str) -> list[str]:
+    """Every ``--reload-exclude`` value, with surrounding quotes removed.
+
+    Handles both CLI forms (``--reload-exclude=<value>`` and the space form
+    ``--reload-exclude <value>``) and both shell quotings the launchers use:
+
+    * ``docker/dev-entrypoint.sh`` puts each flag on its own line.
+    * ``scripts/serve.sh`` packs every flag into a single double-quoted
+      ``GATEWAY_EXTRA_FLAGS="... --reload-exclude='$X' ..."`` assignment. A
+      whole-line ``shlex`` would collapse that assignment into one token and
+      find no flags (this is what regressed serve.sh in CI); matching balanced
+      inner quotes here keeps the assignment's closing ``"`` out of the value,
+      so every exclude — including the last ``$BACKEND_RUNTIME_HOME`` — is seen.
+    """
+    values: list[str] = []
+    for line in _logical_lines(script):
+        for raw in _RELOAD_EXCLUDE.findall(line):
+            values.append(raw.strip("\"'"))
+    return values
+
+
+def _mkdir_dirs(script: str) -> set[str]:
+    """Exact set of directories created by every ``mkdir`` command.
+
+    Tokenizes each ``mkdir`` argument list rather than substring-matching, so
+    ``/app/backend/sandbox`` is not falsely considered created by, say,
+    ``mkdir -p /app/backend/sandbox-other``.
+    """
+    dirs: set[str] = set()
+    for line in _logical_lines(script):
+        match = re.search(r"\bmkdir\b(.*)", line)
+        if not match:
+            continue
+        args = _CMD_BOUNDARY.split(match.group(1), maxsplit=1)[0]
+        for token in _shlex(args):
+            if token.startswith("-"):  # skip flags such as -p
+                continue
+            dirs.add(token)
+    return dirs
+
+
+@pytest.mark.skipif(
+    sys.version_info >= (3, 13),
+    reason="pathlib accepts absolute glob patterns on 3.13+, so the crash is 3.12-only",
+)
+def test_resolve_reload_patterns_crashes_on_missing_absolute_dir(tmp_path):
+    """The exact #3454 failure: absolute exclude + missing dir on Python 3.12."""
+    missing = tmp_path / "sandbox"  # absolute path that does not exist yet
+    assert not missing.exists()
+    with pytest.raises(NotImplementedError):
+        resolve_reload_patterns([str(missing)], [])
+
+
+def test_resolve_reload_patterns_is_safe_once_dir_exists(tmp_path):
+    """The fix's mechanism: a pre-created dir takes uvicorn's is_dir() path."""
+    sandbox = tmp_path / "sandbox"
+    sandbox.mkdir()
+    _patterns, directories = resolve_reload_patterns([str(sandbox)], [])
+    resolved = {d.resolve() for d in directories}
+    assert sandbox.resolve() in resolved
+
+
+@pytest.mark.parametrize("name", list(LAUNCHERS))
+def test_launcher_precreates_every_absolute_reload_exclude(name):
+    """Every absolute ``--reload-exclude`` dir must be created by ``mkdir`` first.
+
+    Relative glob patterns (``*.pyc``, ``__pycache__``) are safe and skipped;
+    anything anchored at ``/`` or a shell variable is an absolute path that
+    uvicorn would glob — and crash on — unless it already exists. Membership is
+    an exact match against the parsed ``mkdir`` argument set (not a substring
+    test), so a path-prefix can't produce a false pass.
+    """
+    script = LAUNCHERS[name].read_text(encoding="utf-8")
+    created = _mkdir_dirs(script)
+
+    absolute_excludes = [v for v in _reload_exclude_values(script) if v.startswith(("/", "$"))]
+    assert absolute_excludes, f"{name}: expected at least one absolute reload-exclude"
+
+    for value in absolute_excludes:
+        assert value in created, f"{name}: absolute reload-exclude {value!r} is never created via mkdir (created dirs: {sorted(created)})"
+
+
+@pytest.mark.parametrize("name", list(LAUNCHERS))
+def test_sandbox_mkdir_precedes_uvicorn_launch(name):
+    """The sandbox mkdir must come before the uvicorn launch, not just exist.
+
+    ``_mkdir_dirs`` only proves the mkdir is present somewhere; this pins script
+    order so a future edit can't move (or guard) the mkdir below the launch and
+    silently reintroduce the #3454 crash on a fresh checkout. ``uv run uvicorn``
+    matches the launch but not serve.sh's ``stop_all`` kill line.
+    """
+    lines = LAUNCHERS[name].read_text(encoding="utf-8").splitlines()
+    launch_idx = next((i for i, ln in enumerate(lines) if "uv run uvicorn" in ln), None)
+    mkdir_idx = next((i for i, ln in enumerate(lines) if re.search(r"\bmkdir\b", ln) and "sandbox" in ln), None)
+
+    assert launch_idx is not None, f"{name}: could not locate the 'uv run uvicorn' launch line"
+    assert mkdir_idx is not None, f"{name}: could not locate the sandbox mkdir line"
+    assert mkdir_idx < launch_idx, f"{name}: sandbox mkdir (line {mkdir_idx + 1}) must precede uvicorn launch (line {launch_idx + 1})"
+
+
+def test_precreated_sandbox_artifacts_are_gitignored():
+    """backend/sandbox is runtime state — its contents must stay out of git so
+    sandbox artifacts can't be accidentally committed (matches the reload-exclude
+    intent). A content path is existence-independent, unlike the bare dir path.
+
+    Guards against the inaccurate "gitignored" claim by making it verifiable.
+    """
+    probe = "backend/sandbox/__artifact_probe__"
+    result = subprocess.run(
+        ["git", "-C", str(REPO_ROOT), "check-ignore", "-q", probe],
+        capture_output=True,
+    )
+    if result.returncode == 128:  # not a git checkout (e.g. packaged install)
+        pytest.skip("not inside a git working tree")
+    assert result.returncode == 0, "backend/sandbox/* should be gitignored (see backend/.gitignore '/sandbox/')"