feat: add unified strategy project workflow

frontend-web/src/components/workspace/agents/agent-chat-sidebar.tsx

@@ -51,6 +51,10 @@ import {
   SelectValue,
 } from "@/components/ui/select";
 import { ShareConversationDialog } from "@/components/workspace/thread-share-dialogs";
+import {
+  MyProjectThreadBadge,
+  MyProjectThreadIcon,
+} from "@/components/workspace/my-project-thread-indicator";
 import { useTheme } from "@/contexts/ThemeContext";
 import { useAgentsPaginated } from "@/core/agents";
 import { getAPIClient } from "@/core/api";
@@ -69,6 +73,7 @@ import {
   useToggleThreadPin,
 } from "@/core/threads/hooks";
 import type { AgentThread, AgentThreadState } from "@/core/threads/types";
+import { myProjectConversationTypeOfThread } from "@/core/threads/project-metadata";
 import {
   bootstrapResumePath,
   isBootstrapThread,
@@ -479,6 +484,7 @@ function RecentChatsPane({ activeAgentId }: { activeAgentId?: string }) {
         ) : (
           filteredThreads.map((thread) => {
             const isBoot = isBootstrapThread(thread);
+            const projectType = myProjectConversationTypeOfThread(thread);
             const href = isBoot ? bootstrapResumePath(thread.thread_id) : pathOf(thread);
             const isActive = href === pathname;
             const pinned = isThreadPinned(thread);
@@ -505,6 +511,8 @@ function RecentChatsPane({ activeAgentId }: { activeAgentId?: string }) {
                       )}
                       aria-label="智能体创建会话"
                     />
+                  ) : projectType ? (
+                    <MyProjectThreadIcon type={projectType} />
                   ) : (
                     <MessageSquare
                       className={cn(
@@ -516,9 +524,15 @@ function RecentChatsPane({ activeAgentId }: { activeAgentId?: string }) {
                   {pinned && (
                     <Pin className="text-muted-foreground/70 size-3 shrink-0" />
                   )}
-                  <span className="truncate">
+                  <span className="min-w-0 flex-1 truncate">
                     {desensitize(titleOfThread(thread, t.pages.newChat))}
                   </span>
+                  {projectType && (
+                    <MyProjectThreadBadge
+                      className="mr-4"
+                      type={projectType}
+                    />
+                  )}
                   {isActive && (
                     <span className="absolute top-1/2 right-1 h-5 w-1 -translate-y-1/2 rounded-full bg-primary" />
                   )}

frontend-web/src/components/workspace/agents/agent-recent-chats.tsx

@@ -4,7 +4,12 @@ import { MessageSquareIcon } from "lucide-react";
 import Link from "next/link";
 import { usePathname } from "next/navigation";
 
+import {
+  MyProjectThreadBadge,
+  MyProjectThreadIcon,
+} from "@/components/workspace/my-project-thread-indicator";
 import { useThreadsPage } from "@/core/threads/hooks";
+import { myProjectConversationTypeOfThread } from "@/core/threads/project-metadata";
 import { pathOfThread, titleOfThread, isHiddenFromRecentChats, isBootstrapThread } from "@/core/threads/utils";
 import { desensitize } from "@/lib/desensitize";
 import { cn } from "@/lib/utils";
@@ -45,6 +50,7 @@ export function AgentRecentChats({ agentId }: { agentId: string }) {
           {threads.map((thread) => {
             const href = pathOfThread(thread);
             const isActive = href === pathname;
+            const projectType = myProjectConversationTypeOfThread(thread);
             return (
               <Link
                 key={thread.thread_id}
@@ -57,15 +63,20 @@ export function AgentRecentChats({ agentId }: { agentId: string }) {
                     : "text-muted-foreground hover:bg-accent hover:text-foreground",
                 )}
               >
-                <MessageSquareIcon
-                  className={cn(
-                    "size-3.5 shrink-0",
-                    isActive ? "text-primary" : "text-muted-foreground/70",
-                  )}
-                />
-                <span className="truncate">
+                {projectType ? (
+                  <MyProjectThreadIcon type={projectType} />
+                ) : (
+                  <MessageSquareIcon
+                    className={cn(
+                      "size-3.5 shrink-0",
+                      isActive ? "text-primary" : "text-muted-foreground/70",
+                    )}
+                  />
+                )}
+                <span className="min-w-0 flex-1 truncate">
                   {desensitize(titleOfThread(thread, "新对话"))}
                 </span>
+                {projectType && <MyProjectThreadBadge type={projectType} />}
               </Link>
             );
           })}

frontend-web/src/components/workspace/general-qa-sidebar.tsx

@@ -60,6 +60,10 @@ import {
 } from "@/components/ui/dropdown-menu";
 import { Input } from "@/components/ui/input";
 import { ShareConversationDialog } from "@/components/workspace/thread-share-dialogs";
+import {
+  MyProjectThreadBadge,
+  MyProjectThreadIcon,
+} from "@/components/workspace/my-project-thread-indicator";
 import { useAgentsPaginated, type Agent } from "@/core/agents";
 import { getAPIClient } from "@/core/api";
 import { useI18n } from "@/core/i18n/hooks";
@@ -75,6 +79,7 @@ import {
   useToggleThreadPin,
 } from "@/core/threads/hooks";
 import type { AgentThread, AgentThreadState } from "@/core/threads/types";
+import { myProjectConversationTypeOfThread } from "@/core/threads/project-metadata";
 import {
   isBootstrapThread,
   isHiddenFromRecentChats,
@@ -483,6 +488,7 @@ export function GeneralQaSidebar() {
                     );
                     const isActive = href === pathname;
                     const isBoot = isBootstrapThread(thread);
+                    const projectType = myProjectConversationTypeOfThread(thread);
                     const pinned = isThreadPinned(thread);
                     const favorited = isThreadFavorite(thread);
                     return (
@@ -507,6 +513,8 @@ export function GeneralQaSidebar() {
                               )}
                               aria-label="智能体创建会话"
                             />
+                          ) : projectType ? (
+                            <MyProjectThreadIcon type={projectType} />
                           ) : (
                             <MessageSquare
                               className={cn(
@@ -518,9 +526,15 @@ export function GeneralQaSidebar() {
                           {pinned && (
                             <Pin className="size-3 shrink-0 text-muted-foreground/70" />
                           )}
-                          <span className="truncate">
+                          <span className="min-w-0 flex-1 truncate">
                             {desensitize(titleOfThread(thread, t.pages.newChat))}
                           </span>
+                          {projectType && (
+                            <MyProjectThreadBadge
+                              className="mr-4"
+                              type={projectType}
+                            />
+                          )}
                           {isActive && (
                             <span className="absolute top-1/2 right-1 h-5 w-1 -translate-y-1/2 rounded-full bg-primary" />
                           )}

frontend-web/src/components/workspace/model-name-select.tsx

@@ -25,6 +25,7 @@ export function ModelNameSelect({
   className,
   triggerClassName,
   defaultLabel = "默认模型",
+  title = "选择用于本次操作的大模型(默认使用系统配置的模型)",
 }: {
   value: string | null;
   onChange: (modelName: string | null) => void;
@@ -32,6 +33,7 @@ export function ModelNameSelect({
   className?: string;
   triggerClassName?: string;
   defaultLabel?: string;
+  title?: string;
 }) {
   const { models } = useModels();
   return (
@@ -42,7 +44,7 @@ export function ModelNameSelect({
     >
       <SelectTrigger
         className={cn("h-8 gap-1.5 text-xs", triggerClassName, className)}
-        title="选择用于本次操作的大模型(默认使用系统配置的模型)"
+        title={title}
       >
         <SelectValue placeholder={defaultLabel} />
       </SelectTrigger>

frontend-web/src/components/workspace/my-project-thread-indicator.tsx

@@ -0,0 +1,51 @@
+import { FolderKanban } from "lucide-react";
+
+import {
+  MY_PROJECT_CONVERSATION_LABELS,
+  type MyProjectConversationType,
+} from "@/core/threads/project-metadata";
+import { cn } from "@/lib/utils";
+
+const BADGE_STYLES: Record<MyProjectConversationType, string> = {
+  qa: "border-sky-200 bg-sky-50 text-sky-700 dark:border-sky-700/70 dark:bg-sky-950/55 dark:text-sky-300",
+  strategy:
+    "border-violet-200 bg-violet-50 text-violet-700 dark:border-violet-700/70 dark:bg-violet-950/55 dark:text-violet-300",
+  solution:
+    "border-emerald-200 bg-emerald-50 text-emerald-700 dark:border-emerald-700/70 dark:bg-emerald-950/55 dark:text-emerald-300",
+};
+
+export function MyProjectThreadIcon({
+  type,
+  className,
+}: {
+  type: MyProjectConversationType;
+  className?: string;
+}) {
+  return (
+    <FolderKanban
+      aria-label={`我的项目 · ${MY_PROJECT_CONVERSATION_LABELS[type]}`}
+      className={cn("size-3.5 shrink-0 text-violet-500", className)}
+    />
+  );
+}
+
+export function MyProjectThreadBadge({
+  type,
+  className,
+}: {
+  type: MyProjectConversationType;
+  className?: string;
+}) {
+  return (
+    <span
+      className={cn(
+        "shrink-0 rounded border px-1 py-0.5 text-[9px] font-medium leading-none",
+        BADGE_STYLES[type],
+        className,
+      )}
+      title={`来自我的项目 · ${MY_PROJECT_CONVERSATION_LABELS[type]}`}
+    >
+      {MY_PROJECT_CONVERSATION_LABELS[type]}
+    </span>
+  );
+}

frontend-web/src/components/workspace/recent-chat-list.tsx

@@ -49,7 +49,11 @@ import {
   SidebarMenuButton,
   SidebarMenuItem,
 } from "@/components/ui/sidebar";
-import { ShareConversationDialog } from "@/components/workspace/thread-share-dialogs";
+import { ShareConversationDialog } from "@/components/workspace/thread-share-dialogs";
+import {
+  MyProjectThreadBadge,
+  MyProjectThreadIcon,
+} from "@/components/workspace/my-project-thread-indicator";
 import { getAPIClient } from "@/core/api";
 import { useI18n } from "@/core/i18n/hooks";
 import {
@@ -63,7 +67,8 @@ import {
   useToggleThreadFavorite,
   useToggleThreadPin,
 } from "@/core/threads/hooks";
-import type { AgentThread, AgentThreadState } from "@/core/threads/types";
+import type { AgentThread, AgentThreadState } from "@/core/threads/types";
+import { myProjectConversationTypeOfThread } from "@/core/threads/project-metadata";
 import {
   isBootstrapThread,
   isHiddenFromRecentChats,
@@ -245,7 +250,8 @@ export function RecentChatList({
               {shownThreads.map((thread) => {
                 const href = listPathOfThread(thread);
                 const isActive = href === pathname;
-                const isBoot = isBootstrapThread(thread);
+                const isBoot = isBootstrapThread(thread);
+                const projectType = myProjectConversationTypeOfThread(thread);
                 const pinned = isThreadPinned(thread);
                 const favorited = isThreadFavorite(thread);
                 return (
@@ -279,8 +285,10 @@ export function RecentChatList({
                             }
                             aria-label="智能体创建会话"
                           />
-                        ) : (
-                          compact && (
+                        ) : projectType ? (
+                          <MyProjectThreadIcon type={projectType} />
+                        ) : (
+                          compact && (
                             <MessageSquare
                               className={
                                 "size-3.5 shrink-0 " +
@@ -294,9 +302,15 @@ export function RecentChatList({
                         {pinned && (
                           <Pin className="size-3 shrink-0 text-muted-foreground/70" />
                         )}
-                        <span className="truncate">
-                          {desensitize(titleOfThread(thread, t.pages.newChat))}
-                        </span>
+                        <span className="min-w-0 flex-1 truncate">
+                          {desensitize(titleOfThread(thread, t.pages.newChat))}
+                        </span>
+                        {projectType && (
+                          <MyProjectThreadBadge
+                            className="mr-3"
+                            type={projectType}
+                          />
+                        )}
                       </Link>
                     </SidebarMenuButton>
                     {env.NEXT_PUBLIC_STATIC_WEBSITE_ONLY !== "true" && (

frontend-web/src/components/workspace/workspace-nav-chat-list.tsx

@@ -14,7 +14,7 @@ import {
   SidebarMenuItem,
 } from "@/components/ui/sidebar";
 import { useI18n } from "@/core/i18n/hooks";
-import { BookOpen, BotIcon, BrainIcon, FileSearch, FileText, Library, ListChecks, MessageSquarePlus, MessagesSquare, PenLine, Plus, SparklesIcon, Telescope, Users } from "lucide-react";
+import { BookOpen, BotIcon, BrainIcon, FileSearch, FileText, FolderKanban, Library, ListChecks, MessageSquarePlus, MessagesSquare, PenLine, Plus, SparklesIcon, Telescope, Users } from "lucide-react";
 
 import { KnowledgeRagToggle } from "./knowledge-rag-toggle";
 import { SidebarCollapseButton } from "./workspace-header";
@@ -65,6 +65,15 @@ export const WORKSPACE_COMPACT_NAV_ITEMS: WorkspaceCompactNavItem[] = [
     path: "/page/workspace/chats",
     match: (pathname) => pathname === "/page/workspace/chats",
   },
+  {
+    id: "strategy-projects",
+    label: "我的项目",
+    icon: FolderKanban,
+    path: "/page/strategy/qa/projects",
+    match: (pathname) =>
+      pathname.startsWith("/page/strategy/qa/projects") ||
+      pathname.startsWith("/page/strategy/qa/strategy-selection"),
+  },
   {
     id: "workspace-library",
     label: "资料库",

frontend-web/src/core/page-layout/sidebar-menu.ts

@@ -21,6 +21,7 @@ import {
   FileBox,
   FileSearch,
   FileText,
+  FolderKanban,
   Gauge,
   Grid3X3,
   HelpCircle,
@@ -69,10 +70,11 @@ export const sidebarMenuItems: MenuItem[] = [
         path: "/page/strategy/qa/multi-agent-roundtable",
       },
       {
-        id: "strategy-selection",
-        label: "策略优选",
-        icon: Sparkles,
-        path: "/page/strategy/qa/strategy-selection",
+        id: "strategy-projects",
+        label: "我的项目",
+        icon: FolderKanban,
+        path: "/page/strategy/qa/projects",
+        aliasPaths: ["/page/strategy/qa/strategy-selection"],
       },
       // {
       //   id: "position-roundtable",

frontend-web/src/core/threads/project-metadata.test.ts

@@ -0,0 +1,46 @@
+import assert from "node:assert/strict";
+import test from "node:test";
+
+import {
+  myProjectConversationTypeFromSearchParams,
+  myProjectConversationTypeOfThread,
+  myProjectThreadMetadata,
+  withMyProjectConversationMarker,
+} from "./project-metadata";
+
+test("project conversation type is read from persisted metadata", () => {
+  assert.equal(
+    myProjectConversationTypeOfThread({
+      metadata: myProjectThreadMetadata("strategy"),
+    }),
+    "strategy",
+  );
+  assert.equal(
+    myProjectConversationTypeOfThread({
+      metadata: { project_source: "elsewhere", project_type: "qa" },
+    }),
+    null,
+  );
+});
+
+test("metadata wins over the compatibility context fallback", () => {
+  assert.equal(
+    myProjectConversationTypeOfThread({
+      metadata: myProjectThreadMetadata("solution"),
+      context: myProjectThreadMetadata("qa"),
+    }),
+    "solution",
+  );
+});
+
+test("new-chat route marker round-trips all supported project types", () => {
+  for (const type of ["qa", "strategy", "solution"] as const) {
+    const path = withMyProjectConversationMarker(
+      "/page/strategy/chats/new?keep=1",
+      type,
+    );
+    const params = new URLSearchParams(path.split("?", 2)[1]);
+    assert.equal(params.get("keep"), "1");
+    assert.equal(myProjectConversationTypeFromSearchParams(params), type);
+  }
+});

frontend-web/src/core/threads/project-metadata.ts

@@ -0,0 +1,94 @@
+/**
+ * Stable marker for conversations entered from 「我的项目」.
+ *
+ * Keep this separate from ``project_id``: that key belongs to DeerFlow's
+ * folder-style conversation projects, while this marker describes the product
+ * mode that created (or explicitly continued) a conversation.
+ */
+export const MY_PROJECT_THREAD_SOURCE = "my-projects" as const;
+
+export const MY_PROJECT_THREAD_SOURCE_KEY = "project_source" as const;
+export const MY_PROJECT_THREAD_TYPE_KEY = "project_type" as const;
+
+export const MY_PROJECT_QUERY_SOURCE_KEY = "projectSource" as const;
+export const MY_PROJECT_QUERY_TYPE_KEY = "projectType" as const;
+
+export type MyProjectConversationType = "qa" | "strategy" | "solution";
+
+export const MY_PROJECT_CONVERSATION_LABELS: Record<
+  MyProjectConversationType,
+  string
+> = {
+  qa: "普通问答",
+  strategy: "策略优选",
+  solution: "方案生成",
+};
+
+const MY_PROJECT_CONVERSATION_TYPES = new Set<MyProjectConversationType>([
+  "qa",
+  "strategy",
+  "solution",
+]);
+
+function typeFromRecord(
+  value: Record<string, unknown> | null | undefined,
+): MyProjectConversationType | null {
+  if (value?.[MY_PROJECT_THREAD_SOURCE_KEY] !== MY_PROJECT_THREAD_SOURCE) {
+    return null;
+  }
+  const type = value[MY_PROJECT_THREAD_TYPE_KEY];
+  return typeof type === "string" &&
+    MY_PROJECT_CONVERSATION_TYPES.has(type as MyProjectConversationType)
+    ? (type as MyProjectConversationType)
+    : null;
+}
+
+export function myProjectThreadMetadata(
+  type: MyProjectConversationType,
+): Record<string, unknown> {
+  return {
+    [MY_PROJECT_THREAD_SOURCE_KEY]: MY_PROJECT_THREAD_SOURCE,
+    [MY_PROJECT_THREAD_TYPE_KEY]: type,
+  };
+}
+
+/** Read persisted metadata first; context is only a compatibility fallback. */
+export function myProjectConversationTypeOfThread(thread: {
+  metadata?: Record<string, unknown> | null;
+  context?: Record<string, unknown> | null;
+}): MyProjectConversationType | null {
+  return typeFromRecord(thread.metadata) ?? typeFromRecord(thread.context);
+}
+
+export function myProjectConversationTypeFromSearchParams(params: {
+  get(name: string): string | null;
+}): MyProjectConversationType | null {
+  if (params.get(MY_PROJECT_QUERY_SOURCE_KEY) !== MY_PROJECT_THREAD_SOURCE) {
+    return null;
+  }
+  const type = params.get(MY_PROJECT_QUERY_TYPE_KEY);
+  return typeof type === "string" &&
+    MY_PROJECT_CONVERSATION_TYPES.has(type as MyProjectConversationType)
+    ? (type as MyProjectConversationType)
+    : null;
+}
+
+/** Add an explicit, one-shot marker to a new-conversation route. */
+export function withMyProjectConversationMarker(
+  path: string,
+  type: MyProjectConversationType,
+): string {
+  const hashIndex = path.indexOf("#");
+  const hash = hashIndex >= 0 ? path.slice(hashIndex) : "";
+  const pathWithoutHash = hashIndex >= 0 ? path.slice(0, hashIndex) : path;
+  const queryIndex = pathWithoutHash.indexOf("?");
+  const pathname =
+    queryIndex >= 0 ? pathWithoutHash.slice(0, queryIndex) : pathWithoutHash;
+  const params = new URLSearchParams(
+    queryIndex >= 0 ? pathWithoutHash.slice(queryIndex + 1) : "",
+  );
+  params.set(MY_PROJECT_QUERY_SOURCE_KEY, MY_PROJECT_THREAD_SOURCE);
+  params.set(MY_PROJECT_QUERY_TYPE_KEY, type);
+  const search = params.toString();
+  return `${pathname}${search ? `?${search}` : ""}${hash}`;
+}

frontend-web/src/pages/ChatPage.tsx

@@ -64,6 +64,10 @@ import {
   useThreadSettings,
 } from "@/core/settings";
 import { useThreadStream, stopActiveThreadBeforeClarificationReply } from "@/core/threads/hooks";
+import {
+  myProjectConversationTypeFromSearchParams,
+  myProjectThreadMetadata,
+} from "@/core/threads/project-metadata";
 import { useResearchWritingFeed } from "@/core/threads/use-research-writing-feed";
 import { clearResearchReportStream } from "@/core/threads/use-research-report-stream";
 import { resolveWritingModeReportPath } from "@/core/threads/writing-mode";
@@ -285,16 +289,28 @@ export default function ChatPage() {
   }, [selectedAgentId, selectorAgents, mineAgents, squareAgents, selectorLoading]);
 
   const { showNotification } = useNotification();
+  const projectConversationType =
+    myProjectConversationTypeFromSearchParams(searchParams);
+  const newThreadMetadata = useMemo<Record<string, unknown> | undefined>(() => {
+    const metadata: Record<string, unknown> = projectConversationType
+      ? myProjectThreadMetadata(projectConversationType)
+      : {};
+    if (knowledgeSelectionReady) {
+      metadata.llmwiki_knowledge_base_ids = selectedKnowledgeBaseIds;
+      metadata.assistant_knowledge_base_ids = selectedAssistantKnowledgeBaseIds;
+    }
+    return Object.keys(metadata).length > 0 ? metadata : undefined;
+  }, [
+    knowledgeSelectionReady,
+    projectConversationType,
+    selectedAssistantKnowledgeBaseIds,
+    selectedKnowledgeBaseIds,
+  ]);
 
   const [thread, sendMessage, isUploading] = useThreadStream({
     threadId: isNewThread ? undefined : threadId,
     context: streamContext,
-    threadMetadata: knowledgeSelectionReady
-      ? {
-          llmwiki_knowledge_base_ids: selectedKnowledgeBaseIds,
-          assistant_knowledge_base_ids: selectedAssistantKnowledgeBaseIds,
-        }
-      : undefined,
+    threadMetadata: newThreadMetadata,
     isMock,
     onStart: (createdThreadId) => {
       knowledgeSelectionThread.current = createdThreadId;
@@ -405,7 +421,9 @@ export default function ChatPage() {
           try {
             let targetThreadId = threadId;
             if (isNewThread) {
-              const created = await getAPIClient(isMock).threads.create({});
+              const created = await getAPIClient(isMock).threads.create({
+                metadata: newThreadMetadata ?? {},
+              });
               targetThreadId = created.thread_id;
               setThreadId(targetThreadId);
               setIsNewThread(false);
@@ -465,13 +483,8 @@ export default function ChatPage() {
           try {
             const created = await getAPIClient(isMock).threads.create({
               metadata: {
+                ...newThreadMetadata,
                 agent_id: selectedAgentId,
-                ...(knowledgeSelectionReady
-                  ? {
-                      llmwiki_knowledge_base_ids: selectedKnowledgeBaseIds,
-                      assistant_knowledge_base_ids: selectedAssistantKnowledgeBaseIds,
-                    }
-                  : {}),
               },
             });
             sessionStorage.setItem(
@@ -490,7 +503,7 @@ export default function ChatPage() {
             );
             saveLastAgentId(selectedAgentId);
             router.push(
-              `/page/workspace/agents/${selectedAgentId}/chats/${created.thread_id}`,
+              `${routeBase}/agents/${encodeURIComponent(selectedAgentId)}/chats/${encodeURIComponent(created.thread_id)}`,
             );
           } catch (err) {
             agentHandoffPendingRef.current = false;
@@ -549,6 +562,7 @@ export default function ChatPage() {
       selectedAssistantKnowledgeBaseIds,
       selectedKnowledgeBaseIds,
       knowledgeSelectionReady,
+      newThreadMetadata,
       agentHandoffPending,
       isMock,
       router,

frontend-web/src/pages/OfficialDeerFlowEntry.tsx

@@ -5,6 +5,7 @@ import {
   ChevronDown,
   CircleHelp,
   Clock3,
+  FolderKanban,
   LoaderCircle,
   MessageSquareText,
   PanelLeftClose,
@@ -20,7 +21,12 @@ import {
 } from "lucide-react";
 import { type FormEvent, useCallback, useMemo, useState } from "react";
 import { useLocation, useNavigate } from "react-router-dom";
+import { Toaster } from "sonner";
 
+import {
+  MyProjectThreadBadge,
+  MyProjectThreadIcon,
+} from "@/components/workspace/my-project-thread-indicator";
 import { useAgent, useAgents } from "@/core/agents";
 import { getAccountDisplayName } from "@/core/auth";
 import {
@@ -29,28 +35,41 @@ import {
   useScheduledTaskRuns,
   useScheduledTasks,
 } from "@/core/scheduled-tasks";
-import { useLocalSettings } from "@/core/settings";
 import {
   useAppearanceSettings,
   useCitationDisplaySettings,
 } from "@/core/system-settings/hooks";
 import { useThreadStream, useThreads } from "@/core/threads/hooks";
+import {
+  myProjectConversationTypeOfThread,
+  myProjectConversationTypeFromSearchParams,
+  myProjectThreadMetadata,
+} from "@/core/threads/project-metadata";
 import { textOfMessage, titleOfThread } from "@/core/threads/utils";
 import { uuid } from "@/core/utils/uuid";
 import {
   OFFICIAL_DEERFLOW_HOME_ROUTE,
   OFFICIAL_DEERFLOW_ROUTE_PREFIX,
 } from "@/core/official-deerflow/routes";
+import StrategyProjectsPage from "@/strategy-selection/StrategyProjectsPage";
+import StrategySelectionPage from "@/strategy-selection/StrategySelectionPage";
 
 import "./official-deerflow-entry.css";
 
-type OfficialPage = "chat" | "agents" | "agent-chat" | "scheduled" | "settings";
+type OfficialPage =
+  | "chat"
+  | "projects"
+  | "agents"
+  | "agent-chat"
+  | "scheduled"
+  | "settings";
 
 function pageFromPath(pathname: string): OfficialPage {
   const path = pathname.slice(OFFICIAL_DEERFLOW_ROUTE_PREFIX.length);
   if (path.startsWith("/workspace/agents/") && path.includes("/chats")) {
     return "agent-chat";
   }
+  if (path.startsWith("/workspace/projects")) return "projects";
   if (path.startsWith("/workspace/agents")) return "agents";
   if (path.startsWith("/workspace/scheduled-tasks")) return "scheduled";
   if (path.startsWith("/workspace/settings")) return "settings";
@@ -78,6 +97,11 @@ function parseScheduledTaskId(pathname: string) {
   return match ? decodeURIComponent(match[1]!) : null;
 }
 
+function parseProjectId(pathname: string) {
+  const match = pathname.match(/\/workspace\/projects\/([^/]+)/);
+  return match ? decodeURIComponent(match[1]!) : null;
+}
+
 function readableError(error: unknown, fallback: string) {
   return error instanceof Error && error.message ? error.message : fallback;
 }
@@ -159,20 +183,36 @@ function ChatWorkspace({
   routeThreadId: string;
 }) {
   const navigate = useNavigate();
+  const location = useLocation();
   const [prompt, setPrompt] = useState("");
   const [sendError, setSendError] = useState<string | null>(null);
   const isNewThread = routeThreadId === "new";
+  const projectConversationType = isNewThread
+    ? myProjectConversationTypeFromSearchParams(
+        new URLSearchParams(location.search),
+      )
+    : null;
   // A new conversation uses the same client-generated id approach as the
   // existing ChatPage. The backend owns the persisted id once streaming starts.
   const [draftThreadId] = useState<string>(() => uuid() as string);
   const activeThreadId = isNewThread ? draftThreadId : routeThreadId;
   const { agent } = useAgent(agentId, { enabled: !!agentId });
-  const [localSettings] = useLocalSettings();
   const [thread, sendMessage, isUploading] = useThreadStream({
     threadId: isNewThread ? undefined : routeThreadId,
     assistantId: agentId ?? undefined,
+    threadMetadata: projectConversationType
+      ? myProjectThreadMetadata(projectConversationType)
+      : undefined,
     context: {
-      ...localSettings.context,
+      // This compact official shell has no model/mode controls of its own.
+      // Do not inherit a hidden selection saved by the customized workspace
+      // (for example an obsolete or quota-exhausted model); an omitted model
+      // lets the backend resolve the current system default or the agent's
+      // globally configured model.
+      model_name: undefined,
+      mode: undefined,
+      reasoning_effort: undefined,
+      writing_mode: false,
       ...(agentId ? { agent_id: agentId } : {}),
     },
     onStart: (createdThreadId) => {
@@ -658,6 +698,10 @@ export default function OfficialDeerFlowEntry() {
     () => parseScheduledTaskId(location.pathname),
     [location.pathname],
   );
+  const projectId = useMemo(
+    () => parseProjectId(location.pathname),
+    [location.pathname],
+  );
   const { data: threads = [], isLoading: threadsLoading, error: threadsError } =
     useThreads({
       limit: 20,
@@ -666,10 +710,12 @@ export default function OfficialDeerFlowEntry() {
       select: ["thread_id", "updated_at", "values", "metadata"],
     });
   const go = (path: string) => navigate(path);
+  const projectBasePath = `${OFFICIAL_DEERFLOW_ROUTE_PREFIX}/workspace/projects`;
 
   const nav = [
     { icon: PlusSquare, label: "新对话", path: OFFICIAL_DEERFLOW_HOME_ROUTE, pages: ["chat"] },
     { icon: MessageSquareText, label: "对话", path: `${OFFICIAL_DEERFLOW_ROUTE_PREFIX}/workspace/chats/new`, pages: ["chat"] },
+    { icon: FolderKanban, label: "我的项目", path: projectBasePath, pages: ["projects"] },
     { icon: Bot, label: "智能体", path: `${OFFICIAL_DEERFLOW_ROUTE_PREFIX}/workspace/agents`, pages: ["agents", "agent-chat"] },
     { icon: CalendarClock, label: "定时任务", path: `${OFFICIAL_DEERFLOW_ROUTE_PREFIX}/workspace/scheduled-tasks`, pages: ["scheduled"] },
   ] as const;
@@ -706,29 +752,43 @@ export default function OfficialDeerFlowEntry() {
           ) : threadsError ? (
             <p className="official-sidebar-error">对话列表加载失败</p>
           ) : threads.length ? (
-            threads.map((chat) => (
-              <button
-                className={`official-recent-chat${chatRoute.threadId === chat.thread_id ? " is-active" : ""}`}
-                key={chat.thread_id}
-                onClick={() => {
-                  const agentId = typeof chat.context?.agent_id === "string"
-                    ? chat.context.agent_id
-                    : typeof chat.metadata?.agent_id === "string"
-                      ? chat.metadata.agent_id
-                      : null;
-                  go(
-                    agentId
-                      ? `${OFFICIAL_DEERFLOW_ROUTE_PREFIX}/workspace/agents/${encodeURIComponent(agentId)}/chats/${encodeURIComponent(chat.thread_id)}`
-                      : `${OFFICIAL_DEERFLOW_ROUTE_PREFIX}/workspace/chats/${encodeURIComponent(chat.thread_id)}`,
-                  );
-                }}
-                type="button"
-              >
-                <MessageSquareText aria-hidden="true" size={15} />
-                <span>{titleOfThread(chat, "未命名对话")}</span>
-                <small>{formatTimestamp(chat.updated_at)}</small>
-              </button>
-            ))
+            threads.map((chat) => {
+              const projectType = myProjectConversationTypeOfThread(chat);
+              return (
+                <button
+                  className={`official-recent-chat${chatRoute.threadId === chat.thread_id ? " is-active" : ""}`}
+                  key={chat.thread_id}
+                  onClick={() => {
+                    const agentId = typeof chat.context?.agent_id === "string"
+                      ? chat.context.agent_id
+                      : typeof chat.metadata?.agent_id === "string"
+                        ? chat.metadata.agent_id
+                        : null;
+                    go(
+                      agentId
+                        ? `${OFFICIAL_DEERFLOW_ROUTE_PREFIX}/workspace/agents/${encodeURIComponent(agentId)}/chats/${encodeURIComponent(chat.thread_id)}`
+                        : `${OFFICIAL_DEERFLOW_ROUTE_PREFIX}/workspace/chats/${encodeURIComponent(chat.thread_id)}`,
+                    );
+                  }}
+                  type="button"
+                >
+                  {projectType ? (
+                    <MyProjectThreadIcon className="size-[15px]" type={projectType} />
+                  ) : (
+                    <MessageSquareText aria-hidden="true" size={15} />
+                  )}
+                  <span className="official-recent-chat-copy">
+                    <span className="official-recent-chat-title">
+                      {titleOfThread(chat, "未命名对话")}
+                    </span>
+                    {projectType && (
+                      <MyProjectThreadBadge type={projectType} />
+                    )}
+                  </span>
+                  <small>{formatTimestamp(chat.updated_at)}</small>
+                </button>
+              );
+            })
           ) : (
             <p className="official-sidebar-empty">暂无历史对话</p>
           )}
@@ -754,6 +814,17 @@ export default function OfficialDeerFlowEntry() {
             routeThreadId={chatRoute.threadId}
           />
         )}
+        {page === "projects" && (
+          projectId ? (
+            <StrategySelectionPage
+              key={projectId}
+              projectBasePath={projectBasePath}
+              projectId={projectId}
+            />
+          ) : (
+            <StrategyProjectsPage basePath={projectBasePath} />
+          )
+        )}
         {page === "agents" && (
           <AgentsPage
             openAgent={(agentId) =>
@@ -771,6 +842,7 @@ export default function OfficialDeerFlowEntry() {
         {page === "scheduled" && <ScheduledTasksPage selectedTaskId={scheduledTaskId} />}
         {page === "settings" && <SettingsPage />}
       </div>
+      <Toaster position="top-center" />
     </main>
   );
 }

frontend-web/src/pages/StrategyRoutes.tsx

@@ -1,4 +1,4 @@
-import { Navigate, Route, Routes } from "react-router-dom";
+import { Navigate, Route, Routes, useParams } from "react-router-dom";
 import { Toaster } from "sonner";
 
 import { SidebarInset, SidebarProvider } from "@/components/ui/sidebar";
@@ -78,6 +78,7 @@ import UsersPage from "./UsersPage";
 import LlmMetricsPage from "./LlmMetricsPage";
 import AdminScheduledTasksPage from "./AdminScheduledTasksPage";
 import AdminUserActivityPage from "./AdminUserActivityPage";
+import StrategyProjectsPage from "@/strategy-selection/StrategyProjectsPage";
 import StrategySelectionPage from "@/strategy-selection/StrategySelectionPage";
 import { ChatRuntime } from "./WorkspaceRoutes";
 
@@ -99,6 +100,11 @@ function StrategyChatThreadLayout() {
   );
 }
 
+function StrategyProjectWorkbenchRoute() {
+  const { project_id: projectId = "" } = useParams<{ project_id: string }>();
+  return <StrategySelectionPage key={projectId} projectId={projectId} />;
+}
+
 export default function StrategyRoutes() {
   const storedAuth = getStoredAuth();
   const canManageBusinessMappings = !storedAuth || storedAuth.system_role === "admin";
@@ -111,7 +117,20 @@ export default function StrategyRoutes() {
             <Route index element={<Navigate to="qa/general" replace />} />
 
             <Route path="qa/general" element={<GeneralQA />} />
-            <Route path="qa/strategy-selection" element={<StrategySelectionPage />} />
+            <Route
+              path="qa/projects"
+              element={
+                <StrategyProjectsPage basePath="/page/strategy/qa/projects" />
+              }
+            />
+            <Route
+              path="qa/projects/:project_id"
+              element={<StrategyProjectWorkbenchRoute />}
+            />
+            <Route
+              path="qa/strategy-selection"
+              element={<Navigate to="/page/strategy/qa/projects" replace />}
+            />
             <Route
               path="qa/expert-qa"
               element={

frontend-web/src/pages/official-deerflow-entry.css

@@ -64,6 +64,8 @@
 .official-recent-section > p { color: #90908e; font-size: 12px; margin: 0 8px 9px; }
 .official-recent-chat { display: grid; font-size: 13px; gap: 8px; grid-template-columns: 15px minmax(0, 1fr) auto; padding: 8px; }
 .official-recent-chat span { overflow: hidden; text-overflow: ellipsis; white-space: nowrap; }
+.official-recent-chat-copy { align-items: center; display: flex; gap: 6px; min-width: 0; }
+.official-recent-chat-title { flex: 1; min-width: 0; }
 .official-recent-chat small { color: #acaca9; font-size: 11px; }
 .official-recent-chat.is-active { background: #efefed; color: #252525; }
 .official-sidebar-loading,

frontend-web/src/strategy-selection/AgentConfigDialog.tsx

@@ -2,6 +2,9 @@ import { useEffect, useMemo, useState } from "react";
 import { Bot, Check, LoaderCircle, Save, Sparkles } from "lucide-react";
 import { toast } from "sonner";
 
+import { SkillTransferSelector } from "@/components/workspace/agents/skill-transfer-selector";
+import { ModelNameSelect } from "@/components/workspace/model-name-select";
+import { SkillDetailDialog } from "@/components/workspace/skills/skill-detail-dialog";
 import { Badge } from "@/components/ui/badge";
 import { Button } from "@/components/ui/button";
 import {
@@ -15,6 +18,7 @@ import {
 import { Textarea } from "@/components/ui/textarea";
 import { getAgent, updateAgent } from "@/core/agents/api";
 import type { Agent } from "@/core/agents/types";
+import { useAllSkillsAdmin } from "@/core/skills/hooks";
 import { cn } from "@/lib/utils";
 
 import { STRATEGY_AGENT_ROLES } from "./constants";
@@ -24,15 +28,33 @@ interface AgentConfigDialogProps {
   onOpenChange: (open: boolean) => void;
 }
 
-function parseSkills(value: string): string[] {
-  return [...new Set(value.split(/[,，\n]/).map((item) => item.trim()).filter(Boolean))];
+interface AgentConfigDraft {
+  soul: string;
+  model: string | null;
+  skills: string[];
+}
+
+function normalizeSkills(skills: string[]) {
+  return [...new Set(skills)].sort((left, right) => left.localeCompare(right));
+}
+
+function sameSkills(left: string[], right: string[]) {
+  const normalizedLeft = normalizeSkills(left);
+  const normalizedRight = normalizeSkills(right);
+  return (
+    normalizedLeft.length === normalizedRight.length &&
+    normalizedLeft.every((skill, index) => skill === normalizedRight[index])
+  );
 }
 
 export function AgentConfigDialog({ open, onOpenChange }: AgentConfigDialogProps) {
   const [selectedId, setSelectedId] = useState<string>(STRATEGY_AGENT_ROLES[0].id);
   const [agent, setAgent] = useState<Agent | null>(null);
   const [soul, setSoul] = useState("");
-  const [skillsText, setSkillsText] = useState("");
+  const [model, setModel] = useState<string | null>(null);
+  const [selectedSkills, setSelectedSkills] = useState<string[]>([]);
+  const [savedDraft, setSavedDraft] = useState<AgentConfigDraft | null>(null);
+  const [detailSkillName, setDetailSkillName] = useState<string | null>(null);
   const [loading, setLoading] = useState(false);
   const [saving, setSaving] = useState(false);
   const [error, setError] = useState("");
@@ -41,6 +63,31 @@ export function AgentConfigDialog({ open, onOpenChange }: AgentConfigDialogProps
     () => STRATEGY_AGENT_ROLES.find((role) => role.id === selectedId)!,
     [selectedId],
   );
+  const {
+    skills,
+    isLoading: isSkillsLoading,
+    error: skillsError,
+  } = useAllSkillsAdmin(open);
+  const selectableSkills = useMemo(
+    () =>
+      skills.filter((skill) => {
+        const globallyAvailable =
+          Boolean(skill.builtin) || Boolean(skill.published);
+        return (
+          skill.enabled &&
+          (skill.state ?? "active") === "active" &&
+          globallyAvailable
+        );
+      }),
+    [skills],
+  );
+  const dirty = Boolean(
+    agent &&
+      savedDraft &&
+      (soul !== savedDraft.soul ||
+        model !== savedDraft.model ||
+        !sameSkills(selectedSkills, savedDraft.skills)),
+  );
 
   useEffect(() => {
     if (!open || !selectedId) return;
@@ -48,12 +95,20 @@ export function AgentConfigDialog({ open, onOpenChange }: AgentConfigDialogProps
     setLoading(true);
     setError("");
     setAgent(null);
+    setSavedDraft(null);
     void getAgent(selectedId)
       .then((data) => {
         if (!active) return;
         setAgent(data);
-        setSoul(data.soul ?? "");
-        setSkillsText((data.skills ?? []).join("\n"));
+        const nextDraft = {
+          soul: data.soul ?? "",
+          model: data.model ?? null,
+          skills: data.skills ?? [],
+        };
+        setSoul(nextDraft.soul);
+        setModel(nextDraft.model);
+        setSelectedSkills(nextDraft.skills);
+        setSavedDraft(nextDraft);
       })
       .catch((reason: unknown) => {
         if (!active) return;
@@ -77,11 +132,18 @@ export function AgentConfigDialog({ open, onOpenChange }: AgentConfigDialogProps
     try {
       const updated = await updateAgent(agent.id, {
         soul: soul.trim(),
-        skills: parseSkills(skillsText),
+        model,
+        skills: selectedSkills,
       });
       setAgent(updated);
       setSoul(updated.soul ?? "");
-      setSkillsText((updated.skills ?? []).join("\n"));
+      setModel(updated.model ?? null);
+      setSelectedSkills(updated.skills ?? []);
+      setSavedDraft({
+        soul: updated.soul ?? "",
+        model: updated.model ?? null,
+        skills: updated.skills ?? [],
+      });
       toast.success(`${updated.name} 配置已保存`);
     } catch (reason) {
       toast.error(reason instanceof Error ? reason.message : "保存失败");
@@ -90,8 +152,21 @@ export function AgentConfigDialog({ open, onOpenChange }: AgentConfigDialogProps
     }
   };
 
+  const confirmDiscardChanges = () =>
+    !dirty || window.confirm("当前智能体配置尚未保存，确定放弃这些修改吗？");
+
+  const selectRole = (roleId: string) => {
+    if (roleId === selectedId || saving || !confirmDiscardChanges()) return;
+    setSelectedId(roleId);
+  };
+
+  const handleOpenChange = (nextOpen: boolean) => {
+    if (!nextOpen && (saving || !confirmDiscardChanges())) return;
+    onOpenChange(nextOpen);
+  };
+
   return (
-    <Dialog open={open} onOpenChange={onOpenChange}>
+    <Dialog open={open} onOpenChange={handleOpenChange}>
       <DialogContent className="h-[min(780px,calc(100vh-48px))] max-w-[1080px] grid-rows-[auto_minmax(0,1fr)_auto] gap-0 overflow-hidden p-0 sm:max-w-[1080px]">
         <DialogHeader className="border-b px-6 py-5 dark:border-[#173d68]">
           <DialogTitle className="flex items-center gap-2">
@@ -99,7 +174,7 @@ export function AgentConfigDialog({ open, onOpenChange }: AgentConfigDialogProps
             策略智能体配置
           </DialogTitle>
           <DialogDescription>
-            每个流程角色对应一个默认智能体。管理员可修改 SOUL 和技能；保存后下一次运行即生效。
+            这是全局统一配置，不属于某一个项目。管理员保存后，所有策略项目下一次运行都会使用这里的模型、SOUL 和技能。
           </DialogDescription>
         </DialogHeader>
 
@@ -116,7 +191,7 @@ export function AgentConfigDialog({ open, onOpenChange }: AgentConfigDialogProps
                     key={role.id}
                     type="button"
                     disabled={saving}
-                    onClick={() => setSelectedId(role.id)}
+                    onClick={() => selectRole(role.id)}
                     className={cn(
                       "w-full rounded-lg border px-3 py-3 text-left transition-colors disabled:cursor-not-allowed disabled:opacity-60",
                       selected
@@ -160,15 +235,22 @@ export function AgentConfigDialog({ open, onOpenChange }: AgentConfigDialogProps
               </div>
             ) : agent ? (
               <div className="space-y-5">
-                <div className="grid grid-cols-2 gap-3 rounded-lg border bg-muted/20 p-3 text-sm dark:border-[#173d68] dark:bg-[#031b38]">
+                <div className="grid grid-cols-[minmax(0,1fr)_minmax(220px,0.9fr)] gap-3 rounded-lg border bg-muted/20 p-3 text-sm dark:border-[#173d68] dark:bg-[#031b38]">
                   <div>
                     <span className="text-xs text-muted-foreground">当前名称</span>
                     <div className="mt-1 font-medium">{agent.name}</div>
                   </div>
-                  <div>
+                  <label className="block">
                     <span className="text-xs text-muted-foreground">运行模型</span>
-                    <div className="mt-1 font-medium">{agent.model || "使用系统默认模型"}</div>
-                  </div>
+                    <ModelNameSelect
+                      value={model}
+                      onChange={setModel}
+                      disabled={saving}
+                      defaultLabel="使用系统默认模型"
+                      title="选择该全局智能体运行时使用的大模型；未指定时使用系统默认模型"
+                      triggerClassName="mt-1 w-full bg-background"
+                    />
+                  </label>
                 </div>
 
                 <label className="block">
@@ -179,40 +261,52 @@ export function AgentConfigDialog({ open, onOpenChange }: AgentConfigDialogProps
                     value={soul}
                     disabled={saving}
                     onChange={(event) => setSoul(event.target.value)}
-                    className="min-h-[300px] resize-y font-mono text-xs leading-6"
+                    className="min-h-[220px] resize-y font-mono text-xs leading-6"
                     placeholder="定义智能体的角色、分析方法、边界和输出要求…"
                   />
                 </label>
 
-                <label className="block">
-                  <span className="mb-2 block text-sm font-medium">技能</span>
-                  <Textarea
-                    value={skillsText}
-                    disabled={saving}
-                    onChange={(event) => setSkillsText(event.target.value)}
-                    placeholder="多个技能可用逗号分隔"
-                    rows={3}
-                    className="resize-y text-sm"
-                  />
-                  <p className="mt-1.5 text-xs text-muted-foreground">
-                    可用逗号、中文逗号或换行分隔；留空表示不绑定专用技能。
+                <div className="space-y-2">
+                  <div className="flex items-center justify-between gap-3">
+                    <span className="text-sm font-medium">技能库选择</span>
+                    <Badge variant="secondary">已选 {selectedSkills.length} 个</Badge>
+                  </div>
+                  <p className="text-xs leading-5 text-muted-foreground">
+                    从系统技能库勾选该智能体可使用的技能；这里保存的是全局白名单，不接受手工输入技能名。
                   </p>
-                </label>
+                  <SkillTransferSelector
+                    skills={selectableSkills}
+                    selected={selectedSkills}
+                    onChange={setSelectedSkills}
+                    isLoading={isSkillsLoading}
+                    onViewDetail={setDetailSkillName}
+                  />
+                  {skillsError ? (
+                    <p className="text-xs text-destructive">技能库加载失败，请稍后重试。</p>
+                  ) : null}
+                </div>
               </div>
             ) : null}
           </div>
         </div>
 
         <DialogFooter className="border-t px-6 py-4 dark:border-[#173d68]">
-          <Button variant="outline" onClick={() => onOpenChange(false)}>
+          <Button variant="outline" disabled={saving} onClick={() => handleOpenChange(false)}>
             关闭
           </Button>
-          <Button disabled={!agent || loading || saving} onClick={() => void save()}>
+          <Button disabled={!agent || loading || saving || isSkillsLoading} onClick={() => void save()}>
             {saving ? <LoaderCircle className="animate-spin" /> : <Save />}
             保存当前智能体
           </Button>
         </DialogFooter>
       </DialogContent>
+      <SkillDetailDialog
+        skillName={detailSkillName}
+        open={detailSkillName !== null}
+        onOpenChange={(nextOpen) => {
+          if (!nextOpen) setDetailSkillName(null);
+        }}
+      />
     </Dialog>
   );
 }

frontend-web/src/strategy-selection/projects.ts

@@ -0,0 +1,336 @@
+import { apiFetch } from "@/core/api/fetch-client";
+import { getBackendBaseURL } from "@/core/config";
+import { createClientId } from "@/lib/client-id";
+
+import {
+  EMPTY_TASK_DRAFT,
+  INITIAL_INTENT_TURNS,
+  STRATEGY_ANGLES,
+  TAIWAN_STRAIT_DEMO_EVALUATIONS,
+  TAIWAN_STRAIT_DEMO_OUTPUTS,
+  TAIWAN_STRAIT_DEMO_SYNTHESIS,
+  TAIWAN_STRAIT_DEMO_TASK,
+  TAIWAN_STRAIT_DEMO_TURNS,
+} from "./constants";
+import type {
+  AgentOutputState,
+  IntentTurn,
+  StrategyEvaluation,
+  StrategyStage,
+  StrategyTaskDraft,
+} from "./types";
+
+export const STRATEGY_PROJECT_ID_PREFIX = "strategy-selection-";
+const SNAPSHOT_KIND = "strategy-selection-project";
+
+const DEMO_JUDGE_CONTENT = `### 评判结论
+
+六个角度均与任务目标相关，其中治理统筹、安全风险和外交沟通直接作用于“减少误判与阻断升级”，应优先纳入；法律规则是高压情境下的必要边界。经济韧性和社会民生策略建议与主策略合并实施，避免形成两套割裂的连续性机制。
+
+**组合提醒：** 对外沟通节奏、市场稳定措施和风险等级调整必须使用同一事实基线；任何高风险政策动作均需设置冷静期、法律复核与退出条件。`;
+
+export interface StrategyProjectSnapshot {
+  version: 1;
+  stage: StrategyStage;
+  taskDraft: StrategyTaskDraft;
+  turns: IntentTurn[];
+  outputs: Record<string, AgentOutputState>;
+  judgeStatus: AgentOutputState["status"];
+  judgeContent: string;
+  evaluations: StrategyEvaluation[];
+  selectedStrategyIds: string[];
+  synthesis: string;
+  synthesisStatus: AgentOutputState["status"];
+  isDemo: boolean;
+  workflowStale: boolean;
+}
+
+export interface StrategyProjectSummary {
+  id: string;
+  title: string;
+  brief: string;
+  createdAt: string | null;
+  updatedAt: string | null;
+  stage: StrategyStage;
+  questionCount: number;
+  angleCount: number;
+  completedStrategyCount: number;
+  hasEvaluation: boolean;
+  hasSolution: boolean;
+  isDemo: boolean;
+  workflowStale: boolean;
+}
+
+export interface StrategyProject extends StrategyProjectSummary {
+  snapshot: StrategyProjectSnapshot;
+}
+
+interface ParallelTaskResponse {
+  id: string;
+  title?: string;
+  brief?: string | null;
+  agents?: Array<{ agent_id: string; name?: string; avatarType?: string | null }>;
+  messages?: Array<Record<string, unknown>> | null;
+  created_at?: string | null;
+  updated_at?: string | null;
+}
+
+interface ParallelTaskListResponse {
+  tasks?: ParallelTaskResponse[];
+}
+
+interface SnapshotEnvelope extends Record<string, unknown> {
+  kind: typeof SNAPSHOT_KIND;
+  version: 1;
+  snapshot: StrategyProjectSnapshot;
+}
+
+const cloneTask = (task: StrategyTaskDraft): StrategyTaskDraft => ({
+  ...task,
+  selectedAngleIds: [...task.selectedAngleIds],
+});
+
+const cloneTurns = (turns: IntentTurn[]): IntentTurn[] =>
+  turns.map((turn) => ({ ...turn, streaming: false }));
+
+const cloneOutputs = (
+  outputs: Record<string, AgentOutputState>,
+): Record<string, AgentOutputState> =>
+  Object.fromEntries(
+    Object.entries(outputs).map(([id, output]) => [
+      id,
+      { ...output, steps: [...(output.steps ?? [])] },
+    ]),
+  );
+
+const cloneEvaluations = (evaluations: StrategyEvaluation[]) =>
+  evaluations.map((item) => ({
+    ...item,
+    strengths: [...item.strengths],
+    risks: [...item.risks],
+  }));
+
+export function createEmptyStrategySnapshot(): StrategyProjectSnapshot {
+  return {
+    version: 1,
+    stage: "intent",
+    taskDraft: cloneTask(EMPTY_TASK_DRAFT),
+    turns: cloneTurns(INITIAL_INTENT_TURNS),
+    outputs: {},
+    judgeStatus: "idle",
+    judgeContent: "",
+    evaluations: [],
+    selectedStrategyIds: [],
+    synthesis: "",
+    synthesisStatus: "idle",
+    isDemo: false,
+    workflowStale: false,
+  };
+}
+
+export function createDemoStrategySnapshot(): StrategyProjectSnapshot {
+  return {
+    version: 1,
+    stage: "workspace",
+    taskDraft: cloneTask(TAIWAN_STRAIT_DEMO_TASK),
+    turns: cloneTurns(TAIWAN_STRAIT_DEMO_TURNS),
+    outputs: cloneOutputs(TAIWAN_STRAIT_DEMO_OUTPUTS),
+    judgeStatus: "done",
+    judgeContent: DEMO_JUDGE_CONTENT,
+    evaluations: cloneEvaluations(TAIWAN_STRAIT_DEMO_EVALUATIONS),
+    selectedStrategyIds: TAIWAN_STRAIT_DEMO_EVALUATIONS.filter(
+      (item) => item.score >= 88,
+    ).map((item) => item.agentId),
+    synthesis: TAIWAN_STRAIT_DEMO_SYNTHESIS,
+    synthesisStatus: "done",
+    isDemo: true,
+    workflowStale: false,
+  };
+}
+
+function isObject(value: unknown): value is Record<string, unknown> {
+  return Boolean(value) && typeof value === "object" && !Array.isArray(value);
+}
+
+function readSnapshot(task: ParallelTaskResponse): StrategyProjectSnapshot | null {
+  const envelope = task.messages?.find(
+    (message) => message.kind === SNAPSHOT_KIND && message.version === 1,
+  );
+  if (!isObject(envelope) || !isObject(envelope.snapshot)) return null;
+  const snapshot = envelope.snapshot as unknown as StrategyProjectSnapshot;
+  if (
+    snapshot.version !== 1 ||
+    (snapshot.stage !== "intent" && snapshot.stage !== "workspace") ||
+    !isObject(snapshot.taskDraft) ||
+    !Array.isArray(snapshot.taskDraft.selectedAngleIds) ||
+    !Array.isArray(snapshot.turns) ||
+    !isObject(snapshot.outputs) ||
+    !Array.isArray(snapshot.evaluations) ||
+    !Array.isArray(snapshot.selectedStrategyIds)
+  ) {
+    return null;
+  }
+  return {
+    ...snapshot,
+    workflowStale: snapshot.workflowStale === true,
+    taskDraft: cloneTask(snapshot.taskDraft),
+    turns: cloneTurns(snapshot.turns),
+    outputs: cloneOutputs(snapshot.outputs),
+    evaluations: cloneEvaluations(snapshot.evaluations),
+    selectedStrategyIds: [...snapshot.selectedStrategyIds],
+  };
+}
+
+function toProject(task: ParallelTaskResponse): StrategyProject | null {
+  const snapshot = readSnapshot(task);
+  if (!snapshot) return null;
+  const completedStrategyCount = Object.values(snapshot.outputs).filter(
+    (output) => output.status === "done" && output.content.trim(),
+  ).length;
+  return {
+    id: task.id,
+    title: snapshot.taskDraft.name.trim() || task.title?.trim() || "未命名策略项目",
+    brief: snapshot.taskDraft.detail.trim() || task.brief?.trim() || "尚未补充项目说明",
+    createdAt: task.created_at ?? null,
+    updatedAt: task.updated_at ?? null,
+    stage: snapshot.stage,
+    questionCount: snapshot.turns.filter((turn) => turn.role === "user").length,
+    angleCount: snapshot.taskDraft.selectedAngleIds.length,
+    completedStrategyCount,
+    hasEvaluation:
+      !snapshot.workflowStale &&
+      snapshot.judgeStatus === "done" &&
+      Boolean(snapshot.judgeContent.trim()),
+    hasSolution:
+      !snapshot.workflowStale &&
+      snapshot.synthesisStatus === "done" &&
+      Boolean(snapshot.synthesis.trim()),
+    isDemo: snapshot.isDemo,
+    workflowStale: snapshot.workflowStale,
+    snapshot,
+  };
+}
+
+async function readError(response: Response): Promise<string> {
+  const body = (await response.json().catch(() => null)) as
+    | { detail?: string }
+    | null;
+  return body?.detail || `请求失败（HTTP ${response.status}）`;
+}
+
+const endpoint = (suffix = "") =>
+  `${getBackendBaseURL()}/api/parallel-agent-tasks${suffix}`;
+
+async function getParallelTask(id: string): Promise<ParallelTaskResponse> {
+  const response = await apiFetch(endpoint(`/${encodeURIComponent(id)}`));
+  if (!response.ok) throw new Error(await readError(response));
+  return (await response.json()) as ParallelTaskResponse;
+}
+
+export async function listStrategyProjects(): Promise<StrategyProjectSummary[]> {
+  const response = await apiFetch(endpoint());
+  if (!response.ok) throw new Error(await readError(response));
+  const body = (await response.json()) as ParallelTaskListResponse;
+  const candidates = (body.tasks ?? []).filter((task) =>
+    task.id.startsWith(STRATEGY_PROJECT_ID_PREFIX),
+  );
+  const records = await Promise.allSettled(
+    candidates.map((task) => getParallelTask(task.id)),
+  );
+  return records
+    .flatMap((result) => {
+      if (result.status !== "fulfilled") return [];
+      const project = toProject(result.value);
+      return project ? [project] : [];
+    })
+    .sort((a, b) =>
+      String(b.updatedAt ?? "").localeCompare(String(a.updatedAt ?? "")),
+    );
+}
+
+export async function getStrategyProject(id: string): Promise<StrategyProject> {
+  if (!id.startsWith(STRATEGY_PROJECT_ID_PREFIX)) {
+    throw new Error("这不是一个策略优选项目");
+  }
+  const task = await getParallelTask(id);
+  const project = toProject(task);
+  if (!project) throw new Error("项目数据不完整，无法恢复策略工作台");
+  return project;
+}
+
+function projectAgents(snapshot: StrategyProjectSnapshot) {
+  const selected = new Set(snapshot.taskDraft.selectedAngleIds);
+  const angleAgents = STRATEGY_ANGLES.filter((angle) => selected.has(angle.id)).map(
+    (angle) => ({ agent_id: angle.agentId, name: angle.name }),
+  );
+  return [
+    { agent_id: "strategy-selection-intent", name: "意图理解智能体" },
+    ...angleAgents,
+    { agent_id: "strategy-selection-judge", name: "策略评判智能体" },
+    { agent_id: "strategy-selection-solution", name: "方案整理智能体" },
+  ];
+}
+
+function snapshotEnvelope(snapshot: StrategyProjectSnapshot): SnapshotEnvelope {
+  return {
+    kind: SNAPSHOT_KIND,
+    version: 1,
+    snapshot,
+  };
+}
+
+export async function createStrategyProject(
+  snapshot: StrategyProjectSnapshot = createEmptyStrategySnapshot(),
+): Promise<StrategyProject> {
+  const id = `${STRATEGY_PROJECT_ID_PREFIX}${createClientId()}`;
+  const response = await apiFetch(endpoint(), {
+    method: "POST",
+    headers: { "Content-Type": "application/json" },
+    body: JSON.stringify({
+      id,
+      title: snapshot.taskDraft.name.trim() || "未命名策略项目",
+      brief: snapshot.taskDraft.detail.trim() || null,
+      agents: projectAgents(snapshot),
+      messages: [snapshotEnvelope(snapshot)],
+    }),
+  });
+  if (!response.ok) throw new Error(await readError(response));
+  const project = toProject((await response.json()) as ParallelTaskResponse);
+  if (!project) throw new Error("项目已创建，但返回数据无法识别");
+  return project;
+}
+
+export async function saveStrategyProject(
+  id: string,
+  snapshot: StrategyProjectSnapshot,
+  options: {
+    keepalive?: boolean;
+    signal?: AbortSignal;
+  } = {},
+): Promise<StrategyProject> {
+  const response = await apiFetch(endpoint(`/${encodeURIComponent(id)}`), {
+    method: "PUT",
+    headers: { "Content-Type": "application/json" },
+    keepalive: options.keepalive,
+    signal: options.signal,
+    body: JSON.stringify({
+      title: snapshot.taskDraft.name.trim() || "未命名策略项目",
+      brief: snapshot.taskDraft.detail.trim() || null,
+      agents: projectAgents(snapshot),
+      messages: [snapshotEnvelope(snapshot)],
+    }),
+  });
+  if (!response.ok) throw new Error(await readError(response));
+  const project = toProject((await response.json()) as ParallelTaskResponse);
+  if (!project) throw new Error("项目已保存，但返回数据无法识别");
+  return project;
+}
+
+export async function deleteStrategyProject(id: string): Promise<void> {
+  const response = await apiFetch(endpoint(`/${encodeURIComponent(id)}`), {
+    method: "DELETE",
+  });
+  if (!response.ok && response.status !== 404) {
+    throw new Error(await readError(response));
+  }
+}

offline-backend-20260512/backend/CLAUDE.md

@@ -542,6 +542,8 @@ Self-contained product knowledge base. **All knowledge capability lives in this
 
 Custom agent metadata lives in the `agents` ORM table (`deerflow.persistence.agents`). `agents.id` is the stable runtime id and the filesystem directory name under `.deer-flow/agents/{id}/`; `agents.name` is display-only, can contain Chinese characters, and is not unique. `user_id IS NULL` marks built-in agents, user-owned agents are visible only to their owner unless `published = true`, and update/delete operations require ownership. The runtime accepts `agent_id` in context/configurable, and non-default `assistant_id` values are treated as agent ids after visibility checks.
 
+Strategy-selection fan-out (`routers/parallel_agents.py`) must inspect its final AI message with the shared `is_llm_error_message` detector and require substantive visible text before constructing a success result. A middleware fallback, empty/thinking-only response, or punctuation-only provider degeneration is a failed seat run: raise so the stream emits `agent_error`; never wrap it in `agent_done`. Regression coverage: `tests/test_roundtable_model_fallback.py`.
+
 **Listing cache + pagination** ? to keep `GET /api/agents` fast, the gallery's per-card extras (skills + tool_groups) are denormalized into two cache tables instead of reading every agent's `config.yaml` on each request: `agent_skills` (relational, one row per (agent, skill) with `position`) and `agent_extras` (one row per agent: `tool_groups` JSON + `model` + `skills_synced_at`). `config.yaml` remains authoritative for the agent runtime; these tables are a read cache, write-through on create/update and backfilled from disk by `_sync_legacy_agents` (mtime-vs-`skills_synced_at` drift check). The list endpoint enriches via `AgentStore.get_extras_for([ids])` (two batched `IN` queries). Both tables are auto-created by `Base.metadata.create_all` (no migration needed). `GET /api/agents` supports **opt-in server-side pagination**: `scope` (`mine` = owned + favorited / `square` = built-in/published public), `page`, `page_size`, returning `{agents, total, page, page_size}`; omitting `scope`/`page` preserves the legacy "return everything" behavior. Name `search` matches the raw OR desensitized name (the frontend's static term?abbrev map is mirrored server-side in `deerflow/config/agent_name_desensitize.py`); `tag_ids` is an SQL OR-filter; `owner` keeps only agents published by that user id (the card's ??? ? built-in agents never match), powering the gallery's click-???-to-filter. `POST /api/agents/private-square/list` takes the same pagination params (incl. `owner`). Repository entry point: `AgentStore.list_paginated(...)`. Tests: `tests/test_agent_listing_cache.py::test_list_paginated_owner_filter_keeps_one_publisher`.
 
 **Homepage selector (agent picker on the new-chat page)** ? single admin-curated list backed by `agents.featured_order` (nullable BIGINT). NULL = not featured. Only `published = true` agents can be featured (router enforces on writes); any published agent is eligible regardless of ownership. Cleared with `order: null`. The list rendered to end users is `WHERE featured_order IS NOT NULL` + visibility-filter, sorted by `featured_order ASC`. Admins reorder by sending the desired ids to `PUT /api/agents/featured/order` (assigns indices 0..N-1). BIGINT is used rather than INT so the management UI can seed initial values from `Date.now()` (overflows INT on MySQL).
@@ -1000,6 +1002,15 @@ scheduler runs once per deployment. Per run:
 - Supports `supports_vision` flag for image understanding models
 - Config values starting with `$` resolved as environment variables
 - Missing provider modules surface actionable install hints from reflection resolvers (for example `uv add langchain-google-genai`)
+- Generic `langchain_openai:ChatOpenAI` entries are transparently wrapped by
+  `PatchedChatOpenAI`. Besides preserving reasoning/tool-call metadata, the
+  patch recognizes compatible gateways that encode failures inside HTTP 200
+  payloads (`base_resp.status_code != 0` with null/empty `choices`) in both
+  streaming and non-streaming paths. It raises the stable
+  `OpenAICompatibleUpstreamError`; `LLMErrorHandlingMiddleware` retries
+  transient concurrency/inference failures, while genuine quota/balance
+  failures are classified as non-retriable and surfaced immediately. Embedded
+  vendor failures therefore cannot become empty successful assistant turns.
 
 ### Roundtable Model Fault Tolerance (会商模型自动容错 / 换下一个模型)
 

offline-backend-20260512/backend/README.md

@@ -471,7 +471,7 @@ Custom agents are indexed in the `agents` database table. The `id` column is the
 
 The built-in `forced-research-responder` (「强制检索输出助手」) is seeded at Gateway startup. Unlike an ordinary skill-enabled custom agent, it has a runtime-enforced per-turn collection gate: the model cannot finish a response until a retrieval/knowledge/MCP tool or a skill Python script returns usable information. It then answers directly in the user's requested chat format rather than generating an artifact. The agent may create or edit only temporary `.py` files below `/mnt/user-data/workspace/` and may execute `.py` skill scripts through `bash`; writes to `outputs`, Markdown/document creation, `present_files`, general shell commands, and skill mutation are denied. Administrators can edit its model and skill allowlist from agent management; the runtime safety policy remains fixed. Regression coverage: `tests/test_forced_research_agent.py`.
 
-The strategy-selection workbench owns nine folder-backed functional agents: one intent agent, six independent angle agents (governance, diplomacy, economy/supply-chain, security risk, public opinion, and law/policy), one judge, and one final solution editor. Defaults ship in `app/gateway/routers/_strategy_selection_seed_assets/` and are copied only when an agent directory is absent, before `_sync_legacy_agents`; existing administrator edits are never overwritten. The angle agents use the existing `policy-knowledge` skill and read/search tool groups, intent uses `intent-clarification-policy`, judging is input-only, and the solution editor has file-write access for `/mnt/user-data/outputs/综合策略方案.md`. Every default SOUL requires neutral evidence handling, de-escalation and civilian protection, and prohibits operational combat guidance or targeted political manipulation. Regression coverage: `tests/test_strategy_selection_seed.py`.
+The strategy-selection workbench owns nine folder-backed functional agents: one intent agent, six independent angle agents (governance, diplomacy, economy/supply-chain, security risk, public opinion, and law/policy), one judge, and one final solution editor. Defaults ship in `app/gateway/routers/_strategy_selection_seed_assets/` and are copied only when an agent directory is absent, before `_sync_legacy_agents`; existing administrator edits are never overwritten. The angle agents use the existing `policy-knowledge` skill and read/search tool groups, intent uses `intent-clarification-policy`, judging is input-only, and the solution editor has file-write access for `/mnt/user-data/outputs/综合策略方案.md`. Every default SOUL requires neutral evidence handling, de-escalation and civilian protection, and prohibits operational combat guidance or targeted political manipulation. The parallel strategy stream treats a final `is_llm_error_message` fallback, empty/thinking-only response, or punctuation-only provider degeneration as `agent_error`, never as a successful `agent_done`. Regression coverage: `tests/test_strategy_selection_seed.py` and `tests/test_roundtable_model_fallback.py`.
 
 ### AI Writing Intranet Retrieval
 
@@ -545,6 +545,13 @@ the configured model has an explicit, proxy-supported thinking control. This
 prevents DeerFlow's connection check from sending vendor-specific `thinking`
 fields that a generic OpenAI-compatible gateway may reject.
 
+OpenAI-compatible gateways that return vendor errors inside an HTTP 200
+response (for example, a non-zero `base_resp.status_code` with empty/null
+`choices`) are treated as upstream failures in both streaming and
+non-streaming calls. DeerFlow retries transient upstream responses instead of
+accepting an empty assistant turn, while genuine quota/balance failures are
+classified as non-retriable and surfaced immediately instead of being retried.
+
 ### Running
 
 **Full Application** (from project root):

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

@@ -15,7 +15,8 @@ from fastapi import APIRouter, Depends, HTTPException, Query, Request
 from pydantic import BaseModel, Field
 
 from app.gateway.auth.password import verify_password_async
-from app.gateway.deps import get_agent_store, get_config, get_tag_store
+from app.gateway.deps import get_agent_store, get_config, get_skill_store, get_tag_store
+from app.gateway.routers._strategy_selection_seed import required_agent_ids as required_strategy_agent_ids
 from deerflow.agents.lead_agent.prompt import refresh_skills_system_prompt_cache_async
 from deerflow.config.agents_api_config import get_agents_api_config
 from deerflow.config.agents_config import CommonQuestion, list_custom_agents, load_agent_config, load_agent_soul, validate_agent_id
@@ -23,13 +24,17 @@ from deerflow.config.app_config import AppConfig
 from deerflow.config.paths import get_paths
 from deerflow.config.system_settings import load_system_settings, normalize_square_id, resolve_default_square_id
 from deerflow.persistence.agents import AgentStore
+from deerflow.persistence.skills import SkillStore
 from deerflow.persistence.tags import TagStore
 from deerflow.runtime.user_context import get_effective_user_id
 from deerflow.skills.cascade import sync_agent_skills_to_available
 from deerflow.skills.storage import get_or_new_skill_storage
+from deerflow.skills.types import SkillCategory
+from deerflow.skills.usage import all_entries as get_skill_usage_entries
 
 logger = logging.getLogger(__name__)
 router = APIRouter(prefix="/api", tags=["agents"])
+_STRATEGY_SELECTION_AGENT_IDS = frozenset(required_strategy_agent_ids())
 
 
 class AgentResponse(BaseModel):
@@ -276,6 +281,109 @@ def _validate_storage_id(agent_id: str) -> str:
         raise HTTPException(status_code=422, detail=str(exc)) from exc
 
 
+async def _validate_strategy_agent_skills(
+    requested_skills: list[str] | None,
+    *,
+    app_config: AppConfig,
+    skill_store: SkillStore,
+) -> list[str] | None:
+    """Validate a global strategy role's skill allowlist.
+
+    Strategy-selection agents are built-in roles shared by every project and
+    every user.  Their allowlists may therefore reference only canonical skill
+    names that exist on disk, are enabled/active, and are globally visible:
+    deployment-owned public skills, explicit built-in rows, or custom skills
+    currently published by their owner.  In particular, an administrator must
+    not be able to attach a different user's unpublished skill merely because
+    ``?admin=true`` exposes it in the management catalog.
+    """
+
+    if requested_skills is None:
+        return None
+
+    normalized: list[str] = []
+    for raw_name in requested_skills:
+        name = raw_name.strip()
+        if not name:
+            raise HTTPException(
+                status_code=422,
+                detail="Strategy agent skill names cannot be blank",
+            )
+        if name not in normalized:
+            normalized.append(name)
+
+    try:
+        skills = get_or_new_skill_storage(app_config=app_config).load_skills(
+            enabled_only=False
+        )
+        ownership = {
+            str(record.get("name") or ""): record
+            for record in await skill_store.list_all()
+            if record.get("name")
+        }
+        usage_entries = get_skill_usage_entries()
+    except HTTPException:
+        raise
+    except Exception as exc:  # noqa: BLE001 - stable API response
+        logger.exception("Failed to validate strategy-agent skill allowlist")
+        raise HTTPException(status_code=503, detail="Skill catalog is unavailable") from exc
+
+    by_name = {skill.name: skill for skill in skills}
+    unknown = [name for name in normalized if name not in by_name]
+    if unknown:
+        raise HTTPException(
+            status_code=422,
+            detail=f"Unknown strategy agent skills: {', '.join(unknown)}",
+        )
+
+    unavailable = [
+        name
+        for name in normalized
+        if not by_name[name].enabled
+        or str((usage_entries.get(name) or {}).get("state") or "active") != "active"
+    ]
+    if unavailable:
+        raise HTTPException(
+            status_code=422,
+            detail=f"Disabled or archived strategy agent skills: {', '.join(unavailable)}",
+        )
+
+    not_global: list[str] = []
+    for name in normalized:
+        skill = by_name[name]
+        if skill.category != SkillCategory.CUSTOM:
+            continue
+        record = ownership.get(name)
+        if record is not None and (
+            record.get("owner_user_id") is None or bool(record.get("published"))
+        ):
+            continue
+        not_global.append(name)
+    if not_global:
+        raise HTTPException(
+            status_code=422,
+            detail=(
+                "Strategy agent skills must be globally available; "
+                f"unpublished or unregistered custom skills: {', '.join(not_global)}"
+            ),
+        )
+
+    return normalized
+
+
+def _ensure_strategy_agent_deletable(agent_id: str) -> None:
+    """Keep fixed strategy role ids alive; their SOUL/skills remain editable."""
+
+    if agent_id in _STRATEGY_SELECTION_AGENT_IDS:
+        raise HTTPException(
+            status_code=409,
+            detail=(
+                f"Strategy role agent '{agent_id}' cannot be deleted; "
+                "edit its SOUL and skills instead"
+            ),
+        )
+
+
 def _write_agent_config(
     agent_id: str,
     *,
@@ -953,7 +1061,14 @@ async def update_agent(agent_id: str, request: AgentUpdateRequest, http_request:
         next_description = update_data.get("description", current.get("description") or "")
 
         existing_extras = _load_config_extras(agent_id)
-        next_skills = request.skills if "skills" in fields_set else existing_extras["skills"]
+        if "skills" in fields_set and agent_id in _STRATEGY_SELECTION_AGENT_IDS:
+            next_skills = await _validate_strategy_agent_skills(
+                request.skills,
+                app_config=get_config(http_request),
+                skill_store=get_skill_store(http_request),
+            )
+        else:
+            next_skills = request.skills if "skills" in fields_set else existing_extras["skills"]
         next_model = request.model if "model" in fields_set else existing_extras["model"]
         next_tool_groups = request.tool_groups if "tool_groups" in fields_set else existing_extras["tool_groups"]
         next_common_questions = request.common_questions if "common_questions" in fields_set else existing_extras["common_questions"]
@@ -1079,6 +1194,7 @@ async def delete_agent(agent_id: str, request: Request) -> None:
         _, edit_mode = await _get_editable_or_raise(
             store, agent_id, user_id, is_admin=is_admin
         )
+        _ensure_strategy_agent_deletable(agent_id)
 
         if edit_mode == "admin":
             deleted = await store.delete_any(agent_id)

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

@@ -31,13 +31,15 @@ from __future__ import annotations
 import asyncio
 import json
 import logging
-from typing import Any, AsyncIterator
+from collections.abc import AsyncIterator
+from typing import Any
 
 import httpx
 from fastapi import APIRouter, Body, HTTPException, Request
 from fastapi.responses import StreamingResponse
 from pydantic import BaseModel, Field
 
+from app.gateway.roundtable_model_fallback import is_llm_error_message, reason_text
 from app.gateway.routers.multi_agent import (
     _ROUNDTABLE_THREAD_METADATA,
     _auth_headers,
@@ -50,6 +52,7 @@ from app.gateway.routers.multi_agent import (
     _stream_upstream,
     _validate_agent_id,
 )
+from deerflow.agents.roundtable_orchestrator.delivery import visible_seat_text
 from deerflow.tools.builtins.clarification_utils import resolve_allow_multiple
 
 logger = logging.getLogger(__name__)
@@ -58,6 +61,17 @@ router = APIRouter(prefix="/api/parallel-agents", tags=["parallel-agents"])
 # Soft cap on parallel degree — protects remote model concurrency + sandbox.
 MAX_PARALLEL_AGENTS = 8
 
+# Strategy roles are expected to return a substantive task/strategy/evaluation,
+# not merely punctuation or a broken provider placeholder.  Counting Unicode
+# alphanumerics keeps the check language-neutral while rejecting outputs such as
+# a long run of "!!!", which otherwise look non-empty to the UI.
+MIN_MEANINGFUL_CONTENT_CHARS = 20
+
+
+def _has_substantive_content(content: str) -> bool:
+    visible = visible_seat_text(content)
+    return sum(character.isalnum() for character in visible) >= MIN_MEANINGFUL_CONTENT_CHARS
+
 # 禁两类工具：①**写文件**（write_file / str_replace）—— 并行席位互相写文件会打架；
 # ②**派活 / 脚本逃逸**（agent_orchestration / bash）—— 本面板里每个智能体只做自己那
 # 份分析交付，绝不该扮演「总控」去调度别人。弱模型（deepseek 等）拿到带「总控 / 业务
@@ -231,6 +245,9 @@ async def _run_one_agent(
         if isinstance(msg, dict) and (msg.get("type") or "").lower() in ("ai", "aimessage", "aimessagechunk"):
             last_ai = msg
             break
+    failure_reason = is_llm_error_message(last_ai)
+    if failure_reason:
+        raise RuntimeError(f"模型调用失败：{reason_text(failure_reason)}")
     content = _flatten_content(last_ai.get("content", ""))
     # 收集**所有** AI 消息的 tool_calls（全量 args，按顺序）—— 用于在收口时补发所有步骤
     # （含 ls / skill_list 这类无参/中间步骤），保证步骤条不丢步、且 args 完整。
@@ -250,6 +267,8 @@ async def _run_one_agent(
             "tool_calls": final_tool_calls,
         }
     else:
+        if not _has_substantive_content(content):
+            raise RuntimeError("智能体未生成有效正文，请重试或更换全局模型")
         yield {
             "status": f"子智能体 {agent_id} 完成",
             "content": content,
@@ -408,8 +427,24 @@ async def run_parallel_agents_stream(request: Request, payload: dict = Body(...)
                             await _emit_tool(tc)
             if not done_sent:
                 # 流被抢占/截断,没收到终态帧 —— 用已累积正文兜底收口本席位。
+                buffered_content = "".join(buffer)
+                failure_reason = is_llm_error_message(
+                    {"type": "ai", "content": buffered_content}
+                )
+                if failure_reason:
+                    raise RuntimeError(
+                        f"模型调用失败：{reason_text(failure_reason)}"
+                    )
+                if not _has_substantive_content(buffered_content):
+                    raise RuntimeError(
+                        "智能体未生成有效正文，请重试或更换全局模型"
+                    )
                 await queue.put(
-                    {"type": "agent_done", "agent_id": agent_id, "content": "".join(buffer)}
+                    {
+                        "type": "agent_done",
+                        "agent_id": agent_id,
+                        "content": buffered_content,
+                    }
                 )
         except Exception as exc:  # noqa: BLE001 — 单个 agent 失败不拖垮其它
             logger.warning("[parallel-agents] %s failed: %r", agent_id, exc)

offline-backend-20260512/backend/extensions_config.json

@@ -26,7 +26,7 @@
       "enabled": true
     },
     "policy-knowledge": {
-      "enabled": false
+      "enabled": true
     },
     "html-page-builder": {
       "enabled": true

offline-backend-20260512/backend/packages/harness/deerflow/agents/middlewares/llm_error_handling_middleware.py

@@ -96,9 +96,11 @@ _BUSY_PATTERNS = (
     "稍后重试",
     "请稍后重试",
 )
-_QUOTA_PATTERNS = (
-    "insufficient_quota",
-    "quota",
+_QUOTA_PATTERNS = (
+    "insufficient_quota",
+    "insufficient balance",
+    "token plan limit",
+    "quota",
     "billing",
     "credit",
     "payment",
@@ -122,8 +124,10 @@ _AUTH_PATTERNS = (
 # error wrapped as `bad_response_status_code`, or a truncated/garbled inference
 # response). These are almost always transient inference-side issues and safe
 # to retry.
-_UPSTREAM_GARBAGE_PATTERNS = (
-    "bad_response_status_code",
+_UPSTREAM_GARBAGE_PATTERNS = (
+    "openai-compatible upstream application error",
+    "null value for 'choices'",
+    "bad_response_status_code",
     "bad response status",
     "expecting ',' delimiter",
     "expecting value",

offline-backend-20260512/backend/packages/harness/deerflow/models/patched_openai.py

@@ -25,7 +25,8 @@ message that originally carried it:
 
 from __future__ import annotations
 
-from typing import Any
+from collections.abc import Mapping
+from typing import Any
 
 from langchain_core.language_models import LanguageModelInput
 from langchain_core.messages import AIMessage, AIMessageChunk
@@ -34,6 +35,65 @@ from langchain_openai import ChatOpenAI
 
 from deerflow.models.message_ordering import normalize_chat_payload_messages
 
+
+class OpenAICompatibleUpstreamError(RuntimeError):
+    """An OpenAI-compatible gateway reported an error inside a HTTP 200 body.
+
+    Several compatible gateways do not use an HTTP error status for quota,
+    concurrency, or inference failures. Instead they return ``choices=null``
+    (or an empty streamed chunk) together with a vendor ``base_resp`` object.
+    LangChain raises a generic ``TypeError`` for the non-streaming shape and
+    treats the streaming shape as an empty successful response. Raising one
+    stable exception here lets DeerFlow's model middleware retry both paths.
+    """
+
+    def __init__(self, *, code: Any, message: str | None = None) -> None:
+        self.code = code
+        detail = _bounded_error_message(message)
+        suffix = f": {detail}" if detail else ""
+        super().__init__(f"OpenAI-compatible upstream application error (code={code}){suffix}")
+
+
+def _bounded_error_message(value: Any, *, limit: int = 500) -> str:
+    """Return a log-safe, bounded one-line provider message."""
+    if not isinstance(value, str):
+        return ""
+    normalized = " ".join(value.split())
+    return normalized[:limit]
+
+
+def _application_error(payload: Mapping[str, Any]) -> tuple[Any, str | None] | None:
+    """Extract a non-success ``base_resp`` error from a compatible payload."""
+    raw = payload.get("base_resp") or payload.get("baseResp")
+    if not isinstance(raw, Mapping):
+        return None
+
+    code = raw.get("status_code")
+    if code is None:
+        code = raw.get("statusCode")
+    if code is None:
+        code = raw.get("code")
+
+    # MiniMax-compatible responses use 0 for success. Be conservative for
+    # gateways that put informational metadata in ``base_resp``.
+    normalized_code = str(code).strip().lower() if code is not None else ""
+    if normalized_code in {"", "0", "200", "ok", "success"}:
+        return None
+
+    message = raw.get("status_msg")
+    if message is None:
+        message = raw.get("statusMsg")
+    if message is None:
+        message = raw.get("message")
+    return code, message if isinstance(message, str) else None
+
+
+def _raise_for_application_error(payload: Mapping[str, Any]) -> None:
+    error = _application_error(payload)
+    if error is not None:
+        code, message = error
+        raise OpenAICompatibleUpstreamError(code=code, message=message)
+
 
 class PatchedChatOpenAI(ChatOpenAI):
     """ChatOpenAI with ``thought_signature`` preservation for Gemini thinking via OpenAI gateway.
@@ -100,16 +160,20 @@ class PatchedChatOpenAI(ChatOpenAI):
         normalize_chat_payload_messages(payload)
         return payload
 
-    def _convert_chunk_to_generation_chunk(
-        self,
-        chunk: dict,
-        default_chunk_class: type,
-        base_generation_info: dict | None,
-    ) -> ChatGenerationChunk | None:
-        """Preserve streamed ``reasoning_content`` in ``additional_kwargs``."""
-        generation_chunk = super()._convert_chunk_to_generation_chunk(
-            chunk,
-            default_chunk_class,
+    def _convert_chunk_to_generation_chunk(
+        self,
+        chunk: dict,
+        default_chunk_class: type,
+        base_generation_info: dict | None,
+    ) -> ChatGenerationChunk | None:
+        """Preserve streamed ``reasoning_content`` in ``additional_kwargs``."""
+        # Some compatible gateways return a vendor error event followed by a
+        # normal-looking usage chunk, all under HTTP 200. Detect the first
+        # event before LangChain converts it into an empty AIMessageChunk.
+        _raise_for_application_error(chunk)
+        generation_chunk = super()._convert_chunk_to_generation_chunk(
+            chunk,
+            default_chunk_class,
             base_generation_info,
         )
         if generation_chunk is None:
@@ -130,11 +194,12 @@ class PatchedChatOpenAI(ChatOpenAI):
         self,
         response: dict | Any,
         generation_info: dict | None = None,
-    ) -> ChatResult:
-        """Preserve non-stream ``reasoning_content`` in ``additional_kwargs``."""
-        result = super()._create_chat_result(response, generation_info)
-        response_dict = response if isinstance(response, dict) else response.model_dump()
-        choices = response_dict.get("choices", [])
+    ) -> ChatResult:
+        """Preserve non-stream ``reasoning_content`` in ``additional_kwargs``."""
+        response_dict = response if isinstance(response, dict) else response.model_dump()
+        _raise_for_application_error(response_dict)
+        result = super()._create_chat_result(response, generation_info)
+        choices = response_dict.get("choices", [])
 
         generations: list[ChatGeneration] = []
         for index, generation in enumerate(result.generations):

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

@@ -11,9 +11,11 @@ import asyncio
 from types import SimpleNamespace
 
 import httpx
-from langchain_core.messages import AIMessage
+import pytest
+from langchain_core.messages import AIMessage, AIMessageChunk
 
 from deerflow.agents.middlewares.llm_error_handling_middleware import LLM_ERROR_MARKER, LLMErrorHandlingMiddleware
+from deerflow.models.patched_openai import OpenAICompatibleUpstreamError, PatchedChatOpenAI
 
 
 def _middleware() -> LLMErrorHandlingMiddleware:
@@ -26,6 +28,10 @@ def _middleware() -> LLMErrorHandlingMiddleware:
     return middleware
 
 
+def _openai_model() -> PatchedChatOpenAI:
+    return PatchedChatOpenAI(model="test-model", api_key="test-key")
+
+
 def test_httpx_read_timeout_is_transient() -> None:
     assert _middleware()._classify_error(httpx.ReadTimeout("read timed out")) == (True, "transient")
 
@@ -46,6 +52,98 @@ def test_value_error_stays_generic() -> None:
     assert _middleware()._classify_error(ValueError("boom")) == (False, "generic")
 
 
+def test_openai_compatible_embedded_error_is_retriable_upstream() -> None:
+    error = RuntimeError("OpenAI-compatible upstream application error (code=2056)")
+    assert _middleware()._classify_error(error) == (True, "upstream")
+
+
+def test_openai_compatible_null_choices_error_is_retriable_upstream() -> None:
+    error = TypeError("Received response with null value for 'choices'.")
+    assert _middleware()._classify_error(error) == (True, "upstream")
+
+
+def test_insufficient_balance_stays_non_retriable_quota() -> None:
+    """The 200-body compatibility fix must not hide a real billing failure."""
+
+    class PaymentError(RuntimeError):
+        status_code = 402
+
+    error = PaymentError("Insufficient Balance")
+    assert _middleware()._classify_error(error) == (False, "quota")
+
+
+def test_minimax_token_plan_limit_stays_non_retriable_quota() -> None:
+    error = OpenAICompatibleUpstreamError(
+        code=2056,
+        message="Token Plan limit reached",
+    )
+
+    assert _middleware()._classify_error(error) == (False, "quota")
+
+
+def test_non_stream_embedded_application_error_is_raised() -> None:
+    response = {
+        "id": "failed-response",
+        "object": "chat.completion",
+        "created": 0,
+        "model": "test-model",
+        "choices": None,
+        "base_resp": {
+            "status_code": 2056,
+            "status_msg": "Token Plan limit reached",
+        },
+    }
+
+    with pytest.raises(OpenAICompatibleUpstreamError, match=r"code=2056") as exc_info:
+        _openai_model()._create_chat_result(response)
+
+    assert exc_info.value.code == 2056
+    assert "Token Plan limit reached" in str(exc_info.value)
+
+
+def test_stream_embedded_application_error_is_raised() -> None:
+    chunk = {
+        "id": "failed-response",
+        "object": "chat.completion.chunk",
+        "created": 0,
+        "model": "test-model",
+        "choices": [],
+        "base_resp": {
+            "status_code": 2056,
+            "status_msg": "Token Plan limit reached",
+        },
+    }
+
+    with pytest.raises(OpenAICompatibleUpstreamError, match=r"code=2056"):
+        _openai_model()._convert_chunk_to_generation_chunk(chunk, AIMessageChunk, None)
+
+
+def test_normal_empty_usage_chunk_is_not_treated_as_error() -> None:
+    chunk = {
+        "id": "usage-response",
+        "object": "chat.completion.chunk",
+        "created": 0,
+        "model": "test-model",
+        "choices": [],
+        "usage": {
+            "prompt_tokens": 3,
+            "completion_tokens": 2,
+            "total_tokens": 5,
+        },
+    }
+
+    result = _openai_model()._convert_chunk_to_generation_chunk(chunk, AIMessageChunk, None)
+
+    assert result is not None
+    assert result.message.usage_metadata == {
+        "input_tokens": 3,
+        "output_tokens": 2,
+        "total_tokens": 5,
+        "input_token_details": {},
+        "output_token_details": {},
+    }
+
+
 def test_read_timeout_is_retried_and_recovers() -> None:
     """第一次 ReadTimeout、第二次成功：必须重试并返回真实结果。"""
     middleware = _middleware()

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

@@ -13,9 +13,14 @@
 from __future__ import annotations
 
 import asyncio
+import json
+from contextlib import asynccontextmanager
 from types import SimpleNamespace
 
+import pytest
+
 import app.gateway.roundtable_model_fallback as mf
+import app.gateway.routers.parallel_agents as parallel_agents
 from app.gateway.roundtable_model_fallback import (
     fallback_model_chain,
     is_llm_error_message,
@@ -56,6 +61,181 @@ def test_is_llm_error_message_normal_is_none() -> None:
     assert is_llm_error_message({"type": "ai", "content": ""}) is None
 
 
+def test_parallel_agent_run_raises_instead_of_completing_llm_fallback(monkeypatch) -> None:
+    fallback_message = {
+        "type": "ai",
+        "content": "大模型本次调用未能成功完成，请稍后再试或更换模型。",
+    }
+
+    async def fake_stream_upstream(*_args, **_kwargs):
+        yield None, [f"data: {json.dumps({'messages': [fallback_message]}, ensure_ascii=False)}"]
+
+    monkeypatch.setattr(parallel_agents, "_stream_upstream", fake_stream_upstream)
+
+    async def collect() -> list[object]:
+        return [
+            item
+            async for item in parallel_agents._run_one_agent(
+                None,  # type: ignore[arg-type]
+                "http://gateway.test",
+                {"Authorization": "Bearer test"},
+                "strategy-selection-intent",
+                "thread-id",
+                "test task",
+                "",
+            )
+        ]
+
+    try:
+        asyncio.run(collect())
+    except RuntimeError as exc:
+        assert "模型调用失败" in str(exc)
+    else:
+        raise AssertionError("LLM fallback message must not be emitted as agent_done")
+
+
+def test_parallel_agent_run_rejects_punctuation_only_delivery(monkeypatch) -> None:
+    invalid_message = {"type": "ai", "content": "!" * 500}
+
+    async def fake_stream_upstream(*_args, **_kwargs):
+        yield None, [f"data: {json.dumps({'messages': [invalid_message]}, ensure_ascii=False)}"]
+
+    monkeypatch.setattr(parallel_agents, "_stream_upstream", fake_stream_upstream)
+
+    async def collect() -> list[object]:
+        return [
+            item
+            async for item in parallel_agents._run_one_agent(
+                None,  # type: ignore[arg-type]
+                "http://gateway.test",
+                {"Authorization": "Bearer test"},
+                "strategy-selection-angle-security",
+                "thread-id",
+                "test task",
+                "",
+            )
+        ]
+
+    try:
+        asyncio.run(collect())
+    except RuntimeError as exc:
+        assert "未生成有效正文" in str(exc)
+    else:
+        raise AssertionError("Punctuation-only output must not be emitted as agent_done")
+
+
+def test_parallel_agent_run_allows_empty_content_clarification(monkeypatch) -> None:
+    clarification_message = {
+        "type": "ai",
+        "content": "",
+        "tool_calls": [
+            {
+                "id": "clarify-1",
+                "name": "ask_clarification",
+                "args": {
+                    "question": "请确认策略时间范围。",
+                    "clarification_type": "single_choice",
+                    "options": ["短期", "长期"],
+                    "allow_custom": True,
+                },
+            }
+        ],
+    }
+
+    async def fake_stream_upstream(*_args, **_kwargs):
+        yield None, [
+            f"data: {json.dumps({'messages': [clarification_message]}, ensure_ascii=False)}"
+        ]
+
+    monkeypatch.setattr(parallel_agents, "_stream_upstream", fake_stream_upstream)
+
+    async def collect() -> list[object]:
+        return [
+            item
+            async for item in parallel_agents._run_one_agent(
+                None,  # type: ignore[arg-type]
+                "http://gateway.test",
+                {"Authorization": "Bearer test"},
+                "strategy-selection-intent",
+                "thread-id",
+                "test task",
+                "",
+            )
+        ]
+
+    events = asyncio.run(collect())
+
+    assert len(events) == 1
+    event = events[0]
+    assert isinstance(event, dict)
+    assert event["type"] == "clarification"
+    assert event["content"] == ""
+    assert event["clarification"]["question"] == "请确认策略时间范围。"
+
+
+def test_parallel_agent_substantive_content_accepts_chinese_and_english() -> None:
+    assert parallel_agents._has_substantive_content("这是一份包含目标、前置条件、阶段路径和验收标准的完整策略。")
+    assert parallel_agents._has_substantive_content(
+        "A complete strategy with objectives, prerequisites, milestones, and measurable outcomes."
+    )
+    assert not parallel_agents._has_substantive_content("<think>internal reasoning only</think>!!!")
+
+
+@pytest.mark.parametrize(
+    ("buffered_content", "expected_error"),
+    [
+        ("大模型本次调用未能成功完成，请稍后再试或更换模型。", "模型调用失败"),
+        ("", "未生成有效正文"),
+        ("<think>internal reasoning only</think>", "未生成有效正文"),
+        ("!" * 500, "未生成有效正文"),
+    ],
+)
+def test_parallel_agent_truncated_stream_rejects_invalid_buffer(
+    monkeypatch,
+    buffered_content: str,
+    expected_error: str,
+) -> None:
+    async def fake_run_one_agent(*_args, **_kwargs):
+        yield "event: messages"
+        yield f"data: {json.dumps([{'type': 'ai', 'content': buffered_content}], ensure_ascii=False)}"
+
+    @asynccontextmanager
+    async def fake_client(*_args, **_kwargs):
+        yield object()
+
+    async def fake_create_thread(*_args, **_kwargs):
+        return "thread-id"
+
+    monkeypatch.setattr(parallel_agents, "_run_one_agent", fake_run_one_agent)
+    monkeypatch.setattr(parallel_agents, "_make_loopback_client", fake_client)
+    monkeypatch.setattr(parallel_agents, "_create_thread", fake_create_thread)
+    monkeypatch.setattr(parallel_agents, "_loopback_base", lambda _request: "http://gateway.test")
+    monkeypatch.setattr(parallel_agents, "_auth_headers", lambda _request: {})
+
+    async def collect() -> list[dict[str, object]]:
+        response = await parallel_agents.run_parallel_agents_stream(
+            SimpleNamespace(),
+            {
+                "task_name": "test task",
+                "brief": "test brief",
+                "agent_ids": ["strategy-selection-intent"],
+            },
+        )
+        events: list[dict[str, object]] = []
+        async for chunk in response.body_iterator:
+            text = chunk.decode() if isinstance(chunk, bytes) else chunk
+            for line in text.splitlines():
+                if line.startswith("data:"):
+                    events.append(json.loads(line[5:].strip()))
+        return events
+
+    events = asyncio.run(collect())
+    assert not any(event.get("type") == "agent_done" for event in events)
+    errors = [event for event in events if event.get("type") == "agent_error"]
+    assert len(errors) == 1
+    assert expected_error in str(errors[0].get("message"))
+
+
 # ── 中间件给兜底 AIMessage 打标记 ────────────────────────────────────────────
 
 

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

@@ -6,9 +6,13 @@ from pathlib import Path
 
 import pytest
 import yaml
+from fastapi import HTTPException
 
 from app.gateway.routers import _strategy_selection_seed as seed
+from app.gateway.routers import agents as agents_router
 from deerflow.config.paths import Paths
+from deerflow.persistence.skills.memory import MemorySkillStore
+from deerflow.skills.types import Skill, SkillCategory
 
 
 @pytest.fixture()
@@ -73,6 +77,18 @@ def test_seed_assets_use_role_appropriate_existing_skills_and_tools() -> None:
     assert solution["tool_groups"] == ["file:write"]
 
 
+def test_default_strategy_skills_are_enabled_in_the_system_catalog() -> None:
+    extensions_path = Path(__file__).resolve().parents[1] / "extensions_config.json"
+    extensions = yaml.safe_load(extensions_path.read_text(encoding="utf-8")) or {}
+    configured = extensions.get("skills") or {}
+
+    # A missing entry means enabled by default.  An explicit false would make
+    # the seeded allowlist impossible to save under the server-side validator
+    # and silently remove the skill from strategy runs.
+    for skill_name in ("intent-clarification-policy", "policy-knowledge"):
+        assert (configured.get(skill_name) or {}).get("enabled", True) is True
+
+
 def test_seed_assets_define_machine_readable_handoff_contracts() -> None:
     intent_soul = _asset(seed.STRATEGY_INTENT_AGENT_ID, "SOUL.md").read_text(encoding="utf-8")
     judge_soul = _asset(seed.STRATEGY_JUDGE_AGENT_ID, "SOUL.md").read_text(encoding="utf-8")
@@ -113,3 +129,120 @@ def test_seed_creates_once_and_never_overwrites_admin_changes(tmp_paths: Paths)
 
     assert seed.ensure_strategy_selection_agents() == []
     assert customized_soul.read_text(encoding="utf-8") == "管理员现场修改"
+
+
+class _SkillStorage:
+    def __init__(self, skills: list[Skill]) -> None:
+        self._skills = skills
+
+    def load_skills(self, *, enabled_only: bool) -> list[Skill]:
+        if enabled_only:
+            return [skill for skill in self._skills if skill.enabled]
+        return list(self._skills)
+
+
+def _skill(name: str, *, category: SkillCategory, enabled: bool = True) -> Skill:
+    directory = Path("skills") / category.value / name
+    return Skill(
+        name=name,
+        description=name,
+        license=None,
+        skill_dir=directory,
+        skill_file=directory / "SKILL.md",
+        relative_path=Path(name),
+        category=category,
+        enabled=enabled,
+    )
+
+
+@pytest.mark.asyncio
+async def test_strategy_skill_validation_accepts_only_global_catalog_names(
+    monkeypatch: pytest.MonkeyPatch,
+) -> None:
+    skill_store = MemorySkillStore()
+    await skill_store.create(
+        {
+            "name": "published-custom",
+            "owner_user_id": "publisher",
+            "published": True,
+        }
+    )
+    storage = _SkillStorage(
+        [
+            _skill("public-skill", category=SkillCategory.PUBLIC),
+            _skill("published-custom", category=SkillCategory.CUSTOM),
+        ]
+    )
+    monkeypatch.setattr(agents_router, "get_or_new_skill_storage", lambda **_: storage)
+    monkeypatch.setattr(
+        agents_router,
+        "get_skill_usage_entries",
+        lambda: {},
+    )
+
+    result = await agents_router._validate_strategy_agent_skills(
+        [" public-skill ", "published-custom", "public-skill"],
+        app_config=object(),  # type: ignore[arg-type]
+        skill_store=skill_store,
+    )
+
+    assert result == ["public-skill", "published-custom"]
+
+
+@pytest.mark.asyncio
+@pytest.mark.parametrize(
+    ("requested", "detail_fragment"),
+    [
+        ("missing", "Unknown strategy agent skills"),
+        ("disabled", "Disabled or archived strategy agent skills"),
+        ("stale", "Disabled or archived strategy agent skills"),
+        ("private-custom", "must be globally available"),
+        ("orphan-custom", "must be globally available"),
+    ],
+)
+async def test_strategy_skill_validation_rejects_unselectable_names(
+    monkeypatch: pytest.MonkeyPatch,
+    requested: str,
+    detail_fragment: str,
+) -> None:
+    skill_store = MemorySkillStore()
+    await skill_store.create(
+        {
+            "name": "private-custom",
+            "owner_user_id": "owner",
+            "published": False,
+        }
+    )
+    storage = _SkillStorage(
+        [
+            _skill("disabled", category=SkillCategory.PUBLIC, enabled=False),
+            _skill("stale", category=SkillCategory.PUBLIC),
+            _skill("private-custom", category=SkillCategory.CUSTOM),
+            _skill("orphan-custom", category=SkillCategory.CUSTOM),
+        ]
+    )
+    monkeypatch.setattr(agents_router, "get_or_new_skill_storage", lambda **_: storage)
+    monkeypatch.setattr(
+        agents_router,
+        "get_skill_usage_entries",
+        lambda: {"stale": {"state": "stale"}},
+    )
+
+    with pytest.raises(HTTPException) as exc_info:
+        await agents_router._validate_strategy_agent_skills(
+            [requested],
+            app_config=object(),  # type: ignore[arg-type]
+            skill_store=skill_store,
+        )
+
+    assert exc_info.value.status_code == 422
+    assert detail_fragment in str(exc_info.value.detail)
+
+
+def test_fixed_strategy_role_agents_cannot_be_deleted() -> None:
+    for agent_id in seed.required_agent_ids():
+        with pytest.raises(HTTPException) as exc_info:
+            agents_router._ensure_strategy_agent_deletable(agent_id)
+        assert exc_info.value.status_code == 409
+
+    agents_router._ensure_strategy_agent_deletable("ordinary-custom-agent")