feat: add public wiki embeds and ES query routing

.gitignore

@@ -95,12 +95,15 @@ offline-backend-20260512/backend/tests/*
 !offline-backend-20260512/backend/tests/test_model_management.py
 # Keep fixed-question exact-match and streaming regression coverage versioned.
 !offline-backend-20260512/backend/tests/test_fixed_questions.py
+# Keep configurable es_query system-prompt routing regression coverage versioned.
+!offline-backend-20260512/backend/tests/test_es_query_routing_prompt.py
 # Keep the local LLMWiki vector-index and external API regression coverage versioned.
 !offline-backend-20260512/backend/tests/test_llmwiki_local_index_repository.py
 !offline-backend-20260512/backend/tests/test_llmwiki_vector_search.py
 !offline-backend-20260512/backend/tests/test_llmwiki_wiki_sync.py
 !offline-backend-20260512/backend/tests/test_external_llmwiki_search.py
 !offline-backend-20260512/backend/tests/test_llmwiki_wiki_retrieval.py
+!offline-backend-20260512/backend/tests/test_public_llmwiki_embed.py
 # Deep-research reliability regression coverage.
 !offline-backend-20260512/backend/tests/test_deep_research_persistence.py
 !offline-backend-20260512/backend/tests/test_deep_research_event_sink.py

frontend-web/src/App.tsx

@@ -38,6 +38,7 @@ import EmbedChatPage from "./pages/EmbedChatPage";
 import EmbedRoundtablePage from "./pages/EmbedRoundtablePage";
 import DashboardStandalonePage from "@/roundtable-planning/pages/DashboardStandalonePage";
 import PositionRoundtablePage from "@/position-roundtable/pages/PositionRoundtablePage";
+import WeKnoraWikiPageView from "@/strategy-components/components/resource-management/llmwiki/WeKnoraWikiPageView";
 import {
   isPositionRoundtableStandaloneMode,
   POSITION_ROUNDTABLE_ROUTE,
@@ -45,7 +46,12 @@ import {
 import { ChatRuntime } from "./pages/WorkspaceRoutes";
 import { NotFoundPage } from "./pages/NotFoundPage";
 
-const PUBLIC_EMBED_PREFIXES = ["/share/", "/public/", "/roundtable-share/"];
+const PUBLIC_EMBED_PREFIXES = [
+  "/share/",
+  "/public/",
+  "/roundtable-share/",
+  "/embed/knowledge/",
+];
 
 function AppProviders({ children }: { children: React.ReactNode }) {
   const locale = useMemo(() => detectLocale(), []);
@@ -189,6 +195,10 @@ export function App() {
             }
           />
           <Route path="/embed/roundtable" element={<EmbedRoundtablePage />} />
+          <Route
+            path="/embed/knowledge/:noteId"
+            element={<WeKnoraWikiPageView publicEmbed />}
+          />
           <Route
             path="/roundtable-dashboard"
             element={<DashboardStandalonePage />}

frontend-web/src/core/llmwiki/source-links.ts

@@ -114,6 +114,24 @@ export function buildWeKnoraWikiPagePath(
   return `/page/workspace/knowledge/${encodeURIComponent(knowledgeBaseId)}/wiki/view?${params.toString()}`;
 }
 
+/** Public, chrome-free Wiki reader intended for third-party iframe embedding. */
+export function buildPublicKnowledgeWikiPath(
+  knowledgeBaseId: string,
+  wikiSlug?: string,
+): string {
+  const params = new URLSearchParams();
+  if (wikiSlug) params.set("wikiSlug", wikiSlug);
+  const query = params.toString();
+  return `/embed/knowledge/${encodeURIComponent(knowledgeBaseId)}${query ? `?${query}` : ""}`;
+}
+
+export function buildPublicKnowledgeWikiUrl(
+  knowledgeBaseId: string,
+  wikiSlug?: string,
+): string {
+  return `/#${buildPublicKnowledgeWikiPath(knowledgeBaseId, wikiSlug)}`;
+}
+
 export function buildLegacyKnowledgeSourceUrl(source: KnowledgeSourceLike): string {
   const recUuid = source.recUuid || source.rec_uuid || source.url || "";
   if (!recUuid) return "";

frontend-web/src/core/llmwiki/wiki-page-markdown.ts

@@ -1,5 +1,10 @@
 import { buildWeKnoraWikiPageUrl } from "@/core/llmwiki/source-links";
 
+export type WikiPageUrlBuilder = (
+  knowledgeBaseId: string,
+  wikiSlug: string,
+) => string;
+
 export function stripWikiFrontmatter(value: string) {
   return value.replace(/^\s*---\s*\n[\s\S]*?\n---\s*(?:\n|$)/, "").trim();
 }
@@ -16,12 +21,16 @@ export function exportableWikiMarkdown(title: string, summary: string, content:
     .join("\n\n");
 }
 
-export function wikiLinkMarkdown(markdown: string, knowledgeBaseId: string) {
+export function wikiLinkMarkdown(
+  markdown: string,
+  knowledgeBaseId: string,
+  buildPageUrl: WikiPageUrlBuilder = buildWeKnoraWikiPageUrl,
+) {
   const link = (slugValue: string, labelValue?: string) => {
     const slug = slugValue.trim();
     const fallbackLabel = slug.split("/").filter(Boolean).at(-1) || slug;
     const label = (labelValue || fallbackLabel).trim().replace(/\]/g, "\\]");
-    return `[${label}](${buildWeKnoraWikiPageUrl(knowledgeBaseId, slug)})`;
+    return `[${label}](${buildPageUrl(knowledgeBaseId, slug)})`;
   };
   return markdown
     .replace(/\[\[([^\]|]+)\|([^\]]+)\]\]/g, (_match, slug, label) => link(slug, label))
@@ -33,6 +42,7 @@ export function renderableWikiMarkdown(
   title: string,
   content: string,
   knowledgeBaseId: string,
+  buildPageUrl?: WikiPageUrlBuilder,
 ) {
   const lines = content.trim().split("\n");
   if (lines[0]?.replace(/^#+\s*/, "").trim() === title.trim()) {
@@ -41,5 +51,6 @@ export function renderableWikiMarkdown(
   return wikiLinkMarkdown(
     exportableWikiMarkdown(title, "", lines.join("\n")),
     knowledgeBaseId,
+    buildPageUrl,
   );
 }

frontend-web/src/strategy-components/api/llmwiki.ts

@@ -5,6 +5,7 @@ import { useLiveAccount } from "@/core/auth/use-live-account";
 import { getBackendBaseURL } from "@/core/config";
 
 const API = () => `${getBackendBaseURL()}/api/llmwiki`;
+const PUBLIC_API = () => `${getBackendBaseURL()}/api/public/llmwiki`;
 const SETTINGS_API = () => `${getBackendBaseURL()}/api/system-settings/llmwiki`;
 
 export type LlmWikiProvider = "legacy" | "weknora";
@@ -671,6 +672,44 @@ export async function searchLlmWiki(input: {
   );
 }
 
+export async function getPublicLlmWikiKnowledgeBase(
+  id: string,
+): Promise<LlmWikiKnowledgeBase> {
+  return readJson(
+    await apiFetch(`${PUBLIC_API()}/knowledge-bases/${encodeURIComponent(id)}`),
+    "读取公开知识库详情",
+  );
+}
+
+export async function listPublicLlmWikiWikiPages(
+  knowledgeBaseId: string,
+  page: number,
+  pageSize: number,
+  query = "",
+): Promise<LlmWikiWikiPageList> {
+  const params = new URLSearchParams({ page: String(page), page_size: String(pageSize) });
+  if (query.trim()) params.set("query", query.trim());
+  return readJson(
+    await apiFetch(
+      `${PUBLIC_API()}/knowledge-bases/${encodeURIComponent(knowledgeBaseId)}/wiki/pages?${params.toString()}`,
+    ),
+    "读取公开 Wiki 页面",
+  );
+}
+
+export async function getPublicLlmWikiWikiPage(
+  knowledgeBaseId: string,
+  slug: string,
+): Promise<LlmWikiWikiPage> {
+  const safeSlug = slug.split("/").map(encodeURIComponent).join("/");
+  return readJson(
+    await apiFetch(
+      `${PUBLIC_API()}/knowledge-bases/${encodeURIComponent(knowledgeBaseId)}/wiki/pages/${safeSlug}`,
+    ),
+    "读取公开 Wiki 页面详情",
+  );
+}
+
 export async function createLlmWikiConversationDeposit(input: {
   thread_id: string;
   question: string;
@@ -860,6 +899,46 @@ export function useLlmWikiWikiPage(
   });
 }
 
+export function usePublicLlmWikiKnowledgeBase(
+  knowledgeBaseId: string | null,
+  enabled = true,
+) {
+  return useQuery({
+    queryKey: ["public-llmwiki", "knowledge-base", knowledgeBaseId],
+    queryFn: () => getPublicLlmWikiKnowledgeBase(knowledgeBaseId!),
+    enabled: enabled && !!knowledgeBaseId,
+    staleTime: 60_000,
+  });
+}
+
+export function usePublicLlmWikiWikiPages(
+  knowledgeBaseId: string | null,
+  page: number,
+  pageSize = 50,
+  query = "",
+  enabled = true,
+) {
+  return useQuery({
+    queryKey: ["public-llmwiki", "wiki-pages", knowledgeBaseId, page, pageSize, query],
+    queryFn: () => listPublicLlmWikiWikiPages(knowledgeBaseId!, page, pageSize, query),
+    enabled: enabled && !!knowledgeBaseId,
+    staleTime: 60_000,
+  });
+}
+
+export function usePublicLlmWikiWikiPage(
+  knowledgeBaseId: string | null,
+  slug: string | null,
+  enabled = true,
+) {
+  return useQuery({
+    queryKey: ["public-llmwiki", "wiki-page", knowledgeBaseId, slug],
+    queryFn: () => getPublicLlmWikiWikiPage(knowledgeBaseId!, slug!),
+    enabled: enabled && !!knowledgeBaseId && !!slug,
+    staleTime: 60_000,
+  });
+}
+
 export function useLlmWikiWikiIndexStatus(
   knowledgeBaseId: string | null,
   enabled = true,

frontend-web/src/strategy-components/components/resource-management/llmwiki/WeKnoraWikiPageView.tsx

@@ -18,12 +18,16 @@ import { Badge } from "@/components/ui/badge";
 import { Button } from "@/components/ui/button";
 import { Input } from "@/components/ui/input";
 import { MarkdownContent } from "@/components/workspace/messages/markdown-content";
-import { buildWeKnoraWikiPagePath } from "@/core/llmwiki/source-links";
+import {
+  buildPublicKnowledgeWikiPath,
+  buildWeKnoraWikiPagePath,
+} from "@/core/llmwiki/source-links";
 import {
   buildWikiTree,
   filterWikiPagesWithAncestors,
   type WikiTreeNode,
 } from "@/core/llmwiki/wiki-tree";
+import { usePublicBackground } from "@/core/embed/background";
 import { reasoningPlugins } from "@/core/streamdown";
 import { markdownToDocxBlob } from "@/core/scheduled-tasks/markdown-docx";
 import {
@@ -38,6 +42,9 @@ import {
   useLlmWikiKnowledgeBase,
   useLlmWikiWikiPage,
   useLlmWikiWikiPages,
+  usePublicLlmWikiKnowledgeBase,
+  usePublicLlmWikiWikiPage,
+  usePublicLlmWikiWikiPages,
 } from "@/strategy-components/api/llmwiki";
 
 const LIST_PATH = "/page/workspace/knowledge";
@@ -85,27 +92,84 @@ function downloadBlob(blob: Blob, fileName: string) {
   window.setTimeout(() => URL.revokeObjectURL(url), 30_000);
 }
 
-export function WeKnoraWikiPageView() {
+function selectLandingPage(pages: LlmWikiWikiPage[]): LlmWikiWikiPage | undefined {
+  return (
+    pages.find((page) => page.page_type?.toLowerCase() === "overview") ||
+    pages.find((page) => /^(?:index|home|readme)$/i.test(page.slug)) ||
+    pages.find((page) => !page.parent_slug && (page.depth ?? 0) === 0) ||
+    pages[0]
+  );
+}
+
+export function WeKnoraWikiPageView({
+  publicEmbed = false,
+}: {
+  publicEmbed?: boolean;
+}) {
   const { noteId = "" } = useParams();
   const [searchParams] = useSearchParams();
   const location = useLocation();
   const navigate = useNavigate();
-  const wikiSlug = searchParams.get("wikiSlug")?.trim() || "";
-  const page = useLlmWikiWikiPage(noteId || null, wikiSlug || null, !!noteId && !!wikiSlug);
-  const knowledgeBase = useLlmWikiKnowledgeBase(noteId || null, !!noteId);
-  const pages = useLlmWikiWikiPages(noteId || null, 1, 500, "", !!noteId);
+  const publicBackground = usePublicBackground();
+  const requestedWikiSlug = searchParams.get("wikiSlug")?.trim() || "";
+  const privateKnowledgeBase = useLlmWikiKnowledgeBase(
+    noteId || null,
+    !!noteId && !publicEmbed,
+  );
+  const publicKnowledgeBase = usePublicLlmWikiKnowledgeBase(
+    noteId || null,
+    !!noteId && publicEmbed,
+  );
+  const knowledgeBase = publicEmbed ? publicKnowledgeBase : privateKnowledgeBase;
+  const privatePages = useLlmWikiWikiPages(
+    noteId || null,
+    1,
+    500,
+    "",
+    !!noteId && !publicEmbed,
+  );
+  const publicPages = usePublicLlmWikiWikiPages(
+    noteId || null,
+    1,
+    500,
+    "",
+    !!noteId && publicEmbed,
+  );
+  const pages = publicEmbed ? publicPages : privatePages;
+  const pagesList = useMemo(() => pages.data?.pages || [], [pages.data?.pages]);
+  const landingPage = useMemo(() => selectLandingPage(pagesList), [pagesList]);
+  const wikiSlug = requestedWikiSlug || (publicEmbed ? landingPage?.slug || "" : "");
+  const privatePage = useLlmWikiWikiPage(
+    noteId || null,
+    wikiSlug || null,
+    !!noteId && !!wikiSlug && !publicEmbed,
+  );
+  const publicPage = usePublicLlmWikiWikiPage(
+    noteId || null,
+    wikiSlug || null,
+    !!noteId && !!wikiSlug && publicEmbed,
+  );
+  const page = publicEmbed ? publicPage : privatePage;
   const [downloading, setDownloading] = useState<"md" | "word" | null>(null);
   const [directoryQuery, setDirectoryQuery] = useState("");
   const [collapsedDirectories, setCollapsedDirectories] = useState<Set<string>>(() => new Set());
   const routedPage = (location.state as { wikiPage?: LlmWikiWikiPage } | null)?.wikiPage;
   const pageData = page.data || (routedPage?.slug === wikiSlug ? routedPage : undefined);
-  const pagesList = useMemo(() => pages.data?.pages || [], [pages.data?.pages]);
   const filteredPages = useMemo(
     () => filterWikiPagesWithAncestors(pagesList, directoryQuery),
     [directoryQuery, pagesList],
   );
   const wikiTree = useMemo(() => buildWikiTree(filteredPages), [filteredPages]);
 
+  useEffect(() => {
+    if (!publicEmbed || requestedWikiSlug || !wikiSlug) return;
+    const next = new URLSearchParams(searchParams);
+    next.set("wikiSlug", wikiSlug);
+    navigate(`${buildPublicKnowledgeWikiPath(noteId)}?${next.toString()}`, {
+      replace: true,
+    });
+  }, [navigate, noteId, publicEmbed, requestedWikiSlug, searchParams, wikiSlug]);
+
   useEffect(() => {
     const activeParents = wikiTree.parentKeysBySlug.get(wikiSlug) || [];
     if (activeParents.length === 0) return;
@@ -121,7 +185,18 @@ export function WeKnoraWikiPageView() {
   const summary = cleanText(pageData?.summary);
   const content = stripWikiFrontmatter(cleanText(pageData?.content));
   const displayMarkdown = pageData
-    ? renderableWikiMarkdown(title, content, noteId)
+    ? renderableWikiMarkdown(
+        title,
+        content,
+        noteId,
+        publicEmbed
+          ? (knowledgeBaseId, slug) => {
+              const next = new URLSearchParams(searchParams);
+              next.set("wikiSlug", slug);
+              return `/#${buildPublicKnowledgeWikiPath(knowledgeBaseId)}?${next.toString()}`;
+            }
+          : undefined,
+      )
     : "";
   const exportMarkdown = pageData
     ? wikiLinkMarkdown(exportableWikiMarkdown(title, summary, content), noteId)
@@ -189,7 +264,15 @@ export function WeKnoraWikiPageView() {
           )}
           {node.page ? (
             <Link
-              to={buildWeKnoraWikiPagePath(noteId, node.page.slug)}
+              to={
+                publicEmbed
+                  ? (() => {
+                      const next = new URLSearchParams(searchParams);
+                      next.set("wikiSlug", node.page.slug);
+                      return `${buildPublicKnowledgeWikiPath(noteId)}?${next.toString()}`;
+                    })()
+                  : buildWeKnoraWikiPagePath(noteId, node.page.slug)
+              }
               state={{ wikiPage: node.page }}
               className="flex min-w-0 flex-1 items-center gap-2 py-2"
               aria-current={active ? "page" : undefined}
@@ -219,10 +302,20 @@ export function WeKnoraWikiPageView() {
   };
 
   if (!wikiSlug) {
+    if (publicEmbed && pages.isLoading) {
+      return (
+        <div className="flex h-full items-center justify-center text-sm text-muted-foreground">
+          <Loader2 className="mr-2 size-5 animate-spin" />
+          正在加载公开 Wiki
+        </div>
+      );
+    }
     return (
       <div className="flex h-full flex-col items-center justify-center gap-4 text-sm text-muted-foreground">
-        当前链接缺少 Wiki 页面标识
-        <Button variant="outline" onClick={() => navigate(LIST_PATH)}>返回知识库</Button>
+        {publicEmbed ? "该知识库暂无可展示的 Wiki 页面" : "当前链接缺少 Wiki 页面标识"}
+        {!publicEmbed && (
+          <Button variant="outline" onClick={() => navigate(LIST_PATH)}>返回知识库</Button>
+        )}
       </div>
     );
   }
@@ -245,11 +338,17 @@ export function WeKnoraWikiPageView() {
         <div>
           <div className="font-medium text-foreground">无法打开 Wiki 页面</div>
           <div className="mt-1 text-sm text-muted-foreground">
-            {page.error instanceof Error ? page.error.message : "页面不存在或当前账号无权访问"}
+            {page.error instanceof Error
+              ? page.error.message
+              : publicEmbed
+                ? "知识库未发布、页面不存在或已停止公开访问"
+                : "页面不存在或当前账号无权访问"}
           </div>
         </div>
         <div className="flex gap-2">
-          <Button variant="outline" onClick={() => navigate(LIST_PATH)}>返回知识库</Button>
+          {!publicEmbed && (
+            <Button variant="outline" onClick={() => navigate(LIST_PATH)}>返回知识库</Button>
+          )}
           <Button onClick={() => void page.refetch()}>
             <RefreshCw className="mr-2 size-4" />重试
           </Button>
@@ -259,7 +358,27 @@ export function WeKnoraWikiPageView() {
   }
 
   return (
-    <div className="flex h-full min-h-0 flex-col bg-slate-50/70 dark:bg-slate-950/40">
+    <div
+      className="flex h-full min-h-0 flex-col bg-slate-50/70 dark:bg-slate-950/40"
+      style={publicEmbed ? publicBackground : undefined}
+      data-public-wiki-embed={publicEmbed ? "true" : undefined}
+    >
+      {publicEmbed ? (
+        <header className="flex min-h-14 shrink-0 items-center gap-3 border-b bg-background/95 px-4 py-2.5 shadow-sm sm:px-6">
+          <div className="flex size-9 shrink-0 items-center justify-center rounded-xl bg-emerald-100 text-emerald-700 dark:bg-emerald-950 dark:text-emerald-300">
+            <BookOpenText className="size-4.5" />
+          </div>
+          <div className="min-w-0 flex-1">
+            <h1 className="truncate text-sm font-semibold text-foreground">
+              {knowledgeBase.data?.name || "知识库 Wiki"}
+            </h1>
+            <p className="mt-0.5 truncate text-xs text-muted-foreground">{title}</p>
+          </div>
+          <Badge variant="outline" className="shrink-0 border-emerald-200 text-emerald-700 dark:border-emerald-800 dark:text-emerald-300">
+            公开 Wiki
+          </Badge>
+        </header>
+      ) : (
       <header className="flex shrink-0 flex-wrap items-center justify-between gap-3 border-b bg-background px-4 py-3 shadow-sm sm:px-6">
         <div className="flex min-w-0 flex-1 items-center gap-3">
           <Button size="icon-sm" variant="ghost" onClick={() => navigate(LIST_PATH)} aria-label="返回知识库">
@@ -290,6 +409,7 @@ export function WeKnoraWikiPageView() {
           </Button>
         </div>
       </header>
+      )}
 
       <div className="flex min-h-0 flex-1 overflow-hidden">
         <aside className="flex w-64 shrink-0 flex-col border-r bg-background/90 lg:w-72">

offline-backend-20260512/backend/CLAUDE.md

@@ -719,6 +719,13 @@ Operators upgrading an existing DB run the whole file (`USE <db>;` then execute)
 - **Loading**: `load_skills()` recursively scans `skills/{public,custom}` for `SKILL.md`, parses metadata, and reads enabled state from extensions_config.json. **A directory containing `SKILL.md` is a self-contained leaf** — discovery does not descend into its subdirectories, so a skill *package* that bundles its own `examples/`/`references/` sub-skills (each with a SKILL.md) surfaces as **one** skill, not a swarm of phantom entries.
 - **Discovery↔delete consistency**: a skill is keyed for discovery by its frontmatter `name`, but its on-disk directory name may differ (hand-dropped / mis-extracted package). `LocalSkillStorage._resolve_skill_dir(name, category)` resolves the *discovered* directory (canonical `<category>/<name>` fast-path, else scan-by-frontmatter-name); `custom_skill_exists`/`read_custom_skill`/`delete_custom_skill` all go through it, so **anything that gets listed can also be read and deleted** regardless of directory name (the old code assumed `custom/<name>/` and 404'd "Custom skill 'x' not found." on any non-canonical layout). Delete is path-guarded to never escape the `custom/` root. Tests: `tests/test_skill_storage_delete.py`.
 - **Injection**: Enabled skills listed in agent system prompt with container paths
+- **Configurable `es_query` routing prompt**: `config.yaml → skills.es_query_routing`
+  contains an `enabled` switch and editable `prompt`. When enabled,
+  `lead_agent.prompt._build_es_query_routing_section` injects the rule into the
+  default lead-agent system prompt. Custom-agent-only prompts receive it only
+  when their explicit skill allowlist contains `es_query`; disabling the switch
+  or leaving the prompt blank emits no block. Tests:
+  `tests/test_es_query_routing_prompt.py`.
 - **Installation**: `POST /api/skills/install` extracts .skill ZIP archive to custom/ directory
 - **Installable sentiment analysis package**: `skill-packages/sentiment-analysis.skill` is deliberately separate from the existing frontend virtual-agent path. Its self-contained `config/sentiment-agent.json` owns the external AG-UI address; Basic Auth is resolved from `SENTIMENT_AGENT_AUTH_USERNAME` / `SENTIMENT_AGENT_AUTH_PASSWORD` at runtime (not committed into the package). `scripts/sentiment_stream.py` uses only the Python standard library and converts upstream SSE to stable NDJSON events (`thinking_delta`, `answer_delta`, `done`), with a Markdown convenience mode for normal agent calls. Installation/calling guide: `skill-packages/sentiment-analysis/docs/调用与安装说明.md`.
 - **Chinese name (`name_zh`)**: a Chinese display name stored in the **`skills` DB table** (`SkillRow.name_zh`, `String(128)`, migration `20260609_01`) ? never written to the on-disk SKILL.md, so it works for built-in skills too. Threaded through `SkillStore` create/ensure_legacy/update/update_admin exactly like `detail`; surfaced on `SkillResponse.name_zh` from the ownership record in `_skill_to_response`. Authorization mirrors `detail`: custom skill ? owner or admin; built-in/public ? admin only (row materialized on demand via `ensure_legacy`). Endpoints (in `app/gateway/routers/skills.py`): `PUT /api/skills/{name}/name-zh` (set/clear), `POST /api/skills/{name}/name-zh/generate` (LLM generates one), `POST /api/skills/name-zh/generate-missing` (????: **admin-only** bulk-generate for every skill that lacks one, bounded-concurrency `asyncio.gather`). **Optional model selection**: both generate endpoints accept an optional JSON body `{model_name}` ? an explicit name wins, else the curator model setting, else the main model (`_resolve_skill_name_zh_model_name`). **Model-error surfacing**: `_generate_skill_name_zh` raises `SkillNameZhModelError` when the model itself fails (build/timeout/API error) ? distinct from the model returning an unusable name (? `None`). The single endpoint maps that to `502 ?????,?????????:?`; the bulk endpoint fails fast on a model-build error (502) and otherwise carries a representative `model_error` string in `SkillNameZhBulkResponse` so the UI can say "N ?????????". The frontend (`skill-settings-page.tsx` list + `skill-detail-dialog.tsx` editor, plus the agent skill pickers/badges in `NewAgentPage.tsx` + `agent-card.tsx`) shows `name_zh || name`, offers per-skill "AI ??" plus an **admin-only** header "???????" button, and a compact model dropdown (`components/workspace/model-name-select.tsx`, default = configured model) beside each action.
@@ -1471,6 +1478,17 @@ Wiki directory, reconstruct hierarchy from `parent_slug`, `wiki_path`,
 directory navigation on the same lightweight route rather than mounting the
 WeKnora iframe.
 
+Third-party pages embed published Wiki content through the chrome-free route
+`/#/embed/knowledge/{mapping_id}` (optional exact-page `wikiSlug`). It defaults
+to an overview/root Wiki page, retains directory navigation, and supports the
+shared public-embed `theme` / `bg` / `text` appearance inputs. All anonymous
+reader calls use `/api/public/llmwiki/knowledge-bases/{id}` and its Wiki-page
+children. Those endpoints must resolve the mapping with a synthetic anonymous
+user and `is_admin=False`, explicitly require `publication_status=published`,
+and hard-deny the system conversation-deposit mapping. Never point this page at
+the authenticated `/api/llmwiki` reads or weaken the published-only gate merely
+because the mapping id is hard to guess.
+
 Owners manually force a full sync/vectorization through `POST
 /api/llmwiki/knowledge-bases/{id}/vectorize`; status is available through `GET
 /api/llmwiki/knowledge-bases/{id}/wiki-index-status`. The Wiki management page

offline-backend-20260512/backend/README.md

@@ -504,7 +504,9 @@ Key sections:
 - `tools` - Tool definitions with module paths and groups
 - `tool_groups` - Logical tool groupings
 - `sandbox` - Execution environment provider
-- `skills` - Skills directory paths
+- `skills` - Skills directory paths plus optional prompt routing; `skills.es_query_routing`
+  can inject an editable system-prompt rule that sends flexible Elasticsearch Query DSL
+  requests to the `es_query` skill, and can be disabled without changing code
 - `title` - Auto-title generation settings
 - `summarization` - Context summarization settings
 - `subagents` - Subagent system (enabled/disabled)
@@ -810,6 +812,16 @@ left. It reconstructs hierarchy from `parent_slug`, `wiki_path`,
 page, and switches directory entries through the same lightweight reader route
 without mounting the WeKnora iframe.
 
+Published knowledge bases also have a login-free, chrome-free reader at
+`/#/embed/knowledge/{mapping_id}` for direct third-party iframe use. With no
+`wikiSlug`, it selects an overview/root page and keeps directory navigation
+inside the embed route; `?wikiSlug=...` deep-links one page. The reader supports
+`theme=light|dark`, `bg`, and `text` embed appearance parameters. Its data comes
+only from the read-only `/api/public/llmwiki/knowledge-bases/{id}/...` namespace,
+which rechecks `publication_status=published` on every request and denies the
+system conversation-deposit knowledge base. Private or unpublished bases are
+never exposed by this route.
+
 Wiki management also provides **导出 Excel**. `GET
 /api/llmwiki/knowledge-bases/{id}/wiki/export.xlsx` exports every processed Wiki
 page, including its full directory path, current directory, parent-directory

offline-backend-20260512/backend/app/gateway/routers/llmwiki.py

@@ -1778,6 +1778,24 @@ async def _authorized_mapping(
     return row, user_id, is_admin
 
 
+async def _public_mapping(request: Request, mapping_id: str) -> dict[str, Any]:
+    """Resolve a world-readable knowledge base without inheriting actor/admin state."""
+
+    row = await _store(request).get_authorized(
+        mapping_id,
+        "__public_wiki__",
+        write=False,
+        is_admin=False,
+    )
+    if (
+        row is None
+        or row.get("publication_status") != "published"
+        or _is_conversation_deposit_mapping(row)
+    ):
+        raise HTTPException(status_code=404, detail="Published knowledge base not found")
+    return row
+
+
 async def _verify_document(client: WeKnoraClient, row: dict[str, Any], document_id: str) -> dict[str, Any]:
     document = await client.get_document(document_id)
     if str(document.get("knowledge_base_id") or "") != str(row["weknora_id"]):
@@ -2399,6 +2417,70 @@ async def test_llmwiki_connection(request: Request, body: LlmWikiConnectionTest)
     return {"success": True, "provider": "weknora", "health": health}
 
 
+@router.get("/api/public/llmwiki/knowledge-bases/{mapping_id}")
+async def get_public_knowledge_base(request: Request, mapping_id: str) -> dict[str, Any]:
+    """Return the safe public metadata used by the chrome-free Wiki reader."""
+
+    row = await _public_mapping(request, mapping_id)
+    try:
+        remote = await _client_or_503().get_knowledge_base(str(row["weknora_id"]))
+    except WeKnoraError as exc:
+        _raise_upstream(exc)
+    return _mapping_view(
+        row,
+        remote,
+        actor_user_id="__public_wiki__",
+        is_admin=False,
+    )
+
+
+@router.get("/api/public/llmwiki/knowledge-bases/{mapping_id}/wiki/pages")
+async def list_public_wiki_pages(
+    request: Request,
+    mapping_id: str,
+    page: int = Query(default=1, ge=1),
+    page_size: int = Query(default=50, ge=1, le=500),
+    query: str = Query(default="", max_length=255),
+) -> dict[str, Any]:
+    """List Wiki pages for a published knowledge base without requiring login."""
+
+    row = await _public_mapping(request, mapping_id)
+    try:
+        result = await _client_or_503().list_wiki_pages(
+            str(row["weknora_id"]),
+            page=page,
+            page_size=page_size,
+            query=query.strip(),
+        )
+    except WeKnoraError as exc:
+        _raise_upstream(exc)
+    raw_pages = result.get("pages") if isinstance(result, dict) else []
+    pages = [
+        view
+        for page_item in (raw_pages if isinstance(raw_pages, list) else [])
+        if isinstance(page_item, dict)
+        for view in [_wiki_page_view(page_item)]
+        if view is not None
+    ]
+    return {**result, "pages": pages}
+
+
+@router.get("/api/public/llmwiki/knowledge-bases/{mapping_id}/wiki/pages/{slug:path}")
+async def get_public_wiki_page(
+    request: Request,
+    mapping_id: str,
+    slug: str,
+) -> dict[str, Any]:
+    """Read one Wiki article from a published knowledge base."""
+
+    row = await _public_mapping(request, mapping_id)
+    try:
+        page = await _client_or_503().get_wiki_page(str(row["weknora_id"]), slug)
+    except WeKnoraError as exc:
+        _raise_upstream(exc)
+    return _wiki_page_view(page) or page
+
+
 @router.get("/api/llmwiki/knowledge-bases")
 async def list_knowledge_bases(
     request: Request,

offline-backend-20260512/backend/config.yaml

@@ -372,6 +372,15 @@ skills:
   path: skills
   security_scan:
     enabled: false
+  # ES 灵活查询技能路由提示：开启后注入整体 system prompt；修改 prompt 可调整
+  # 触发边界和调用要求。关闭后该提示完全不注入。
+  es_query_routing:
+    enabled: true
+    prompt: |
+      当用户的问题需要基于 Elasticsearch 查询语句（Query DSL）灵活构造、调整或执行查询时，必须优先使用 `es_query` 技能。
+      典型场景包括：根据用户条件动态组合 bool/must/filter/should、范围、聚合、排序或分页等 ES 查询；或者用户直接提供、要求修改 ES 语句并据此查询数据。
+      执行前先读取 `es_query` 技能的 SKILL.md，严格按照技能中的流程和参数调用；不要用通用搜索替代，也不要凭记忆臆测查询结果。
+      仅当问题确实需要 ES 数据查询时使用；纯概念解释、普通代码说明或与 ES 无关的问题不要调用。
 
 skill_evolution:
   enabled: true

offline-backend-20260512/backend/docs/CONFIGURATION.md

@@ -270,9 +270,21 @@ skills:
   # Host path (optional, default: ../skills)
   path: /custom/path/to/skills
 
-  # Container mount path (default: /mnt/skills)
-  container_path: /mnt/skills
-```
+  # Container mount path (default: /mnt/skills)
+  container_path: /mnt/skills
+  # Optional system-prompt routing rule for the es_query skill
+  es_query_routing:
+    enabled: true
+    prompt: |
+      当用户的问题需要基于 Elasticsearch Query DSL 灵活构造、调整或执行查询时，优先使用 `es_query` 技能。
+      执行前先读取该技能的 SKILL.md，并严格遵循其中的流程和参数。
+```
+
+`skills.es_query_routing.enabled` controls whether the routing rule is injected
+into the overall agent system prompt. Edit `prompt` to tune the matching boundary
+or invocation requirements. When disabled (the schema default), the block is not
+injected. Custom agents receive it only when their explicit skill allowlist
+contains `es_query`.
 
 **How Skills Work**:
 - Skills are stored in `deer-flow/skills/{public,custom}/`

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

@@ -271,7 +271,42 @@ answers — and never create a skill silently without user confirmation.
 """
 
 
-def _build_available_subagents_description(available_names: list[str], bash_available: bool, *, app_config: AppConfig | None = None) -> str:
+def _build_es_query_routing_section(
+    *,
+    app_config: AppConfig | None = None,
+    available_skills: set[str] | None = None,
+) -> str:
+    """Return the configurable ``es_query`` routing rule for the system prompt.
+
+    A custom agent with an explicit skill allowlist only receives the rule when
+    ``es_query`` is in that allowlist. The default lead agent has no allowlist,
+    so the operator-controlled config switch is authoritative there.
+    """
+    if available_skills is not None and "es_query" not in available_skills:
+        return ""
+
+    config = app_config
+    if config is None:
+        try:
+            from deerflow.config import get_app_config
+
+            config = get_app_config()
+        except Exception:
+            logger.debug("Failed to load es_query routing config", exc_info=True)
+            return ""
+
+    routing = getattr(getattr(config, "skills", None), "es_query_routing", None)
+    if routing is None or not routing.enabled:
+        return ""
+
+    prompt = (routing.prompt or "").strip()
+    if not prompt:
+        return ""
+
+    return f'<skill_routing skill="es_query">\n{prompt}\n</skill_routing>'
+
+
+def _build_available_subagents_description(available_names: list[str], bash_available: bool, *, app_config: AppConfig | None = None) -> str:
     """Dynamically build subagent type descriptions from registry.
 
     Mirrors Codex's pattern where agent_type_description is dynamically generated
@@ -548,9 +583,11 @@ User: "staging"
 You: "Deploying to staging..." [proceed]
 </clarification_system>
 
-{skills_section}
-
-{bootstrap_section}
+{skills_section}
+
+{es_query_routing_section}
+
+{bootstrap_section}
 
 {deferred_tools_section}
 
@@ -663,10 +700,12 @@ combined with a FastAPI gateway for REST API access [citation:FastAPI](https://f
 # style, clarification system, citation rules, response-style / critical-reminder
 # defaults) and no personal memory injection. Only the mechanical sections an
 # agent still needs to actually use its configured skills/tools are kept.
-AGENT_ONLY_PROMPT_TEMPLATE = """{soul}
-{network_policy_section}{skills_section}
-
-{deferred_tools_section}
+AGENT_ONLY_PROMPT_TEMPLATE = """{soul}
+{network_policy_section}{skills_section}
+
+{es_query_routing_section}
+
+{deferred_tools_section}
 
 {writing_mode_section}
 
@@ -719,12 +758,16 @@ def apply_agent_only_prompt_template(
 
     soul = get_agent_soul(storage_agent_id)
 
-    skills_section = get_skills_prompt_section(
-        available_skills,
-        app_config=app_config,
-        display_enabled=rag_mode_enabled,
-    )
-    deferred_tools_section = get_deferred_tools_prompt_section(app_config=app_config)
+    skills_section = get_skills_prompt_section(
+        available_skills,
+        app_config=app_config,
+        display_enabled=rag_mode_enabled,
+    )
+    es_query_routing_section = _build_es_query_routing_section(
+        app_config=app_config,
+        available_skills=available_skills,
+    )
+    deferred_tools_section = get_deferred_tools_prompt_section(app_config=app_config)
 
     n = max_concurrent_subagents
     subagent_section = _build_subagent_section(n, app_config=app_config) if subagent_enabled else ""
@@ -766,9 +809,10 @@ RAG/reference display mode is enabled.
     )
 
     prompt = AGENT_ONLY_PROMPT_TEMPLATE.format(
-        soul=soul,
-        skills_section=skills_section,
-        deferred_tools_section=deferred_tools_section,
+        soul=soul,
+        skills_section=skills_section,
+        es_query_routing_section=es_query_routing_section,
+        deferred_tools_section=deferred_tools_section,
         writing_mode_section=writing_mode_section,
         subagent_section=subagent_section,
         network_policy_section=network_policy_section,
@@ -1377,11 +1421,15 @@ def apply_prompt_template(
     bootstrap_section = _build_bootstrap_section() if is_bootstrap else ""
 
     # Get skills section
-    skills_section = get_skills_prompt_section(
-        available_skills,
-        app_config=app_config,
-        display_enabled=rag_mode_enabled,
-    )
+    skills_section = get_skills_prompt_section(
+        available_skills,
+        app_config=app_config,
+        display_enabled=rag_mode_enabled,
+    )
+    es_query_routing_section = _build_es_query_routing_section(
+        app_config=app_config,
+        available_skills=available_skills,
+    )
 
     # Get deferred tools section (tool_search)
     deferred_tools_section = get_deferred_tools_prompt_section(app_config=app_config)
@@ -1438,9 +1486,10 @@ When a search, knowledge, skill, or MCP tool returns a result list:
     # Format the prompt with dynamic skills and memory
     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,
-        bootstrap_section=bootstrap_section,
+        soul=get_agent_soul(storage_agent_id),
+        skills_section=skills_section,
+        es_query_routing_section=es_query_routing_section,
+        bootstrap_section=bootstrap_section,
         deferred_tools_section=deferred_tools_section,
         writing_mode_section=writing_mode_section,
         memory_context=memory_context,

offline-backend-20260512/backend/packages/harness/deerflow/config/skills_config.py

@@ -5,8 +5,26 @@ from pydantic import BaseModel, Field
 
 from deerflow.config.runtime_paths import project_root, resolve_path
 
-
-class SecurityScanConfig(BaseModel):
+DEFAULT_ES_QUERY_ROUTING_PROMPT = """当用户的问题需要基于 Elasticsearch 查询语句（Query DSL）灵活构造、调整或执行查询时，必须优先使用 `es_query` 技能。
+典型场景包括：根据用户条件动态组合 bool/must/filter/should、范围、聚合、排序或分页等 ES 查询；或者用户直接提供、要求修改 ES 语句并据此查询数据。
+执行前先读取 `es_query` 技能的 SKILL.md，严格按照技能中的流程和参数调用；不要用通用搜索替代，也不要凭记忆臆测查询结果。
+仅当问题确实需要 ES 数据查询时使用；纯概念解释、普通代码说明或与 ES 无关的问题不要调用。"""
+
+
+class EsQueryRoutingConfig(BaseModel):
+    """Prompt steering that routes flexible Elasticsearch queries to ``es_query``."""
+
+    enabled: bool = Field(
+        default=False,
+        description="Inject the es_query routing prompt into the agent system prompt.",
+    )
+    prompt: str = Field(
+        default=DEFAULT_ES_QUERY_ROUTING_PROMPT,
+        description="Editable system-prompt instructions for deciding when and how to use es_query.",
+    )
+
+
+class SecurityScanConfig(BaseModel):
     """Toggle for the LLM-based skill security scanner."""
 
     enabled: bool = Field(
@@ -33,10 +51,14 @@ class SkillsConfig(BaseModel):
         default="/mnt/skills",
         description="Path where skills are mounted in the sandbox container",
     )
-    security_scan: SecurityScanConfig = Field(
-        default_factory=SecurityScanConfig,
-        description="LLM security-scan toggle for skill content.",
-    )
+    security_scan: SecurityScanConfig = Field(
+        default_factory=SecurityScanConfig,
+        description="LLM security-scan toggle for skill content.",
+    )
+    es_query_routing: EsQueryRoutingConfig = Field(
+        default_factory=EsQueryRoutingConfig,
+        description="Optional configurable routing prompt for the es_query skill.",
+    )
 
     def get_skills_path(self) -> Path:
         """

offline-backend-20260512/backend/tests/test_es_query_routing_prompt.py

@@ -0,0 +1,70 @@
+from types import SimpleNamespace
+
+from deerflow.agents.lead_agent import prompt as prompt_module
+from deerflow.config.skills_config import EsQueryRoutingConfig, SkillsConfig
+
+
+def _app_config(*, enabled: bool, prompt: str = "自定义 ES 路由规则") -> SimpleNamespace:
+    return SimpleNamespace(
+        skills=SkillsConfig(
+            es_query_routing=EsQueryRoutingConfig(enabled=enabled, prompt=prompt),
+        )
+    )
+
+
+def test_es_query_routing_config_is_disabled_by_default() -> None:
+    config = SkillsConfig()
+
+    assert config.es_query_routing.enabled is False
+    assert "es_query" in config.es_query_routing.prompt
+
+
+def test_es_query_routing_section_honors_switch_prompt_and_allowlist() -> None:
+    enabled = _app_config(enabled=True, prompt="  自定义 ES 路由规则  ")
+
+    assert prompt_module._build_es_query_routing_section(app_config=enabled) == (
+        '<skill_routing skill="es_query">\n自定义 ES 路由规则\n</skill_routing>'
+    )
+    assert (
+        prompt_module._build_es_query_routing_section(
+            app_config=enabled,
+            available_skills={"other_skill"},
+        )
+        == ""
+    )
+    assert "自定义 ES 路由规则" in prompt_module._build_es_query_routing_section(
+        app_config=enabled,
+        available_skills={"es_query"},
+    )
+    assert prompt_module._build_es_query_routing_section(app_config=_app_config(enabled=False)) == ""
+    assert prompt_module._build_es_query_routing_section(app_config=_app_config(enabled=True, prompt="  ")) == ""
+
+
+def test_es_query_routing_is_injected_into_lead_and_allowed_custom_agent_prompts(monkeypatch) -> None:
+    config = _app_config(enabled=True)
+    monkeypatch.setattr(prompt_module, "_get_memory_context", lambda *args, **kwargs: "")
+    monkeypatch.setattr(prompt_module, "get_agent_soul", lambda *args, **kwargs: "")
+    monkeypatch.setattr(prompt_module, "get_skills_prompt_section", lambda *args, **kwargs: "<skill_system />")
+    monkeypatch.setattr(prompt_module, "get_deferred_tools_prompt_section", lambda *args, **kwargs: "")
+    monkeypatch.setattr(prompt_module, "_build_acp_section", lambda *args, **kwargs: "")
+    monkeypatch.setattr(prompt_module, "_build_custom_mounts_section", lambda *args, **kwargs: "")
+    monkeypatch.setattr(prompt_module, "_current_time_context", lambda: "")
+
+    lead_prompt = prompt_module.apply_prompt_template(app_config=config)
+    allowed_custom_prompt = prompt_module.apply_agent_only_prompt_template(
+        agent_id="agent-with-es",
+        agent_name="Agent with ES",
+        available_skills={"es_query"},
+        app_config=config,
+    )
+    denied_custom_prompt = prompt_module.apply_agent_only_prompt_template(
+        agent_id="agent-without-es",
+        agent_name="Agent without ES",
+        available_skills={"other_skill"},
+        app_config=config,
+    )
+
+    assert '<skill_routing skill="es_query">' in lead_prompt
+    assert "自定义 ES 路由规则" in lead_prompt
+    assert '<skill_routing skill="es_query">' in allowed_custom_prompt
+    assert '<skill_routing skill="es_query">' not in denied_custom_prompt

offline-backend-20260512/backend/tests/test_public_llmwiki_embed.py

@@ -0,0 +1,128 @@
+from __future__ import annotations
+
+from types import SimpleNamespace
+
+import pytest
+from fastapi import HTTPException
+from starlette.requests import Request
+
+from app.gateway.routers import llmwiki
+
+
+def _request(store: object) -> Request:
+    return Request(
+        {
+            "type": "http",
+            "method": "GET",
+            "path": "/api/public/llmwiki/knowledge-bases/kb-one",
+            "headers": [],
+            "app": SimpleNamespace(state=SimpleNamespace(llmwiki_store=store)),
+        }
+    )
+
+
+class PublicStore:
+    def __init__(self, row: dict[str, object] | None) -> None:
+        self.row = row
+        self.calls: list[tuple[str, str, bool, bool]] = []
+
+    async def get_authorized(
+        self,
+        mapping_id: str,
+        user_id: str,
+        *,
+        write: bool,
+        is_admin: bool,
+    ) -> dict[str, object] | None:
+        self.calls.append((mapping_id, user_id, write, is_admin))
+        return self.row
+
+
+def _published_row() -> dict[str, object]:
+    return {
+        "id": "kb-one",
+        "weknora_id": "remote-one",
+        "owner_user_id": "owner-one",
+        "name": "公开知识库",
+        "description": "公开说明",
+        "kb_type": "document",
+        "publication_status": "published",
+    }
+
+
+@pytest.mark.asyncio
+async def test_public_wiki_reader_uses_anonymous_non_admin_authorization(monkeypatch) -> None:
+    store = PublicStore(_published_row())
+
+    class Client:
+        async def get_knowledge_base(self, knowledge_base_id: str):
+            assert knowledge_base_id == "remote-one"
+            return {"id": knowledge_base_id, "name": "公开知识库", "knowledge_count": 2}
+
+    monkeypatch.setattr(llmwiki, "_client_or_503", lambda: Client())
+
+    payload = await llmwiki.get_public_knowledge_base(_request(store), "kb-one")
+
+    assert store.calls == [("kb-one", "__public_wiki__", False, False)]
+    assert payload["publication_status"] == "published"
+    assert payload["owner_user_id"] is None
+    assert payload["can_write"] is False
+
+
+@pytest.mark.asyncio
+@pytest.mark.parametrize(
+    "row",
+    [
+        {**_published_row(), "publication_status": "private"},
+        {
+            **_published_row(),
+            "owner_user_id": "system",
+            "name": "对话沉淀",
+        },
+        None,
+    ],
+)
+async def test_public_wiki_reader_rejects_non_public_resources(row) -> None:
+    with pytest.raises(HTTPException) as exc_info:
+        await llmwiki._public_mapping(_request(PublicStore(row)), "kb-one")
+
+    assert exc_info.value.status_code == 404
+
+
+@pytest.mark.asyncio
+async def test_public_wiki_page_list_is_normalized(monkeypatch) -> None:
+    store = PublicStore(_published_row())
+
+    class Client:
+        async def list_wiki_pages(self, knowledge_base_id: str, **kwargs):
+            assert knowledge_base_id == "remote-one"
+            assert kwargs == {"page": 1, "page_size": 50, "query": "目录"}
+            return {
+                "pages": [
+                    {
+                        "id": "page-one",
+                        "slug": "guide/start",
+                        "title": "开始使用",
+                        "page_type": "article",
+                        "status": "completed",
+                        "content": "# 开始使用",
+                    }
+                ],
+                "total": 1,
+                "page": 1,
+                "page_size": 50,
+                "total_pages": 1,
+            }
+
+    monkeypatch.setattr(llmwiki, "_client_or_503", lambda: Client())
+
+    payload = await llmwiki.list_public_wiki_pages(
+        _request(store),
+        "kb-one",
+        page=1,
+        page_size=50,
+        query=" 目录 ",
+    )
+
+    assert payload["pages"][0]["slug"] == "guide/start"
+    assert payload["pages"][0]["aliases"] == []

offline-backend-20260512/config.yaml

@@ -190,6 +190,15 @@ skills:
   path: /app/skills
   security_scan:
     enabled: false
+  # ES 灵活查询技能路由提示：开启后注入整体 system prompt；修改 prompt 可调整
+  # 触发边界和调用要求。关闭后该提示完全不注入。
+  es_query_routing:
+    enabled: true
+    prompt: |
+      当用户的问题需要基于 Elasticsearch 查询语句（Query DSL）灵活构造、调整或执行查询时，必须优先使用 `es_query` 技能。
+      典型场景包括：根据用户条件动态组合 bool/must/filter/should、范围、聚合、排序或分页等 ES 查询；或者用户直接提供、要求修改 ES 语句并据此查询数据。
+      执行前先读取 `es_query` 技能的 SKILL.md，严格按照技能中的流程和参数调用；不要用通用搜索替代，也不要凭记忆臆测查询结果。
+      仅当问题确实需要 ES 数据查询时使用；纯概念解释、普通代码说明或与 ES 无关的问题不要调用。
 agents_api:
   enabled: true
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