@

feat(skills): skill_list 可见性过滤 + skill 只读工具常驻 + 进化面板对照展示

- skill_list:默认 lead agent 改为只暴露未归档、且内置或属于当前用户的技能;
  自定义 agent 仍严格按白名单。SkillStore 不可用时降级放行全部自定义技能。
- prompt:注入系统提示词的技能列表剔除已归档(state=archived)技能。
- tools:skill_list/skill_view 只读工具改为常驻提供;skill_manage 写工具仍按
  生效配置(含 per-user 覆盖)的 skill_evolution.enabled 门控。
- curator:should_run_now 解析异常时改为不运行;get_curator_status 返回上次
  LLM 建议与实际工具调用两份记录,供前端对照。
- 前端:技能进化面板新增建议 vs 实际动作对照展示 + 配套 i18n。

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
@

frontend-web/src/components/workspace/skills/skill-evolution-panel.tsx

@@ -154,6 +154,73 @@ function StatusCard() {
                 </span>
               </span>
             </StatRow>
+            <StatRow label={tt.lastActions} className="sm:col-span-2">
+              <div className="flex flex-col gap-2 text-xs">
+                <div>
+                  <div className="font-medium">{tt.llmSuggested}</div>
+                  {status.last_consolidation_suggestions.consolidations.length ===
+                    0 &&
+                  status.last_consolidation_suggestions.prunings.length === 0 ? (
+                    <span className="text-muted-foreground">
+                      {tt.noActions}
+                    </span>
+                  ) : (
+                    <ul className="text-muted-foreground mt-0.5 list-disc pl-4">
+                      {status.last_consolidation_suggestions.consolidations.map(
+                        (c, i) => (
+                          <li key={`c${i}`}>
+                            {(c.from ?? "?") + " → " + (c.into ?? "?")}
+                            {c.reason ? `（${c.reason}）` : ""}
+                          </li>
+                        ),
+                      )}
+                      {status.last_consolidation_suggestions.prunings.map(
+                        (p, i) => (
+                          <li key={`p${i}`}>
+                            {p.name ?? "?"}
+                            {p.reason ? `（${p.reason}）` : ""}
+                          </li>
+                        ),
+                      )}
+                    </ul>
+                  )}
+                </div>
+                <div>
+                  <div className="font-medium">{tt.actuallyDid}</div>
+                  {status.last_actual_actions.length === 0 ? (
+                    <span className="text-muted-foreground">
+                      {tt.noActions}
+                    </span>
+                  ) : (
+                    <ul className="mt-0.5 flex flex-col gap-1">
+                      {status.last_actual_actions.map((a, i) => (
+                        <li
+                          key={i}
+                          className="flex flex-wrap items-center gap-1.5"
+                        >
+                          <span className="font-mono">{a.tool ?? "?"}</span>
+                          {typeof a.args?.name === "string" && (
+                            <span className="text-muted-foreground">
+                              {String(a.args.name)}
+                            </span>
+                          )}
+                          <Badge
+                            variant={
+                              a.status === "error"
+                                ? "destructive"
+                                : "secondary"
+                            }
+                            className="px-1 text-[10px]"
+                          >
+                            {a.status}
+                          </Badge>
+                        </li>
+                      ))}
+                    </ul>
+                  )}
+                </div>
+              </div>
+            </StatRow>
           </div>
         ) : null}
       </CardContent>

frontend-web/src/core/curator/types.ts

@@ -11,6 +11,29 @@ export interface CuratorConfig {
   curator: CuratorSubConfig;
 }
 
+export interface CuratorAction {
+  tool: string | null;
+  args: Record<string, unknown>;
+  status: string;
+  result: string;
+}
+
+export interface CuratorConsolidation {
+  from?: string;
+  into?: string;
+  reason?: string;
+}
+
+export interface CuratorPruning {
+  name?: string;
+  reason?: string;
+}
+
+export interface CuratorSuggestions {
+  consolidations: CuratorConsolidation[];
+  prunings: CuratorPruning[];
+}
+
 export interface CuratorStatus {
   enabled: boolean;
   run_count: number;
@@ -23,6 +46,10 @@ export interface CuratorStatus {
     stale: number;
     archived: number;
   };
+  /** 上次运行 LLM 自述的建议(它"说"要做什么)。 */
+  last_consolidation_suggestions: CuratorSuggestions;
+  /** 上次运行的真实工具调用记录(它"实际"做了什么)。 */
+  last_actual_actions: CuratorAction[];
 }
 
 export interface CuratorLogRecord {

frontend-web/src/core/i18n/locales/en-US.ts

@@ -557,6 +557,10 @@ export const enUS: Translations = {
         total: "Total",
         runNow: "Run now",
         runStarted: "Background run started",
+        lastActions: "Last run",
+        llmSuggested: "LLM suggested (self-report)",
+        actuallyDid: "Actually done (tool calls)",
+        noActions: "None",
       },
       config: {
         title: "Configuration",

frontend-web/src/core/i18n/locales/types.ts

@@ -482,6 +482,10 @@ export interface Translations {
         total: string;
         runNow: string;
         runStarted: string;
+        lastActions: string;
+        llmSuggested: string;
+        actuallyDid: string;
+        noActions: string;
       };
       config: {
         title: string;

frontend-web/src/core/i18n/locales/zh-CN.ts

@@ -533,6 +533,10 @@ export const zhCN: Translations = {
         total: "合计",
         runNow: "立即执行",
         runStarted: "已触发后台执行",
+        lastActions: "最近一次运行",
+        llmSuggested: "LLM 建议（自述）",
+        actuallyDid: "实际执行（工具调用）",
+        noActions: "无",
       },
       config: {
         title: "配置",

offline-backend-20260512/backend/packages/harness/deerflow/agents/lead_agent/prompt.py

@@ -69,8 +69,25 @@ _enabled_skills_refresh_version = 0
 _enabled_skills_refresh_event = threading.Event()
 
 
+def _drop_archived_skills(skills: list[Skill]) -> list[Skill]:
+    """从注入提示词的技能列表里剔除已归档(usage state=archived)的技能。
+
+    技能归档是软状态:SKILL.md 仍留在 custom/<name>/、enabled 标志不变,所以
+    load_skills(enabled_only=True) 仍会返回它。但归档技能不应再出现在 agent 的系统
+    提示词里 —— 对 agent 而言它应等同于"不存在"。失败时不过滤(返回原列表)。
+    """
+    try:
+        from deerflow.skills.usage import STATE_ARCHIVED, all_entries
+
+        entries = all_entries()
+        return [s for s in skills if entries.get(s.name, {}).get("state") != STATE_ARCHIVED]
+    except Exception:
+        logger.debug("Failed to filter archived skills for prompt injection", exc_info=True)
+        return skills
+
+
 def _load_enabled_skills_sync() -> list[Skill]:
-    return list(get_or_new_skill_storage().load_skills(enabled_only=True))
+    return _drop_archived_skills(list(get_or_new_skill_storage().load_skills(enabled_only=True)))
 
 
 def _start_enabled_skills_refresh_thread() -> None:
@@ -171,7 +188,7 @@ def _get_enabled_skills_for_config(app_config: AppConfig | None = None) -> list[
     """
     if app_config is None:
         return _get_enabled_skills()
-    return list(get_or_new_skill_storage(app_config=app_config).load_skills(enabled_only=True))
+    return _drop_archived_skills(list(get_or_new_skill_storage(app_config=app_config).load_skills(enabled_only=True)))
 
 
 def _skill_mutability_label(category: SkillCategory | str) -> str:
@@ -479,11 +496,11 @@ You: "Deploying to staging..." [proceed]
 
 {skills_section}
 
-{deferred_tools_section}
-
-{writing_mode_section}
-
-{subagent_section}
+{deferred_tools_section}
+
+{writing_mode_section}
+
+{subagent_section}
 
 <working_directory existed="true">
 - User uploads: `/mnt/user-data/uploads` - Files uploaded by the user (automatically listed in context)
@@ -796,17 +813,17 @@ def _build_custom_mounts_section(*, app_config: AppConfig | None = None) -> str:
     return f"\n**Custom Mounted Directories:**\n{mounts_list}\n- If the user needs files outside `/mnt/user-data`, use these absolute container paths directly when they match the requested directory"
 
 
-def apply_prompt_template(
-    subagent_enabled: bool = False,
-    max_concurrent_subagents: int = 3,
-    *,
-    agent_id: str | None = None,
-    agent_name: str | None = None,
-    writing_mode: bool = False,
-    writing_artifact_path: str | None = None,
-    available_skills: set[str] | None = None,
-    app_config: AppConfig | None = None,
-) -> str:
+def apply_prompt_template(
+    subagent_enabled: bool = False,
+    max_concurrent_subagents: int = 3,
+    *,
+    agent_id: str | None = None,
+    agent_name: str | None = None,
+    writing_mode: bool = False,
+    writing_artifact_path: str | None = None,
+    available_skills: set[str] | None = None,
+    app_config: AppConfig | None = None,
+) -> str:
     storage_agent_id = agent_id if agent_id is not None else agent_name
 
     # Get memory context
@@ -838,33 +855,33 @@ def apply_prompt_template(
     skills_section = get_skills_prompt_section(available_skills, app_config=app_config)
 
     # Get deferred tools section (tool_search)
-    deferred_tools_section = get_deferred_tools_prompt_section(app_config=app_config)
-    current_writing_artifact = (
-        f"\n**Current Markdown Artifact**\n- Continue editing this existing Markdown file unless the user explicitly asks for a new document: `{writing_artifact_path}`\n"
-        if writing_artifact_path
-        else ""
-    )
-    writing_mode_section = (
-        f"""
-<writing_mode>
-Writing mode is enabled for this run.
-
-**Mandatory Output Contract**
-- Treat the user's request as a writing/report-generation task.
-- Your final deliverable MUST be a Markdown file, not only an inline chat answer.
-- If a current Markdown artifact is provided below, you MUST revise that existing file rather than creating a new file, unless the user explicitly asks for a separate/new document.
-- When revising an existing Markdown artifact, read the file first if needed, then overwrite the same path with the complete updated Markdown content.
-- Write the deliverable to `/mnt/user-data/outputs/` with a clear `.md` filename, for example `/mnt/user-data/outputs/report.md`.
-- Use `write_file` or an equivalent file-writing tool to save the complete Markdown content.
-- After writing the file, call `present_files` with the Markdown file path so the user can open it as an artifact/canvas.
-- The final chat response should be brief and point to the generated Markdown artifact. Do not duplicate the full report inline unless the user explicitly asks.
-- If you revise an existing Markdown artifact, update the Markdown file and present it again.
-{current_writing_artifact}
-</writing_mode>
-"""
-        if writing_mode
-        else ""
-    )
+    deferred_tools_section = get_deferred_tools_prompt_section(app_config=app_config)
+    current_writing_artifact = (
+        f"\n**Current Markdown Artifact**\n- Continue editing this existing Markdown file unless the user explicitly asks for a new document: `{writing_artifact_path}`\n"
+        if writing_artifact_path
+        else ""
+    )
+    writing_mode_section = (
+        f"""
+<writing_mode>
+Writing mode is enabled for this run.
+
+**Mandatory Output Contract**
+- Treat the user's request as a writing/report-generation task.
+- Your final deliverable MUST be a Markdown file, not only an inline chat answer.
+- If a current Markdown artifact is provided below, you MUST revise that existing file rather than creating a new file, unless the user explicitly asks for a separate/new document.
+- When revising an existing Markdown artifact, read the file first if needed, then overwrite the same path with the complete updated Markdown content.
+- Write the deliverable to `/mnt/user-data/outputs/` with a clear `.md` filename, for example `/mnt/user-data/outputs/report.md`.
+- Use `write_file` or an equivalent file-writing tool to save the complete Markdown content.
+- After writing the file, call `present_files` with the Markdown file path so the user can open it as an artifact/canvas.
+- The final chat response should be brief and point to the generated Markdown artifact. Do not duplicate the full report inline unless the user explicitly asks.
+- If you revise an existing Markdown artifact, update the Markdown file and present it again.
+{current_writing_artifact}
+</writing_mode>
+"""
+        if writing_mode
+        else ""
+    )
 
     # Build ACP agent section only if ACP agents are configured
     acp_section = _build_acp_section(app_config=app_config)
@@ -878,10 +895,10 @@ Writing mode is enabled for this run.
     prompt = SYSTEM_PROMPT_TEMPLATE.format(
         agent_name=agent_name or storage_agent_id or "CM 助手",
         soul=get_agent_soul(storage_agent_id),
-        skills_section=skills_section,
-        deferred_tools_section=deferred_tools_section,
-        writing_mode_section=writing_mode_section,
-        memory_context=memory_context,
+        skills_section=skills_section,
+        deferred_tools_section=deferred_tools_section,
+        writing_mode_section=writing_mode_section,
+        memory_context=memory_context,
         network_policy_section=network_policy_section,
         subagent_section=subagent_section,
         subagent_reminder=subagent_reminder,

offline-backend-20260512/backend/packages/harness/deerflow/skills/curator.py

@@ -278,7 +278,7 @@ def should_run_now(user_id: str) -> bool:
         last_dt = datetime.fromisoformat(last_run)
         return datetime.now(UTC) >= last_dt + timedelta(hours=interval_hours)
     except Exception:
-        return True
+        return False
 
 
 def apply_automatic_transitions(user_id: str, now: datetime | None = None) -> dict:
@@ -954,4 +954,8 @@ def get_curator_status(user_id: str) -> dict:
             "stale": counts[STATE_STALE],
             "archived": counts[STATE_ARCHIVED],
         },
+        # 上次运行的两份记录:LLM 自述的建议 + 实际发生的工具调用,供前端对照展示。
+        "last_consolidation_suggestions": state.get("last_consolidation_suggestions")
+        or {"consolidations": [], "prunings": []},
+        "last_actual_actions": state.get("last_actual_actions") or [],
     }

offline-backend-20260512/backend/packages/harness/deerflow/tools/builtins/skill_tools.py

@@ -59,6 +59,66 @@ def _load_agent_skill_whitelist(agent_id: str | None) -> set[str] | None:
         return None
 
 
+def _resolve_effective_user_id() -> str | None:
+    """当前请求/线程绑定的用户 id;解析失败时返回 None。"""
+    try:
+        from deerflow.runtime.user_context import get_effective_user_id
+
+        return get_effective_user_id()
+    except Exception:
+        logger.debug("Failed to resolve effective user id for skill_list", exc_info=True)
+        return None
+
+
+def _run_coro_blocking(coro):
+    """在同步工具里把一个协程跑到完成。
+
+    ``skill_list`` 是同步 ``@tool``:LangChain 通常在线程池里执行它(无运行中的
+    事件循环),但 curator 评审会在已有事件循环的线程里调用它。两种情况都要能
+    拿到 ``SkillStore`` 的异步查询结果 —— 检测到运行中的事件循环就转交独立线程
+    执行 ``asyncio.run``,否则直接跑。
+    """
+    import asyncio
+
+    try:
+        asyncio.get_running_loop()
+        in_loop = True
+    except RuntimeError:
+        in_loop = False
+
+    if in_loop:
+        import concurrent.futures
+
+        with concurrent.futures.ThreadPoolExecutor(max_workers=1) as pool:
+            return pool.submit(asyncio.run, coro).result()
+    return asyncio.run(coro)
+
+
+def _load_owned_skill_names(user_id: str | None) -> set[str] | None:
+    """返回 ``owner_user_id == user_id`` 的自定义技能名集合。
+
+    用于默认 lead agent 的可见性过滤:只算"用户自己拥有的"自定义技能,不含
+    其他用户发布的。返回 ``None`` 表示 ``SkillStore`` 不可用(未配置数据库
+    等)—— 调用方应降级为"放行全部自定义技能",避免离线无库部署下技能凭空
+    消失。
+    """
+    if not user_id:
+        return None
+    try:
+        from deerflow.persistence.engine import get_session_factory
+        from deerflow.persistence.skills import make_skill_store
+
+        factory = get_session_factory()
+        if factory is None:
+            return None
+        store = make_skill_store(factory)
+        records = _run_coro_blocking(store.list_visible(user_id))
+        return {r["name"] for r in records if r.get("owner_user_id") == user_id}
+    except Exception:
+        logger.debug("Failed to load owned skill names for skill_list filter", exc_info=True)
+        return None
+
+
 @tool("skill_view")
 def skill_view_tool(name: str) -> str:
     """Read the full SKILL.md content of a skill by name.
@@ -106,28 +166,47 @@ def skill_list_tool(runtime: ToolRuntime) -> str:
     under the ``skills:`` field — the agent only sees what it was wired to
     use.
 
-    For the **default lead agent** (no agent_id in runtime), there is no
-    per-agent whitelist and every visible skill is returned.
+    For the **default lead agent** (no agent_id in runtime), the result is
+    filtered to non-archived skills that are either built-in (public) or
+    owned by the current user. Other users' published custom skills and
+    archived skills are excluded.
 
     Returns a JSON array with fields: name, description, category, enabled,
     state, use_count, view_count, patch_count, last_activity_at, pinned,
     source.
     """
     from deerflow.skills.storage import get_or_new_skill_storage
-    from deerflow.skills.usage import all_entries, latest_activity_at
+    from deerflow.skills.types import SkillCategory
+    from deerflow.skills.usage import STATE_ARCHIVED, all_entries, latest_activity_at
 
     agent_id = _resolve_active_agent_id(runtime)
     allowed = _load_agent_skill_whitelist(agent_id)
 
+    # 默认 lead agent 没有 per-agent 白名单 —— 改为只暴露"未归档"且"内置或属于
+    # 当前用户"的技能。owned 为 None 表示 SkillStore 不可用,降级放行全部自定义
+    # 技能(见 _load_owned_skill_names)。
+    owned: set[str] | None = None
+    if allowed is None:
+        owned = _load_owned_skill_names(_resolve_effective_user_id())
+
     try:
         storage = get_or_new_skill_storage()
         skills = storage.load_skills(enabled_only=False)
         usage = all_entries()
         result = []
         for skill in skills:
-            if allowed is not None and skill.name not in allowed:
-                continue
             entry = usage.get(skill.name, {})
+            if allowed is not None:
+                # 自定义 agent:严格按 config.yaml 的 skills 白名单过滤。
+                if skill.name not in allowed:
+                    continue
+            else:
+                # 默认 agent:跳过已归档技能。
+                if entry.get("state") == STATE_ARCHIVED:
+                    continue
+                # 自定义技能仅当属于当前用户时可见;内置 public 技能始终可见。
+                if skill.category == SkillCategory.CUSTOM and owned is not None and skill.name not in owned:
+                    continue
             result.append({
                 "name": skill.name,
                 "description": skill.description,

offline-backend-20260512/backend/packages/harness/deerflow/tools/tools.py

@@ -84,12 +84,26 @@ def get_available_tools(
     builtin_tools = BUILTIN_TOOLS.copy()
     if not is_scheduled_run:
         builtin_tools.append(scheduled_task_tool)
-    skill_evolution_config = getattr(config, "skill_evolution", None)
+    # skill_list / skill_view 是只读工具(发现、查看技能),与"自我进化"写能力无关,
+    # 始终提供给 agent。
+    from deerflow.tools.builtins.skill_tools import skill_list_tool, skill_view_tool
+
+    builtin_tools.extend([skill_list_tool, skill_view_tool])
+
+    # skill_manage 能创建/修改/删除技能,属于"自我进化"写能力,按 skill_evolution.enabled
+    # 门控。该开关用户可在 per-user 配置里覆盖,所以按"生效配置(含 per-user 覆盖)"判断 ——
+    # Gateway 每次 run 重建 agent,用户改了配置下次 run 即生效;解析失败退回全局 config.yaml。
+    try:
+        from deerflow.config.skill_evolution_runtime import load_skill_evolution_config_for_user
+        from deerflow.runtime.user_context import get_effective_user_id
+
+        skill_evolution_config = load_skill_evolution_config_for_user(get_effective_user_id())
+    except Exception:  # noqa: BLE001 - 解析失败不能阻断 agent 构建
+        skill_evolution_config = getattr(config, "skill_evolution", None)
     if getattr(skill_evolution_config, "enabled", False):
-        from deerflow.tools.builtins.skill_tools import skill_list_tool, skill_view_tool
         from deerflow.tools.skill_manage_tool import skill_manage_tool
 
-        builtin_tools.extend([skill_list_tool, skill_view_tool, skill_manage_tool])
+        builtin_tools.append(skill_manage_tool)
 
     # Add subagent tools only if enabled via runtime parameter
     if subagent_enabled: