fix(skills): harden slash skill activation across chat channels (#3466)

* support slash skill activation

* format slash skill activation

* Preserve slash skill activation with uploads

* Address slash skill review feedback

* Address slash skill follow-up review

* Fix lazy slash skill storage resolution

* Keep slash skill activation out of system prompt

* Address slash skill review issues

* fix: harden slash skill command handling

* feat(frontend): add slash skill autocomplete

* fix: address slash skill review feedback

* fix: preserve slash skill text for IM uploads
This commit is contained in:
DanielWalnut
2026-06-09 23:07:17 +08:00
committed by GitHub
parent 18bbb82f07
commit 16391e35ab
31 changed files with 2758 additions and 57 deletions
@@ -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,
),
@@ -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}
@@ -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)
@@ -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