代码修改

frontend-web/src/assets/icon/down-logo.svg

@@ -0,0 +1 @@
+<svg xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" width="16" height="16" viewBox="0 0 16 16"><defs><style>.a{fill:#fff;opacity:0;}.b{fill:url(#a);}</style><linearGradient id="a" x1="0.277" y1="0.03" x2="0.725" y2="1.083" gradientUnits="objectBoundingBox"><stop offset="0" stop-color="#92eeff"/><stop offset="1" stop-color="#00c7ff"/></linearGradient></defs><g transform="translate(-128.5 -117)"><rect class="a" width="16" height="16" transform="translate(128.5 117)"/><path class="b" d="M4,0,8,5H0Z" transform="translate(140.5 128) rotate(180)"/></g></svg>

frontend-web/src/assets/icon/nav-active.svg

@@ -0,0 +1 @@
+<svg xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" width="84.499" height="70" viewBox="0 0 84.499 70"><defs><style>.a{fill:url(#a);}</style><linearGradient id="a" x1="0.043" x2="0.978" y2="1.016" gradientUnits="objectBoundingBox"><stop offset="0" stop-color="#0062d9" stop-opacity="0.6"/><stop offset="1" stop-color="#0062d9" stop-opacity="0.302"/></linearGradient></defs><path class="a" d="M8855.277-1940.39l-.054-70h78v31.183l6.5,5.257-6.5,5.259v28.3Z" transform="translate(-8855.224 2010.389)"/></svg>

frontend-web/src/assets/icon/nav-line-logo.svg

@@ -0,0 +1 @@
+<svg xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" width="77" height="45" viewBox="0 0 77 45"><defs><style>.a{fill:url(#a);}</style><pattern id="a" preserveAspectRatio="none" width="100%" height="100%" viewBox="0 0 340 45"><image width="340" height="45" xlink:href="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAVQAAAAtCAYAAADxyJMIAAAABHNCSVQICAgIfAhkiAAAIABJREFUeF7tnd2O5MZ1x5vdPTO7WkmGhMiQDQS5NODbvEBeIgbygcRwjOQur+D1K+QiQC4CBMld8hJ+CgO+DpAIcixblvZjZnqG+f/PqcM6Vawii+zuda+0XLSaXawvFos//s85xVHX9/3mXFvXdeeq+htSb/9mB4iX+vlmfZu/PKLs1BX7/ET1fndznsn8w5X1Pkc5jvfPV5ZfPcu784zD6v683QWXMLJbknnpsHy7gXpmWP5sIYRaYHgqsC2dKG97/haQL4Xy2SH8Drqt024JI98BtXVUi/nOBM0pWLaAkX09JRx/sBDe+Vj99sjyR10jV/ijI5Xir44s78+jBcLMPwXis0H3HWz9pXoH1FPdgFLPCaF5DCjXAvLrALM/rQzKuWH36QnH7xTX9bMzw2IO2muhPAfgNwbeM4/fKa7xiet4B9RVAzq4ndb7GL3nquSrnFKXrcBcqhbngHlO4P3+Qp3oH54xcDAH7Dng5nO3FcBTwC3Blv5d29bPeNfbby5o3wF1EVBH/vtl0+tn0ti4TA2ex4JzDpD5uc8B81TQe3FhSnTRHEDmZycCwhys54Cb97sG4GNBW1O0R7sRTjSOS6/fGfO/A2pxcJsDnykcFZjlLYdmGZZj2JZUZisof4iufJHBaykUW+D38QJ1+fIth6ld3fcWwOCLTOUSyPm4zkHa4MvrVwNxK4BL4F0L3bO4DxaM7RnhuKbqd0BdEzuo+TdLSnNOZY6B2W3mgFlSki2grMFxCoinAOBtBbg3ATS14zajP3FT+/WJgPzE3bS/XnPruDJ2HsdUUwL0/6DC78tDsfyEb4Vw3q858K4B7tiN0CNI5rd4Dj+fHajC+S4zBmdbOFOGbxlQm5VnHO4SPH85HNar/Pno6kwrzTZgah05KKlO8rQSKEuQXArHGugIuBawEVot+fzw3U5E+W/w9Js67utZkrd0c7H8kq31XJmvBvClYC5BuATfHLylOWSq92P0L87v8gh44I6V7XjcctiWVG0K2caxvzzIfguA2nht8qkzDVLNXVef3eYHSYVUnbaNZ0GuOBWY5dmSw/M18lLF+C0Hp4GxdMPWoPnBCZRgK/xmwPXRswUuhSUQDHl/+2JF4KkE7KUQLvX1q4q5O3Xt8mM5aKl0nxTcDrWxyl0KU4o2wlVvtCnXQTtYV9y0lwHXbyhQF16PHJ7+Ca3qs361vMk+pTw9NKPCTOtNYanHcqU5pTJPBccZELYC7vFEQF3ByDdSZBsAaudpv+canwX4UjAvgbB1Lodui7K1sh64Ebbjm25ayVptWu67btRyBbs4+PWHg+s3AKiL4ZnOd+/3HJvuqao01VkDZ6o0O5jmaXn75cGpwNSMY1imM6MEzDklWYNaTfUh/3fQFcLh5EC8v5BF+3PEaz1+tdAt0Fjvl1NAranpOQiXoDvnYvDQ9cBNXQjpDViGLc885jPQ/koGpH4De0Wb+mM3y1/RfTOQfQuBugCgpah7C0BT1elvA70qn2brUBWcZbX5x6H4i2C2KjTHV/e22yb3WwRleSaUQFmA5HeOUYmNAOyfnsA90Aibty7bl7jY141R6yMAXYRwCb5LwVuDrsH2Wf8o1+S/8RkHyfRGmXch9JuP3JWtuQ2mAEswzwe7XCPnAexbBNRGkFq25xi7sXO9KwSQNhP+TsJzPPI+KGRqk+A0aD5DJ14EyHrV6RXmJw6qMXAT24og1LQMlgZKb2bOKsoaIClJC1t/dxpQ9nfjB0h3rcqkdEyeTuH4VJ5TwbWlran++vLH9KkKXkC5uM0AuDQ3RuDNoVsCbm1FxE2AKTsXAYslYWEaP4PflqDV+Rtv4AjYmOb9tPkqA1WyMhWGPe8isES6Cp6HH828bM7YdGkvHKiNEOWp5mrUYDq1bGnKhDcVOl6O1GENoQ1uBx+n7kdwlsx0TUvN81Z4Sr4mpTmjKE+pJGsgbJp1LlN/OG/AaWl/avm7/YrAVaGyU8GXVXevZpRvg+IdAZaK9Ius4zVV+1Wn6pRbVLLpTWugVZeBHist9zLIlgJg0UUw5R7Qfoz9rwumwPFwvVCgNoLUQ3QcSJI5N4xmhOd4gE2FlnyeCk8LEOV+Tk3PfZs1c11VZ644c2DmVzX+rgDzGFC2gHE19J4UFO5XGIEPFszxS83K87DNzud1o2mfnVMLrI8BcRW8a4DrFe3NJgJVz0lv3NRf2zvY2pn3ULS2vnYtZLW9qF7jqNYCXM0ugfVgvSCgNtw5BtDclC8Fk8wPGpcraQPe/xkBqsfSYBFTOihP65jBU9O5jddjhjwO5GqqT0EzB+bwO4By8dWdguQiOJaA2HCZzpWlb/TptrbfNQClta6j8xHQV21AngPwWviOwDs9Pn2ibhW0erNERRuVUVx/G/Ikil8By/JfqCdI6nkW0mxwP3THPstuizTQlV6O8XItPX4GwF42UOtm/Hj++nWfPgofAcpF8ikczXS3pUlT8PzAKVWrxfyc0b85D84IBZ0tGtCpq1J3rAbKWUieAYwnhdvNhUf/b08XzT8LxGeUcQ3AS8BbgG1ZnWIyB9BGmBpsU9fBWM3mboMcsgrYuNVWFKQBLl9C2zQFO145MOZKkjKvbS4XqK0wTU35eMbRB5oO0liFjpcrmQk/XpLU4U0dbonZnvk3/ah3m1RVdc48T/OlvewyeEbV2uJzPAFAVwHz0sE4c7uc/PAKEJ8EuA2uh2MhC8CmQL1KzP/EZwfAat7oLoAbYPSQ6gdXQe1FhXTpluiR4Zqpet1sch+swTVforUaqvH2L82XywNqbtaXzXk9F2/Opwvn47nWVaiOzG1gVWk9p19yFFRogOdYUdbBmV8BVaYa+U6g6pRmWbEeCcpmSP4BwDirsk9Ou7YK58zrtloW5KKZ/XVb/qPhu0LZOlWbBzrUhNNAWTxWAe2gYvX+rLsKzB9bh6yW9+o1Va5xMCNcx0GaHLAr3QGXA9Tn4bxjdD6dVbWgEpXo+N12vmGk5cevYarvkzB77ca1Dk/rh1a4AJwllRnAYcCM4FRYjtO19aqtMQvJM8BxNfyusyCV+Qzvj1ue1T9Muwy63elM9mRS3rX5PHM8ngXSM2p4NXwr0MU5jEz+AmxjACIFbb9J/bOSb/DJpko2AteWb/FvIUwBtuR7bfW5rlKu8fa8HKD+WT7t8JsQrQeVIkjjMiYFafSFxgi8+kB1K8NzDC7n74Spnh8f4Adw+mOqQKNpHiEZFWbN3E+A6mA5BuqJQNkExxyEhUuVJ81BrqGKtzrLIog3gPlkEJ4A70Lo4g/fDA+UCM4UtHrT6Jpirwptv098swrZJF8Bsj7oFVcU3AzFbAVBBLGpV3ML8IgCNrZF9Tq1YsD7WyfU65LFdef9f0oZUPn9v+FeSk16TfSRefpDoxKNNyDNeKrQX0O5GEjp+/yYMO0677MeFsN75akL3eHHTCE6Y6ZzOVAEYqq6cuU5AmqAZ0x/H3VlAaylhKnC8pmrqUEdrobjIVOOT9HuHpM4T6+dWK48qTRn1OjG1OhcvrzNNSr2VVYJz23F1gRfvwLgRbmRo6FbcDdMQLYESK5UMOUKn+jQz971LcLUvbxBuA0vNnyZuAwkv3tJoRcs2HrZG2mD/le757lMKw6QD2ylbgHNk75QoGnfw+cX2RinS7H0YAGslwPUf3AnYCAtReipRhWiCh9To+YLZZpF5DWApBsGs7A4ntCSrRIsGvk6R8ozNdVjvzL/qLRxv/Gvl6aQVcU5p1yzq5wo4dGxTYOyXA1L35oHJKGZb0vhFsr3rt4uwMqnFVratObLy1q5Up3FtDkAe9iuBK1vtwm6E0p3NWzrirZ3sC2qT7uM8q1qNsI0fVECMI3H3HlHBVtzEUTrlIEu3fw6WINr+ncJbEkWX4uVW1PKmVugtkqgAaqXA9QfuWFUv2g6jw2kClA9GANKMa9F4fk08kC1MgGgUoea8VLfhxzV7BXJzN/JP4FWU5oJCAumuh5PoVmC51i5qutgbPLPwPJoUJYgOQHGOdClF3PBr+s39CbV3ZJbob3/k6A2KJ9I6cpEngN9BborgMu/TTsAMoyI3pyp6V6HbR2yg6vg91qx1uHfDIuAjfVz5YAB1q8ioHqV+89dY32xIILV2iBgvb81XSWg9UwEsJbMovOa/P84AVGeRFSi0Yy3eU1wKkBT8JThKdec//nA+T4BzyHdgTOmlRWnh11s+2ZCiWaBp2qQ6rovqVmdXUsV35yJfT0G9ipAtsDv0BiAemIX9w1/v25sb98QkFoB6SKA72ZcCQsV8CR024FbB6WCdgTbgqItAtmrWe8q+OrawVUvUw/I6je3q+w4FSsDXKZcrQwBG5WrpipcU5eNh2tJtRYCWP3zxvlDCC2JYLVXqzm7H4cScZlTHlyK78Kb8jSfiFei5nd06pM1B3hKUwGesg94WleL5nbm2/RKU8uH7le+hzxoMwWkgqXbvKen78arC8Csmf/joa0B81hQ1gC5EIr9Q6PKfFgIW6t3h5uG+/y2jWC8Cmk+H4+XoLnDzZS3z7SGrbN2j4XxAgAvAu8pgPsyDER8kKiKVNO9DMZxOouYsk3KzKpap2a9mgZk07YNsApX3Uyt5urVg5X54uuwXrmqWyBLine truncated

frontend-web/src/components/page-sdebar.css

@@ -10,11 +10,12 @@
     flex-direction: column;
     align-items: center;
     padding: 12px 10px;
+    position: relative;
 }
 
 .item-nav{
     width:100%;
-    padding:14px 0;
+    padding:10px 0;
     border-bottom:1px solid rgba(85, 166, 254, 0.2);
     font-family:'Noto Sans S Chinese', sans-serif;
     font-weight:500;
@@ -39,4 +40,45 @@
     box-sizing:border-box;
     letter-spacing:6px;
     word-break:break-all;
+}
+
+.item-nav-content{ 
+    width: 155px;
+    height: 970px;
+    background: rgba(3, 38, 80, 0.8);
+    border: 1px solid;
+    border-color: rgba(43, 143, 254, 0.6);
+    border-radius: 4px;
+    backdrop-filter: blur(2px);
+    position: absolute;
+    left: 97px;
+    top: 0;
+    z-index: 1000;
+}
+
+.item-nav-active{
+    color:#ffffff;
+    position: relative;
+}
+
+.item-nav-active::before{
+    content: '';
+    position: absolute;
+    left: 0;
+    top: 0;
+    width:84.5px;
+    height:70px;
+    background: url('../assets/icon/nav-active.svg') no-repeat;
+    background-size: contain;
+}
+
+.item-nav-active::after{
+    content: '';
+    position: absolute;
+    left: 0;
+    top: 25px;
+    width:77px;
+    height:45px;
+    background: url('../assets/icon/nav-line-logo.svg') no-repeat;
+    background-size: cover;
 }

frontend-web/src/components/page-sidebar-dark.tsx

@@ -332,8 +332,9 @@ export function PageSidebarDark({
       {/* TODO: 在这里编写深色主题的侧边栏 HTML 结构 */}
       <div className="sidebar-contnet">
         <div className="sidebar-contents">
+          <div className="item-nav-content"></div>
           {visibleMenuItems.map((item) => (
-            <div key={item.id} className="item-nav">
+            <div key={item.id} className={`item-nav ${item.id === 'qa-center' ? 'item-nav-active' : ''}`}>
               <span className="item-nav__label">{item.label}</span>
             </div>
           ))}

frontend-web/src/open-canvas/components/ai-writing/AIWritingPanel.tsx

@@ -38,6 +38,7 @@ const ENABLE_PAUSE_RESUME_UI = false;
 import { AIWritingForm } from './AIWritingForm';
 import { AIWritingTimeline } from './AIWritingTimeline';
 import { InterventionCard } from './InterventionCard';
+import { SkillStepsCard } from './SkillStepsCard';
 import { WritingSkeletonCard } from './WritingSkeletonCard';
 import { DraftStreamingView } from './DraftStreamingView';
 import { IntentResultCard } from './IntentResultCard';
@@ -411,6 +412,8 @@ export function AIWritingPanel({
                   reviewResult={state.reviewResult}
                   draftTitle={state.currentDraftTitle}
                   revisionCount={state.revisionCount}
+                  skillSearchSteps={state.skillSearchSteps}
+                  skillSearchInProgress={state.status === 'researching' && state.skillSearchSteps.length > 0}
                   onSubmit={submitIntervention}
                   disabled={false}
                 />
@@ -444,10 +447,19 @@ export function AIWritingPanel({
           />
         )}
 
+        {/* 研究中 + 已有技能步骤：实时流式展示技能检索过程，避免 skeleton 卡片掩盖步骤 */}
+        {state.status === 'researching' && state.skillSearchSteps.length > 0 && (
+          <div className="px-4 pb-2">
+            <SkillStepsCard steps={state.skillSearchSteps} inProgress />
+          </div>
+        )}
+
         {showSkeleton &&
          state.status !== 'writing_draft' &&
          !(state.status === 'writing_outline' && (state.outlineStreamingText || state.outlineThinkingText)) &&
          !(state.status === 'reviewing' && state.streamingReviewItems.length > 0) &&
+         /* 技能检索已经在流式展示步骤，不需要再叠加 skeleton */
+         !(state.status === 'researching' && state.skillSearchSteps.length > 0) &&
          /* 意图解析流式过程中（LLM 还在吐 JSON）不要显示 skeleton */
          !state.intentStreamingText && !state.intentThinkingText && (
           <div className="px-4 pb-4">

frontend-web/src/open-canvas/components/ai-writing/InterventionCard.tsx

@@ -2,7 +2,7 @@ import { useRef, useState } from 'react';
 import {
   PauseCircle, CheckCircle2, RotateCcw, Search,
   RefreshCw, PenLine, ArrowRight, ShieldAlert, ClipboardEdit, SendHorizonal,
-  Trash2, BookOpen,
+  Trash2, BookOpen, Sparkles,
 } from 'lucide-react';
 import { Button } from '@/components/ui/button';
 import { cn } from '@/lib/utils';
@@ -10,11 +10,13 @@ import type {
   AIMaterial, AIOutline, ReviewResult, ReviewIssue,
   ProgressEvent, UserInterventionPayload,
   BlockedSection, SectionDecisionKind,
+  SkillSearchStep,
 } from '../../types/ai-writing';
 import { MaterialsCard } from './MaterialsCard';
 import { MaterialsToolbar } from './MaterialsToolbar';
 import { OutlineCard } from './OutlineCard';
 import { ReviewCard } from './ReviewCard';
+import { SkillStepsCard } from './SkillStepsCard';
 
 interface InterventionCardProps {
   pauseEvent: ProgressEvent;
@@ -23,18 +25,29 @@ interface InterventionCardProps {
   reviewResult: ReviewResult | null;
   draftTitle: string;
   revisionCount: number;
+  skillSearchSteps?: SkillSearchStep[];
+  /** 是否正在检索中（researching/awaiting 切换之间，前端用于流式展示步骤进行中） */
+  skillSearchInProgress?: boolean;
   onSubmit: (payload: UserInterventionPayload) => void;
   disabled?: boolean;
 }
 
 export function InterventionCard({
   pauseEvent, materials, outline, reviewResult,
-  draftTitle, revisionCount, onSubmit, disabled,
+  draftTitle, revisionCount, skillSearchSteps, skillSearchInProgress, onSubmit, disabled,
 }: InterventionCardProps) {
   const pausePoint = pauseEvent.pausePoint;
 
   if (pausePoint === 'material_confirm') {
-    return <MaterialConfirmCard materials={materials} onSubmit={onSubmit} disabled={disabled} />;
+    return (
+      <MaterialConfirmCard
+        materials={materials}
+        skillSearchSteps={skillSearchSteps ?? []}
+        skillSearchInProgress={skillSearchInProgress}
+        onSubmit={onSubmit}
+        disabled={disabled}
+      />
+    );
   }
 
   if (pausePoint === 'outline_confirm') {
@@ -106,30 +119,40 @@ function formatSelectedIssues(issues: ReviewIssue[], selectedIndices: Set<number
 
 interface MaterialConfirmCardProps {
   materials: AIMaterial[];
+  skillSearchSteps: SkillSearchStep[];
+  skillSearchInProgress?: boolean;
   onSubmit: (payload: UserInterventionPayload) => void;
   disabled?: boolean;
 }
 
-function MaterialConfirmCard({ materials, onSubmit, disabled }: MaterialConfirmCardProps) {
+function MaterialConfirmCard({ materials, skillSearchSteps, skillSearchInProgress, onSubmit, disabled }: MaterialConfirmCardProps) {
   const [selectedIds, setSelectedIds] = useState<Set<string>>(
     () => new Set(materials.map((m) => m.id)),
   );
-  const [extraKeywords, setExtraKeywords] = useState<string[]>([]);
+  const [userQuery, setUserQuery] = useState('');
   const [submitting, setSubmitting] = useState(false);
 
   async function handleConfirm() {
     setSubmitting(true);
-    await onSubmit({ action: 'confirm', approvedMaterialIds: [...selectedIds], extraKeywords });
+    await onSubmit({ action: 'confirm', approvedMaterialIds: [...selectedIds], userQuery: userQuery.trim() || undefined });
     setSubmitting(false);
   }
 
   async function handleReSearch() {
     setSubmitting(true);
-    await onSubmit({ action: 're_search', approvedMaterialIds: [], extraKeywords });
+    await onSubmit({ action: 're_search', approvedMaterialIds: [], userQuery: userQuery.trim() || undefined });
     setSubmitting(false);
   }
 
-  const hasExtra = extraKeywords.length > 0;
+  async function handleEnableSkillSearch() {
+    setSubmitting(true);
+    await onSubmit({ action: 'enable_skill_search', userQuery: userQuery.trim() || undefined });
+    setSubmitting(false);
+  }
+
+  const hasQuery = userQuery.trim().length > 0;
+  // 当前素材是否来自技能检索：根据素材 sourceType 推断（覆盖式替换后全是 skill）
+  const isSkillResult = materials.length > 0 && materials.every((m) => m.sourceType === 'skill');
 
   // 空数据态：未检索到任何素材，提示用户重新搜索或在无素材情况下继续
   if (materials.length === 0) {
@@ -140,33 +163,45 @@ function MaterialConfirmCard({ materials, onSubmit, disabled }: MaterialConfirmC
           <div>
             <p className="text-xs font-medium">未检索到任何素材</p>
             <p className="text-xs text-muted-foreground mt-0.5">
-              素材收集专家本次没有检索到相关数据。你可以补充关键词重新搜索，或在无素材的情况下直接继续写作（文章将仅依据写作意图生成）。
+              素材收集专家本次没有检索到相关数据。你可以补充关键词重新搜索、启用技能检索，或在无素材的情况下直接继续写作。
             </p>
           </div>
         </div>
 
+        {(skillSearchSteps.length > 0 || skillSearchInProgress) && (
+          <SkillStepsCard steps={skillSearchSteps} inProgress={skillSearchInProgress} />
+        )}
+
         <MaterialsToolbar
           materials={materials}
           selectedIds={selectedIds}
           onSelectAll={() => setSelectedIds(new Set())}
           onDeselectAll={() => setSelectedIds(new Set())}
-          extraKeywords={extraKeywords}
-          onAddKeyword={(kw) => setExtraKeywords((prev) => [...prev, kw])}
-          onRemoveKeyword={(kw) => setExtraKeywords((prev) => prev.filter((k) => k !== kw))}
+          userQuery={userQuery}
+          onUserQueryChange={setUserQuery}
+          onSubmitQuery={handleReSearch}
+          disabled={disabled || submitting}
         />
 
-        <div className="flex gap-2 pt-1">
+        <div className="flex flex-wrap gap-2 pt-1">
           <Button
-            type="button" size="sm" className="flex-1 h-8 text-xs gap-1.5"
+            type="button" size="sm" className="flex-1 min-w-[140px] h-8 text-xs gap-1.5"
             onClick={handleReSearch} disabled={disabled || submitting}
           >
-            {hasExtra
-              ? <><Search className="size-3.5" />追加搜索</>
+            {hasQuery
+              ? <><Search className="size-3.5" />按输入重新搜索</>
               : <><RotateCcw className="size-3.5" />重新搜索</>}
           </Button>
+          <Button
+            type="button" variant="outline" size="sm"
+            className="h-8 text-xs gap-1.5 shrink-0 border-violet-200 text-violet-700 hover:bg-violet-50 dark:border-violet-800 dark:text-violet-300 dark:hover:bg-violet-950/30"
+            onClick={handleEnableSkillSearch} disabled={disabled || submitting}
+          >
+            <Sparkles className="size-3.5" />技能检索
+          </Button>
           <Button
             type="button" variant="outline" size="sm" className="h-8 text-xs gap-1.5 shrink-0"
-            onClick={handleConfirm} disabled={disabled || submitting}
+            onClick={() => onSubmit({ action: 'confirm', approvedMaterialIds: [] })} disabled={disabled || submitting}
           >
             <ArrowRight className="size-3.5" />无数据继续写作
           </Button>
@@ -182,11 +217,14 @@ function MaterialConfirmCard({ materials, onSubmit, disabled }: MaterialConfirmC
         <div>
           <p className="text-xs font-medium">需要您确认素材，才能继续</p>
           <p className="text-xs text-muted-foreground mt-0.5">
-            已搜集到 {materials.length} 条素材（默认全选）。您可以取消勾选不相关的素材，或补充关键词追加搜索。
+            已搜集到 {materials.length} 条{isSkillResult ? '技能素材' : '素材'}（默认全选）。
+            您可以取消勾选不相关的素材，或补充关键词追加搜索{isSkillResult ? '' : '，也可以启用技能检索从已启用的技能中获取素材'}。
           </p>
         </div>
       </div>
 
+      {skillSearchSteps.length > 0 && <SkillStepsCard steps={skillSearchSteps} />}
+
       <MaterialsCard materials={materials} selectedIds={selectedIds} onToggle={(id) => {
         setSelectedIds((prev) => {
           const next = new Set(prev);
@@ -200,24 +238,34 @@ function MaterialConfirmCard({ materials, onSubmit, disabled }: MaterialConfirmC
         selectedIds={selectedIds}
         onSelectAll={() => setSelectedIds(new Set(materials.map((m) => m.id)))}
         onDeselectAll={() => setSelectedIds(new Set())}
-        extraKeywords={extraKeywords}
-        onAddKeyword={(kw) => setExtraKeywords((prev) => [...prev, kw])}
-        onRemoveKeyword={(kw) => setExtraKeywords((prev) => prev.filter((k) => k !== kw))}
+        userQuery={userQuery}
+        onUserQueryChange={setUserQuery}
+        onSubmitQuery={handleReSearch}
+        disabled={disabled || submitting}
       />
 
-      <div className="flex gap-2 pt-1">
+      <div className="flex flex-wrap gap-2 pt-1">
         <Button
-          type="button" size="sm" className="flex-1 h-8 text-xs gap-1.5"
+          type="button" size="sm" className="flex-1 min-w-[180px] h-8 text-xs gap-1.5"
           onClick={handleConfirm} disabled={disabled || submitting || selectedIds.size === 0}
         >
           <CheckCircle2 className="size-3.5" />确认素材，开始规划大纲
         </Button>
+        {!isSkillResult && (
+          <Button
+            type="button" variant="outline" size="sm"
+            className="h-8 text-xs gap-1.5 shrink-0 border-violet-200 text-violet-700 hover:bg-violet-50 dark:border-violet-800 dark:text-violet-300 dark:hover:bg-violet-950/30"
+            onClick={handleEnableSkillSearch} disabled={disabled || submitting}
+          >
+            <Sparkles className="size-3.5" />技能检索
+          </Button>
+        )}
         <Button
           type="button" variant="outline" size="sm" className="h-8 text-xs gap-1.5 shrink-0"
           onClick={handleReSearch} disabled={disabled || submitting}
         >
-          {hasExtra
-            ? <><Search className="size-3.5" />追加搜索</>
+          {hasQuery
+            ? <><Search className="size-3.5" />按输入重新搜索</>
             : <><RotateCcw className="size-3.5" />重新搜索</>}
         </Button>
       </div>

frontend-web/src/open-canvas/components/ai-writing/MaterialItem.tsx

@@ -1,5 +1,5 @@
 import { useState } from 'react';
-import { ChevronRight, ExternalLink } from 'lucide-react';
+import { ChevronRight, ExternalLink, Sparkles } from 'lucide-react';
 import { cn } from '@/lib/utils';
 import { buildIntranetSourceUrl } from '@/core/config';
 import type { AIMaterial } from '../../types/ai-writing';
@@ -26,12 +26,14 @@ function relevanceLabel(score: number): string {
 export function MaterialItem({ material, checked, onToggle }: MaterialItemProps) {
   const [expanded, setExpanded] = useState(false);
   const pct = Math.round(material.relevanceScore * 100);
+  const isSkill = material.sourceType === 'skill';
 
   return (
     <div
       className={cn(
         'rounded-md border text-xs transition-colors',
         checked ? 'border-border bg-background' : 'border-border/50 bg-muted/30',
+        isSkill && checked && 'border-violet-300/70 dark:border-violet-800/60',
       )}
     >
       {/* 头部行 */}
@@ -50,6 +52,12 @@ export function MaterialItem({ material, checked, onToggle }: MaterialItemProps)
           onClick={() => setExpanded((v) => !v)}
           className="flex flex-1 items-start gap-1.5 text-left"
         >
+          {isSkill && (
+            <span className="mt-0.5 inline-flex items-center gap-0.5 px-1 py-0.5 rounded text-[10px] font-medium bg-violet-100 text-violet-700 dark:bg-violet-900/60 dark:text-violet-200 shrink-0">
+              <Sparkles className="size-2.5" />
+              技能
+            </span>
+          )}
           <span className={cn('flex-1 font-medium leading-snug line-clamp-2', !checked && 'text-muted-foreground')}>
             {material.title}
           </span>

frontend-web/src/open-canvas/components/ai-writing/MaterialsToolbar.tsx

@@ -1,6 +1,4 @@
-import { useState } from 'react';
-import { Plus } from 'lucide-react';
-import { Button } from '@/components/ui/button';
+import { useRef } from 'react';
 import type { AIMaterial } from '../../types/ai-writing';
 
 interface MaterialsToolbarProps {
@@ -8,9 +6,13 @@ interface MaterialsToolbarProps {
   selectedIds: Set<string>;
   onSelectAll: () => void;
   onDeselectAll: () => void;
-  extraKeywords: string[];
-  onAddKeyword: (kw: string) => void;
-  onRemoveKeyword: (kw: string) => void;
+  /** 单输入框文本：可以是技能名、检索来源、补充检索意图 */
+  userQuery: string;
+  onUserQueryChange: (text: string) => void;
+  /** 回车键提交（默认重新搜索；详细按钮交给父组件渲染） */
+  onSubmitQuery?: () => void;
+  placeholder?: string;
+  disabled?: boolean;
 }
 
 export function MaterialsToolbar({
@@ -18,18 +20,27 @@ export function MaterialsToolbar({
   selectedIds,
   onSelectAll,
   onDeselectAll,
-  extraKeywords,
-  onAddKeyword,
-  onRemoveKeyword,
+  userQuery,
+  onUserQueryChange,
+  onSubmitQuery,
+  placeholder,
+  disabled,
 }: MaterialsToolbarProps) {
-  const [kwInput, setKwInput] = useState('');
+  const textareaRef = useRef<HTMLTextAreaElement>(null);
   const allSelected = materials.length > 0 && selectedIds.size === materials.length;
 
-  function handleAddKeyword() {
-    const kw = kwInput.trim();
-    if (!kw || extraKeywords.includes(kw)) return;
-    onAddKeyword(kw);
-    setKwInput('');
+  function handleInput(e: React.ChangeEvent<HTMLTextAreaElement>) {
+    onUserQueryChange(e.target.value);
+    const el = e.target;
+    el.style.height = 'auto';
+    el.style.height = `${Math.min(el.scrollHeight, 96)}px`;
+  }
+
+  function handleKeyDown(e: React.KeyboardEvent<HTMLTextAreaElement>) {
+    if (e.key === 'Enter' && !e.shiftKey && onSubmitQuery) {
+      e.preventDefault();
+      onSubmitQuery();
+    }
   }
 
   return (
@@ -51,50 +62,21 @@ export function MaterialsToolbar({
         </div>
       )}
 
-      {/* 补充关键词 */}
+      {/* 单输入框 */}
       <div className="space-y-1.5">
-        <label className="text-xs text-muted-foreground">补充搜索关键词（可选）</label>
-        <div className="flex gap-1.5">
-          <input
-            type="text"
-            value={kwInput}
-            onChange={(e) => setKwInput(e.target.value)}
-            onKeyDown={(e) => e.key === 'Enter' && handleAddKeyword()}
-            placeholder="输入关键词后按 Enter 或点击 +"
-            className="flex-1 h-7 rounded-md border border-input bg-background px-2.5 py-1 text-xs placeholder:text-muted-foreground focus-visible:outline-none focus-visible:ring-1 focus-visible:ring-ring"
-          />
-          <Button
-            type="button"
-            variant="outline"
-            size="sm"
-            className="h-7 px-2"
-            onClick={handleAddKeyword}
-            disabled={!kwInput.trim()}
-          >
-            <Plus className="size-3" />
-          </Button>
-        </div>
-
-        {/* 已添加关键词 Tag 列表 */}
-        {extraKeywords.length > 0 && (
-          <div className="flex flex-wrap gap-1">
-            {extraKeywords.map((kw) => (
-              <span
-                key={kw}
-                className="inline-flex items-center gap-1 rounded-full bg-primary/10 text-primary px-2 py-0.5 text-xs"
-              >
-                {kw}
-                <button
-                  type="button"
-                  onClick={() => onRemoveKeyword(kw)}
-                  className="hover:text-destructive leading-none"
-                >
-                  ×
-                </button>
-              </span>
-            ))}
-          </div>
-        )}
+        <label className="text-xs text-muted-foreground">
+          补充检索（可选）— 写下你想检索的内容，然后点"重新搜索"或"技能检索"
+        </label>
+        <textarea
+          ref={textareaRef}
+          rows={1}
+          value={userQuery}
+          onChange={handleInput}
+          onKeyDown={handleKeyDown}
+          placeholder={placeholder ?? '例如：想查看各大平台销量 / 2025 年财报 / 行业头部公司近期动态…'}
+          disabled={disabled}
+          className="w-full resize-none rounded-md border border-input bg-background px-2.5 py-1.5 text-xs leading-5 placeholder:text-muted-foreground focus-visible:outline-none focus-visible:ring-1 focus-visible:ring-ring disabled:opacity-50 min-h-[28px] max-h-24"
+        />
       </div>
     </div>
   );

frontend-web/src/open-canvas/components/ai-writing/SkillStepsCard.tsx

@@ -0,0 +1,105 @@
+import { useState } from 'react';
+import { ChevronRight, Sparkles, ListChecks, Zap, Loader2 } from 'lucide-react';
+import { cn } from '@/lib/utils';
+import type { SkillSearchStep } from '../../types/ai-writing';
+import { CollapseTransition } from './CollapseTransition';
+
+interface SkillStepsCardProps {
+  steps: SkillSearchStep[];
+  /** 是否仍在进行中（researching 状态下显示 spinner，让用户看到流式进展） */
+  inProgress?: boolean;
+}
+
+const STEP_ICON: Record<SkillSearchStep['type'], typeof Sparkles> = {
+  list_skills: ListChecks,
+  select_skills: Sparkles,
+  invoke_skill: Zap,
+};
+
+const STEP_LABEL: Record<SkillSearchStep['type'], string> = {
+  list_skills: '列出可用技能',
+  select_skills: '筛选相关技能',
+  invoke_skill: '调用技能',
+};
+
+export function SkillStepsCard({ steps, inProgress }: SkillStepsCardProps) {
+  const [expanded, setExpanded] = useState(true);
+  if (steps.length === 0 && !inProgress) return null;
+
+  return (
+    <div className="rounded-md border border-violet-200 bg-violet-50/40 dark:border-violet-900/40 dark:bg-violet-950/20 overflow-hidden">
+      <button
+        type="button"
+        onClick={() => setExpanded((v) => !v)}
+        className="w-full flex items-center gap-2 px-3 py-2 text-xs font-medium hover:bg-violet-100/50 dark:hover:bg-violet-900/30 transition-colors text-left"
+      >
+        {inProgress
+          ? <Loader2 className="size-3.5 text-violet-500 shrink-0 animate-spin" />
+          : <Sparkles className="size-3.5 text-violet-500 shrink-0" />}
+        <span className="flex-1">
+          技能检索过程
+          <span className="ml-1 text-muted-foreground font-normal">
+            （共 {steps.length} 步{inProgress ? '，进行中…' : ''}）
+          </span>
+        </span>
+        <ChevronRight
+          className={cn(
+            'size-3 text-muted-foreground transition-transform duration-200',
+            expanded && 'rotate-90',
+          )}
+        />
+      </button>
+
+      <CollapseTransition open={expanded}>
+        <ol className="px-3 pb-2.5 pt-1 space-y-1.5 border-t border-violet-200/60 dark:border-violet-900/30">
+          {steps.map((step, idx) => {
+            const Icon = STEP_ICON[step.type] ?? Sparkles;
+            const label = STEP_LABEL[step.type] ?? step.type;
+            return (
+              <li key={idx} className="flex items-start gap-2 text-[11px]">
+                <span className="shrink-0 mt-0.5 inline-flex items-center justify-center size-4 rounded-full text-[10px] font-medium bg-violet-100 dark:bg-violet-900/60 text-violet-600 dark:text-violet-300">
+                  {idx + 1}
+                </span>
+                <div className="flex-1 min-w-0">
+                  <div className="flex items-center gap-1 font-medium text-violet-700 dark:text-violet-300">
+                    <Icon className="size-3 shrink-0" />
+                    <span>{label}</span>
+                    {step.skillName && (
+                      <span className="font-mono text-violet-900 dark:text-violet-100">
+                        · {step.skillName}
+                      </span>
+                    )}
+                  </div>
+                  <div className="text-muted-foreground mt-0.5">{step.message}</div>
+                  {step.skillNames && step.skillNames.length > 0 && (
+                    <div className="mt-1 flex flex-wrap gap-1">
+                      {step.skillNames.map((name) => (
+                        <span
+                          key={name}
+                          className="inline-flex items-center px-1.5 py-0.5 rounded text-[10px] font-mono bg-violet-100 dark:bg-violet-900/60 text-violet-700 dark:text-violet-200"
+                        >
+                          {name}
+                        </span>
+                      ))}
+                    </div>
+                  )}
+                  {step.reason && (
+                    <div className="mt-0.5 text-[10px] text-violet-600/80 dark:text-violet-400/80 italic">
+                      原因：{step.reason}
+                    </div>
+                  )}
+                </div>
+              </li>
+            );
+          })}
+          {inProgress && (
+            <li className="flex items-center gap-2 text-[11px] text-muted-foreground italic">
+              <Loader2 className="size-3 animate-spin" />
+              更多步骤生成中…
+            </li>
+          )}
+        </ol>
+      </CollapseTransition>
+    </div>
+  );
+}

frontend-web/src/open-canvas/hooks/useAIWritingStream.ts

@@ -41,6 +41,7 @@ import type {
   ProgressEventType,
   ReviewIssue,
   ReviewResult,
+  SkillSearchStep,
   StreamingReviewItem,
   UserInterventionPayload,
   WritingStatus,
@@ -71,6 +72,7 @@ const INITIAL_STATE: AIWritingState = {
   intentThinkingText: '',
   parsedIntent: null,
   researchProgress: '',
+  skillSearchSteps: [],
   streamingReviewItems: [],
   revisionSummary: null,
   pendingRevisionContext: null,
@@ -105,7 +107,7 @@ function reducer(prev: AIWritingState, action: Action): AIWritingState {
         ...prev,
         currentPause: null,
         status: ns,
-        ...(ns === 'researching' ? { researchProgress: '' } : {}),
+        ...(ns === 'researching' ? { researchProgress: '', skillSearchSteps: [] } : {}),
         ...(ns === 'writing_outline' ? { outlineStreamingText: '', outlineThinkingText: '' } : {}),
         ...(ns === 'writing_draft' ? { streamingDraftSections: [], streamingDraftTitle: '' } : {}),
         ...(ns === 'reviewing' ? { streamingReviewItems: [] } : {}),
@@ -191,12 +193,22 @@ function handleEvent(prev: AIWritingState, event: ProgressEvent): AIWritingState
     case 'resumed':
       return { ...base, currentPause: null };
 
-    case 'materials_ready':
+    case 'skill_search_step': {
+      const step = event.skillStep;
+      if (!step) return base;
+      return { ...base, skillSearchSteps: [...prev.skillSearchSteps, step] };
+    }
+
+    case 'materials_ready': {
+      // 后端把 pkg.skill_search_steps 一并塞回来时，覆盖前端累积（保证刷新页面回放也对）
+      const incomingSteps = (event as unknown as { skillSearchSteps?: SkillSearchStep[] }).skillSearchSteps;
       return {
         ...base,
         materials: (event.materials ?? []) as AIMaterial[],
         researchProgress: '',
+        ...(incomingSteps ? { skillSearchSteps: incomingSteps } : {}),
       };
+    }
 
     case 'outline_chunk': {
       const text = (event as unknown as { text: string }).text ?? '';
@@ -337,6 +349,7 @@ function handleEvent(prev: AIWritingState, event: ProgressEvent): AIWritingState
 // ── snake_case ↔ camelCase 归一化（custom 通道事件 + interrupt payload） ──────
 
 function normalizeMaterial(m: Record<string, unknown>): AIMaterial {
+  const extra = (m.extra_metadata ?? m.extraMetadata) as Record<string, unknown> | undefined;
   return {
     id: String(m.id ?? ''),
     title: String(m.title ?? ''),
@@ -344,9 +357,21 @@ function normalizeMaterial(m: Record<string, unknown>): AIMaterial {
     source: String(m.source ?? ''),
     publishedAt: String(m.published_at ?? m.publishedAt ?? ''),
     relevanceScore: Number(m.relevance_score ?? m.relevanceScore ?? 0),
-    sourceType: (m.source_type ?? m.sourceType ?? 'internet') as 'internet' | 'intranet',
+    sourceType: (m.source_type ?? m.sourceType ?? 'internet') as AIMaterial['sourceType'],
     url: m.url as string | undefined,
     recUuid: (m.recUuid ?? m.rec_uuid) as string | undefined,
+    extraMetadata: extra,
+  };
+}
+
+function normalizeSkillStep(s: Record<string, unknown>): SkillSearchStep {
+  return {
+    type: (s.type as SkillSearchStep['type']) ?? 'invoke_skill',
+    message: String(s.message ?? ''),
+    skillNames: (s.skill_names ?? s.skillNames) as string[] | undefined,
+    skillName: (s.skill_name ?? s.skillName) as string | undefined,
+    reason: s.reason as string | undefined,
+    matchedCount: (s.matched_count ?? s.matchedCount) as number | undefined,
   };
 }
 
@@ -445,6 +470,7 @@ function customToProgressEvent(raw: unknown, sessionId: string): ProgressEvent |
     'intent_chunk', 'intent_ready',
     'research_progress', 'outline_chunk', 'draft_chunk',
     'review_chunk', 'review_item_done',
+    'skill_search_step',
   ];
   if (!allowed.includes(type as ProgressEventType)) return null;
 
@@ -459,6 +485,10 @@ function customToProgressEvent(raw: unknown, sessionId: string): ProgressEvent |
   if (Array.isArray(merged.issues)) {
     merged.reviewItemIssues = (merged.issues as Record<string, unknown>[]).map(normalizeReviewIssue);
   }
+  // skill_search_step：把字段折成 skillStep 子对象，方便 reducer / UI 取用
+  if (type === 'skill_search_step') {
+    merged.skillStep = normalizeSkillStep(o);
+  }
   return merged as unknown as ProgressEvent;
 }
 
@@ -478,6 +508,9 @@ function nodeUpdatesToEvents(nodeOutput: unknown, sessionId: string): ProgressEv
   // ``material_package`` 出现 → materials_ready（节点 progress_events 里不带）
   if (out.material_package && typeof out.material_package === 'object') {
     const pkg = out.material_package as Record<string, unknown>;
+    const skillSteps = Array.isArray(pkg.skill_search_steps ?? pkg.skillSearchSteps)
+      ? ((pkg.skill_search_steps ?? pkg.skillSearchSteps) as Record<string, unknown>[]).map(normalizeSkillStep)
+      : undefined;
     events.push({
       type: 'materials_ready',
       sessionId,
@@ -485,7 +518,8 @@ function nodeUpdatesToEvents(nodeOutput: unknown, sessionId: string): ProgressEv
       materials: Array.isArray(pkg.materials) ? (pkg.materials as Record<string, unknown>[]).map(normalizeMaterial) : [],
       keywords: (pkg.keywords ?? []) as string[],
       materialSummary: (pkg.summary as string) ?? '',
-    });
+      ...(skillSteps ? { skillSearchSteps: skillSteps } as unknown as Partial<ProgressEvent> : {}),
+    } as ProgressEvent);
   }
 
   // ``current_outline`` 出现且 progress_events 里没 outline_ready → 合成一条

frontend-web/src/open-canvas/types/ai-writing.ts

@@ -7,9 +7,24 @@ export interface AIMaterial {
   source: string;
   publishedAt: string;
   relevanceScore: number;
-  sourceType: 'internet' | 'intranet';
+  sourceType: 'internet' | 'intranet' | 'skill';
   url?: string;
   recUuid?: string;
+  // skill 类素材的元信息（skill_name / container_path / category / skill_full_content 等）
+  extraMetadata?: Record<string, unknown>;
+}
+
+// 技能检索过程的单步记录（前端时间线展示"使用了 X 技能"）
+//   list_skills：列出全部 enabled 技能
+//   select_skills：LLM 按相关度排序的候选
+//   invoke_skill：实际按顺序调用某个技能
+export interface SkillSearchStep {
+  type: 'list_skills' | 'select_skills' | 'invoke_skill';
+  message: string;
+  skillNames?: string[];
+  skillName?: string;
+  reason?: string;
+  matchedCount?: number;
 }
 
 // ── 大纲 ─────────────────────────────────────────────────────────────────────
@@ -139,6 +154,7 @@ export type ProgressEventType =
   | 'await_user'
   | 'resumed'
   | 'notice'
+  | 'skill_search_step'
   | 'done'
   | 'error';
 
@@ -173,6 +189,8 @@ export interface ProgressEvent {
   pauseContext?: Record<string, unknown>;
   // section_help：素材不足、待用户决策的章节
   blockedSections?: BlockedSection[];
+  // skill_search_step：技能检索步骤事件（list_skills / select_skills / invoke_skill）
+  skillStep?: SkillSearchStep;
 }
 
 // ── 用户干预提交体 ────────────────────────────────────────────────────────────
@@ -180,7 +198,10 @@ export interface ProgressEvent {
 export interface UserInterventionPayload {
   action: string;
   approvedMaterialIds?: string[];
+  /** @deprecated 旧版多关键词追加。新版统一用 userQuery 单输入框 */
   extraKeywords?: string[];
+  /** PAUSE-1 素材确认：用户单输入框写的自然语言（技能名/来源/检索意图都行）。re_search / enable_skill_search 共用。 */
+  userQuery?: string;
   editedOutline?: AIOutline;
   outlineFeedback?: string;
   userRevisionNotes?: string;
@@ -291,6 +312,8 @@ export interface AIWritingState {
   parsedIntent: ParsedIntent | null;
   // 素材收集实时进度（最新一条提示文案）
   researchProgress: string;
+  // 技能检索步骤（按发生顺序累积，pause_material 卡片里渲染时间线）
+  skillSearchSteps: SkillSearchStep[];
   // 流式审核（逐条到达）
   streamingReviewItems: StreamingReviewItem[];
   // 修改摘要

frontend-web/src/roundtable-planning/components/RecommendAgentsDialog.tsx

@@ -36,7 +36,9 @@ import {
   type RecommendCandidate,
   type RecommendStreamPhase,
 } from "../api/recommend";
+import { useAutoScroll } from "../hooks/useAutoScroll";
 import { splitInlineReasoning } from "../lib/reasoning";
+import { ScrollToBottomButton } from "./ScrollToBottomButton";
 
 /**
  * Picks-selection dialog that sits between Step 1 (intent) and Step 2
@@ -453,6 +455,7 @@ export function RecommendAgentsDialog({
             state.phase === "loading_agents" || state.phase === "recommending"
           }
           phase={state.phase}
+          scrollDeps={[state.rationale, state.steps, state.streamPhase]}
         >
           <RecommenderOutput state={state} />
         </CollapsibleModelOutput>
@@ -593,16 +596,22 @@ const MODEL_OUTPUT_AUTO_CLOSE_DELAY_MS = 1000;
 function CollapsibleModelOutput({
   isLoading,
   phase,
+  scrollDeps,
   children,
 }: {
   /** True 时面板保持展开 + header 显示 spinner;涵盖加载候选 + 流式生成。 */
   isLoading: boolean;
   phase: DialogPhase;
+  /** 内容变化时触发自动滚到底(与 Step1/Step2 对话区同一套 useAutoScroll)。 */
+  scrollDeps: React.DependencyList;
   children: React.ReactNode;
 }) {
   const [open, setOpen] = useState<boolean>(true);
   const userTouchedRef = useRef<boolean>(false);
   const hasAutoClosedRef = useRef<boolean>(false);
+  const modelOutputScrollRef = useRef<HTMLDivElement>(null);
+  const { atBottom: modelOutputAtBottom, scrollToBottom: scrollModelOutputToBottom } =
+    useAutoScroll(modelOutputScrollRef, scrollDeps);
 
   // 加载中 → 保持展开(用户没手动动过的前提下)。
   // 加载完成 → 延迟自动收起一次(仅一次),让出焦点给下方推荐卡片。
@@ -677,8 +686,16 @@ function CollapsibleModelOutput({
         />
       </button>
       {open && (
-        <div className="px-3 pb-3 min-h-0 flex-1 overflow-y-auto custom-scrollbar">
-          {children}
+        <div className="relative min-h-0 flex-1 flex flex-col">
+          <div
+            ref={modelOutputScrollRef}
+            className="px-3 pb-3 min-h-0 flex-1 overflow-y-auto custom-scrollbar"
+          >
+            {children}
+          </div>
+          {!modelOutputAtBottom && (
+            <ScrollToBottomButton onClick={scrollModelOutputToBottom} />
+          )}
         </div>
       )}
     </section>
@@ -751,7 +768,10 @@ function RecommenderOutput({ state }: { state: InternalState }) {
       {hasReasoning && (
         <ReasoningBlock
           streaming={isStreaming}
-          contentClassName="max-h-48 overflow-y-auto custom-scrollbar"
+          contentClassName={cn(
+            "overflow-y-auto custom-scrollbar",
+            isStreaming ? "max-h-none" : "max-h-48",
+          )}
         >
           {reasoning!}
         </ReasoningBlock>
@@ -762,7 +782,12 @@ function RecommenderOutput({ state }: { state: InternalState }) {
       )}
 
       {hasRationale && (
-        <div className="max-h-40 overflow-y-auto custom-scrollbar rounded-md border border-slate-200 bg-white px-3 py-2.5 text-sm text-slate-700 leading-relaxed">
+        <div
+          className={cn(
+            "overflow-y-auto custom-scrollbar rounded-md border border-slate-200 bg-white px-3 py-2.5 text-sm text-slate-700 leading-relaxed",
+            isStreaming ? "max-h-none" : "max-h-40",
+          )}
+        >
           <MarkdownContent>{cleanedRationale}</MarkdownContent>
           {isStreaming && <StreamingCursor />}
         </div>

offline-backend-20260512/backend/config.yaml

@@ -23,6 +23,19 @@ models:
     supports_vision: true
     supports_thinking: true
 
+  - name: deepseek-chat
+    display_name: DeepSeek Chat
+    use: langchain_openai:ChatOpenAI
+    model: deepseek-chat
+    api_key: sk-1520028668cb4cc388ed8315ff1e856e
+    base_url: https://api.deepseek.com
+    request_timeout: 600.0
+    max_retries: 2
+    max_tokens: 4096
+    temperature: 1.0
+    supports_vision: true
+    supports_thinking: true
+
   - name: deepseek-v4-flash
     display_name: DeepSeek V4 Flash
     use: langchain_openai:ChatOpenAI
@@ -86,6 +99,11 @@ tools:
     use: deerflow.community.ddg_search.tools:web_search_tool
     max_results: 5
 
+  - name: web_fetch
+    group: web
+    use: deerflow.community.jina_ai.tools:web_fetch_tool
+    timeout: 15
+
   - name: ls
     group: file:read
     use: deerflow.sandbox.tools:ls_tool
@@ -121,7 +139,7 @@ sandbox:
   allow_host_bash: true
 
 skills:
-  path: D:\cursor-work\offline-backend-20260512\backend\skills
+  path: skills
   security_scan:
     enabled: false
 

offline-backend-20260512/backend/extensions_config.json

@@ -0,0 +1,11 @@
+{
+  "mcpServers": {},
+  "skills": {
+    "web-research": { "enabled": true },
+    "deep-search": { "enabled": true },
+    "code-retrieval": { "enabled": true },
+    "news-briefing": { "enabled": true },
+    "workspace-search": { "enabled": true },
+    "policy-knowledge": { "enabled": true }
+  }
+}

offline-backend-20260512/backend/packages/harness/deerflow/agents/ai_writing/graph.py

@@ -55,6 +55,9 @@ async def pause_material_confirm(state: AIWritingState) -> dict:
 
     action = user_input.get("action", "confirm")
 
+    # 单输入框文本：可能是技能名 / 来源 / 检索意图，re_search 和 enable_skill_search 都用得到
+    user_query = (user_input.get("userQuery") or user_input.get("user_query") or "").strip()
+
     if action == "confirm":
         approved_ids = set(user_input.get("approvedMaterialIds") or [m["id"] for m in pkg["materials"]])
         filtered = [m for m in pkg["materials"] if m["id"] in approved_ids]
@@ -66,12 +69,22 @@ async def pause_material_confirm(state: AIWritingState) -> dict:
             "progress_events": [{"type": "resumed", "agent_name": "系统", "message": "用户已确认素材，开始规划大纲"}],
         }
 
-    # re_search：重新搜索
+    # enable_skill_search：用户选择"启用技能检索"，回到 researcher 走 skill 模式
+    if action == "enable_skill_search":
+        msg = f"已启用技能检索（输入：{user_query[:30]}）" if user_query else "已启用技能检索，正在筛选可用技能…"
+        return {
+            "last_user_intervention": {**user_input, "action": "enable_skill_search", "user_query": user_query},
+            "status": "researching",
+            "progress_events": [{"type": "resumed", "agent_name": "系统", "message": msg}],
+        }
+
+    # re_search：重新搜索（支持新版 user_query 单输入框 + 旧版 extraKeywords 数组）
     extra_kws = user_input.get("extraKeywords") or []
+    msg = f"按输入「{user_query[:30]}」重新搜索…" if user_query else "重新搜索中..."
     return {
-        "last_user_intervention": {**user_input, "_extra_keywords": extra_kws},
+        "last_user_intervention": {**user_input, "_extra_keywords": extra_kws, "user_query": user_query},
         "status": "researching",
-        "progress_events": [{"type": "resumed", "agent_name": "系统", "message": "重新搜索中..."}],
+        "progress_events": [{"type": "resumed", "agent_name": "系统", "message": msg}],
     }
 
 

offline-backend-20260512/backend/packages/harness/deerflow/agents/ai_writing/nodes/researcher.py

@@ -9,7 +9,7 @@ from typing import List
 
 from langchain_core.runnables import RunnableConfig
 
-from ..search import get_search_provider, SearchResult
+from ..search import get_search_provider, SearchResult, SkillSearchProvider
 from ..state import AIWritingState, Material, MaterialPackage
 from ..prompts.researcher_prompts import (
     EXTRACT_KEYWORDS_SYSTEM, EXTRACT_KEYWORDS_USER,
@@ -96,15 +96,24 @@ async def researcher_node(state: AIWritingState, config: RunnableConfig) -> dict
     # 检查干预模式（PAUSE-1 素材确认 / 素材不足求助）
     intervention = state.get("last_user_intervention") or {}
     extra_keywords: list[str] = intervention.get("_extra_keywords") or intervention.get("extra_keywords") or []
+    # PAUSE-1 单输入框：用户写的自然语言（技能名 / 来源 / 检索意图），优先级最高
+    user_query: str = (intervention.get("user_query") or "").strip()
     action = intervention.get("action")
 
     # 素材不足求助点触发的「补充检索」：保留原大纲，检索完直接回写作、不走素材确认/大纲
     is_supplement = action == "supplement_search"
-    # PAUSE-1 素材确认卡用户点「追加检索」并填了新关键词：
+    # PAUSE-1 素材确认卡用户点「按输入重新搜索」并填了 user_query：
     #   - 跳过 LLM 重新生成检索词（节省一次调用 + 尊重用户意图）
-    #   - 只检索 extra_keywords 这几个新词，不重检索之前 LLM 出过的词
+    #   - 直接用 user_query 作为唯一检索词
     #   - 保留 existing material_package，按 URL 去重合并
-    is_append_only = action == "re_search" and bool(extra_keywords)
+    is_user_query_search = action == "re_search" and bool(user_query)
+    # 兼容旧版"追加关键词"调用方（如果还有 client 传 extra_keywords 数组而非 user_query）
+    is_append_only = action == "re_search" and not user_query and bool(extra_keywords)
+    # PAUSE-1 素材确认卡用户点「启用技能检索」：
+    #   - 不再走 web/intranet 检索，改用 SkillSearchProvider
+    #   - 顺序调用候选技能 + 早停（第一个技能够就停，不够再加下一个）
+    #   - 旧 material_package 完全丢弃（覆盖式替换，让用户对比 web vs skill 结果）
+    is_skill_search = action == "enable_skill_search"
 
     # 用户指定的检索关键词数量（1~10），决定生成多少个检索词、检索多少个方向
     keyword_count = _resolve_keyword_count(state.get("keyword_count"))
@@ -126,10 +135,14 @@ async def researcher_node(state: AIWritingState, config: RunnableConfig) -> dict
         writer({"type": "research_progress", "message": message})
 
     # Step 1: 提取关键词
-    kw_result: dict = {}  # 走追加分支时跳过 LLM 调用，但下方 notice 拼接需要兜底值
-    if is_append_only:
-        # 追加模式：直接用用户填的关键词，不再调 LLM
-        keywords: list[str] = _clean_keywords(extra_keywords, intent)
+    kw_result: dict = {}  # 走"用户输入 / 追加关键词"分支时跳过 LLM 调用，notice 拼接需要兜底值
+    if is_user_query_search:
+        # 用户输入分支：把整段自然语言作为唯一检索词，尊重原意，不再做关键词拆分
+        keywords: list[str] = [user_query]
+        _emit(f"按你的输入「{user_query[:30]}」检索…")
+    elif is_append_only:
+        # 兼容旧版追加模式：直接用用户填的关键词，不再调 LLM
+        keywords = _clean_keywords(extra_keywords, intent)
         _emit(f"追加检索 {len(keywords)} 个关键词…")
     else:
         _emit("正在生成检索词…")
@@ -150,13 +163,31 @@ async def researcher_node(state: AIWritingState, config: RunnableConfig) -> dict
         if extra_keywords:
             keywords = list(dict.fromkeys(keywords + extra_keywords))
 
-    # Step 2: 并发搜索
-    provider = get_search_provider(ai_writing_config)
+    # Step 2: 搜索
+    # 技能检索：用 SkillSearchProvider 替代 web/intranet；步骤事件单独走 skill_search_step 通道
+    skill_steps: list[dict] = []
+
+    if is_skill_search:
+        def _emit_skill_step(step: dict) -> None:
+            skill_steps.append(step)
+            writer({"type": "skill_search_step", "agent_name": "素材收集专家", **step})
+
+        async def _llm_select(system: str, user_prompt: str, fallback: dict) -> dict:
+            return await llm_json(system, user_prompt, fallback=fallback, config=config, model_name=keyword_model)
+
+        provider = SkillSearchProvider(
+            llm_select=_llm_select,
+            emit_step=_emit_skill_step,
+            max_select=max(1, min(int(max_materials), 10)),
+            user_query=user_query,
+        )
+    else:
+        provider = get_search_provider(ai_writing_config)
 
     # 按用户指定的关键词数量截断。
-    # 追加模式：keywords 本身就是用户填的，全部检索不截断（用户填 N 个就搜 N 个）。
+    # 用户输入 / 追加模式：keywords 本身就是用户填的，全部检索不截断。
     # 其他模式：受 keyword_count 限制，但 extra_keywords 在内时上限放宽到 keywords 总数。
-    if is_append_only:
+    if is_user_query_search or is_append_only:
         search_keywords = keywords
     else:
         search_limit = keyword_count
@@ -168,31 +199,48 @@ async def researcher_node(state: AIWritingState, config: RunnableConfig) -> dict
     per_keyword = _per_keyword_limit(max_materials, total)
     _emit(f"检索词已生成，开始检索 {total} 个方向…")
 
-    # 并发搜索，但每完成一个就推送进度（计数在单线程 asyncio 下无需加锁）
-    completed = 0
+    # 技能模式：串行调用 provider（早停语义靠 provider 内部累积计数）
+    # 其它模式：并发调用，每完成一个就推送进度
+    if is_skill_search:
+        all_results_nested: list[list[SearchResult]] = []
+        for kw in search_keywords:
+            try:
+                res = await provider.search(kw, max_results=per_keyword, user_intent=intent)
+            except Exception as e:
+                logger.warning("skill search failed: %s", e)
+                all_results_nested.append(e)  # type: ignore[arg-type]
+                continue
+            all_results_nested.append(res)
+            # provider 内部 early_stop_at 已触发时不会再返回新 skill，提前 break 避免空轮询
+            if not res:
+                break
+    else:
+        completed = 0
 
-    async def _search_one(kw: str) -> list[SearchResult]:
-        nonlocal completed
-        try:
-            return await provider.search(kw, max_results=per_keyword)
-        finally:
-            completed += 1
-            if completed < total:
-                _emit(f"已完成 {completed}/{total} 次检索，正在继续检索相关内容…")
-            else:
-                _emit(f"已完成全部 {total} 次检索")
+        async def _search_one(kw: str) -> list[SearchResult]:
+            nonlocal completed
+            try:
+                return await provider.search(kw, max_results=per_keyword)
+            finally:
+                completed += 1
+                if completed < total:
+                    _emit(f"已完成 {completed}/{total} 次检索，正在继续检索相关内容…")
+                else:
+                    _emit(f"已完成全部 {total} 次检索")
 
-    search_tasks = [_search_one(kw) for kw in search_keywords]
-    all_results_nested: list[list[SearchResult]] = await asyncio.gather(*search_tasks, return_exceptions=True)
+        search_tasks = [_search_one(kw) for kw in search_keywords]
+        all_results_nested = await asyncio.gather(*search_tasks, return_exceptions=True)
 
     # 合并去重
     # - 首次检索 / 普通 re_search（不带 extra_keywords，用户只想 LLM 重出）：旧素材丢弃
     # - 素材不足求助 supplement_search：保留旧素材 + 追加新检索结果
     # - PAUSE-1 追加检索 is_append_only：保留旧素材 + 仅检索新关键词
+    # - 技能检索 is_skill_search：覆盖式替换，旧素材完全丢弃（用户期望对比 web vs skill 结果）
     seen_urls: set[str] = set()
+    seen_skill_ids: set[str] = set()  # skill 素材无 URL，按 skill_name 去重
     raw_materials: list[Material] = []
     existing_pkg = state.get("material_package")
-    preserve_existing = existing_pkg and (is_supplement or is_append_only)
+    preserve_existing = existing_pkg and (is_supplement or is_append_only) and not is_skill_search
     if preserve_existing:
         for m in existing_pkg.get("materials", []):
             seen_urls.add(m.get("url", ""))
@@ -205,10 +253,19 @@ async def researcher_node(state: AIWritingState, config: RunnableConfig) -> dict
             search_errors.append(f"{type(results).__name__}: {results}")
             continue
         for r in results:
-            if r.url and r.url in seen_urls:
+            # skill 素材按 skill_name 去重（同一个 skill 被多个关键词命中只保留一次）
+            if r.source_type == "skill":
+                meta = getattr(r, "extra_metadata", {}) or {}
+                sk_name = meta.get("skill_name", "")
+                if sk_name and sk_name in seen_skill_ids:
+                    continue
+                if sk_name:
+                    seen_skill_ids.add(sk_name)
+            elif r.url and r.url in seen_urls:
                 continue
-            seen_urls.add(r.url)
-            raw_materials.append(Material(
+            else:
+                seen_urls.add(r.url)
+            mat: Material = Material(
                 id=f"m{len(raw_materials)+1:03d}",
                 title=r.title,
                 content=r.content[:500],
@@ -218,7 +275,11 @@ async def researcher_node(state: AIWritingState, config: RunnableConfig) -> dict
                 source_type=r.source_type,
                 url=r.url,
                 recUuid=r.recUuid,
-            ))
+            )
+            extra = getattr(r, "extra_metadata", None)
+            if extra:
+                mat["extra_metadata"] = extra
+            raw_materials.append(mat)
 
     # provider 内部吞掉的检索异常（如内网 ES 连接失败），一并取出用于提示用户
     search_errors.extend(getattr(provider, "errors", []))
@@ -264,6 +325,14 @@ async def researcher_node(state: AIWritingState, config: RunnableConfig) -> dict
         old_kws = list(existing_pkg.get("keywords") or [])
         pkg_keywords = list(dict.fromkeys(old_kws + keywords))
     pkg = MaterialPackage(keywords=pkg_keywords, materials=materials, summary=summary)
+    # 技能检索时把过程步骤一并放进 pkg，前端在素材确认卡里能展示"使用了哪些技能"
+    if is_skill_search:
+        pkg["skill_search_used"] = True
+        pkg["skill_search_steps"] = skill_steps
+    elif existing_pkg and existing_pkg.get("skill_search_used") and (is_supplement or is_append_only):
+        # 保留之前一次技能检索的痕迹（不污染纯 web 检索）
+        pkg["skill_search_used"] = existing_pkg.get("skill_search_used", False)
+        pkg["skill_search_steps"] = existing_pkg.get("skill_search_steps", [])
 
     # 容错告警：检索接口 / 模型调用出错时以非致命 notice 提示用户，不打断写作流程
     notices: list[dict] = []
@@ -281,12 +350,15 @@ async def researcher_node(state: AIWritingState, config: RunnableConfig) -> dict
             raw="\n\n----------\n\n".join(raw_dumps[:3]),
         ))
 
-    # 进度事件文案：追加模式下让用户看到只搜了哪几个新词
-    step_start_msg = (
-        f"追加检索关键词：{', '.join(keywords[:3])}"
-        if is_append_only
-        else f"搜索关键词：{', '.join(keywords[:3])}"
-    )
+    # 进度事件文案：用户输入 / 追加模式 / 技能模式下让用户看到差异化提示
+    if is_skill_search:
+        step_start_msg = f"启用技能检索（{len(skill_steps)} 步）"
+    elif is_user_query_search:
+        step_start_msg = f"按你的输入检索：{user_query[:40]}"
+    elif is_append_only:
+        step_start_msg = f"追加检索关键词：{', '.join(keywords[:3])}"
+    else:
+        step_start_msg = f"搜索关键词：{', '.join(keywords[:3])}"
     return {
         "material_package": pkg,
         # 补充检索：直接回写作（沿用原大纲）；常规检索：进入素材确认暂停点

offline-backend-20260512/backend/packages/harness/deerflow/agents/ai_writing/search/__init__.py

@@ -3,6 +3,7 @@ from .internet_search import InternetSearchProvider
 from .intranet_stub import IntranetSearchProvider
 from .demo_search import DemoSearchProvider
 from .duckduckgo_search import DuckDuckGoSearchProvider
+from .skill_search import SkillSearchProvider
 
 
 def get_search_provider(ai_writing_config: dict) -> BaseSearchProvider:
@@ -60,5 +61,6 @@ __all__ = [
     "BaseSearchProvider", "SearchResult",
     "InternetSearchProvider", "IntranetSearchProvider",
     "DemoSearchProvider", "DuckDuckGoSearchProvider",
+    "SkillSearchProvider",
     "get_search_provider",
 ]

offline-backend-20260512/backend/packages/harness/deerflow/agents/ai_writing/search/skill_search.py

@@ -0,0 +1,248 @@
+"""技能检索 Provider：把已启用的 Skill 当作可检索的素材源。
+
+流程（保持简单，对应素材确认卡上的"技能检索"按钮）：
+1) list_skills 事件 —— 列出当前启用的全部 skill
+2) select_skills 事件 —— LLM 根据用户输入 + 写作意图按相关度选出若干个
+3) invoke_skill 事件 —— 按相关度从高到低顺序产出 SearchResult
+
+输出格式严格对齐 BaseSearchProvider 的 SearchResult，让 researcher 节点
+不需要分支处理，下游 Material 字段同构。
+"""
+from __future__ import annotations
+
+import logging
+import re
+from typing import Callable, List, Optional
+
+from .base import BaseSearchProvider, SearchResult
+
+logger = logging.getLogger(__name__)
+
+
+_SELECT_SKILLS_SYSTEM = """你是一名情报研究员，需要从可用「技能」中挑出对写作任务有帮助的若干个，并按相关度从高到低排序。
+技能是一段封装好的指令 / 知识 / 工作流，每个技能有 name 和 description。
+
+【严禁思考】
+- 这是一个简单的匹配任务，禁止任何思考、分析、推理过程，禁止输出 <think></think> 标签。
+- 收到输入后立即直接输出最终 JSON，不得有任何前置文字。
+
+【输出要求】
+- 只输出一个 JSON 对象，不要 markdown 代码块。
+- 必须使用英文双引号。
+- selected_skills 中的 name 必须严格来自下方"可用技能"列表，不要编造，按相关度从高到低排序。
+- 如果用户输入里明确点名了某个技能（按 name 完全匹配），把它排在第一位。
+
+【完整示例】
+{"selected_skills": ["web-search", "knowledge-lookup"], "reason": "用户想检索互联网信息，web-search 最相关，知识库查询作为补充"}"""
+
+_SELECT_SKILLS_USER = """写作意图：{user_intent}
+用户补充输入：{user_query}
+检索关键词：{keywords}
+
+可用技能（共 {skill_count} 个）：
+{skill_list}
+
+请从中按相关度从高到低选出最多 {max_select} 个技能。如果没有合适的技能，selected_skills 返回空数组。
+只输出 JSON：
+{{"selected_skills": ["name1", "name2"], "reason": "为什么选这些 + 排序依据"}}
+
+/no_think"""
+
+
+EmitStepFn = Callable[[dict], None]
+
+
+def _summarize_skill_content(content: str, limit: int = 500) -> str:
+    """从 SKILL.md 提取摘要：跳过 frontmatter，取正文开头 limit 字。"""
+    if not content:
+        return ""
+    body = content
+    m = re.match(r"^---\s*\n(.*?\n)---\s*\n(.*)$", content, flags=re.DOTALL)
+    if m:
+        body = m.group(2)
+    body = re.sub(r"^#\s+.*?\n", "", body.lstrip(), count=1)
+    body = body.strip()
+    if len(body) > limit:
+        return body[:limit].rstrip() + "…"
+    return body
+
+
+class SkillSearchProvider(BaseSearchProvider):
+    """从启用的 Skills 中筛选并返回作为素材。
+
+    构造参数：
+      llm_select: 异步 LLM 调用 (system, user, fallback) -> dict。
+      emit_step:  可选；推送时间线步骤事件（list_skills / select_skills / invoke_skill）。
+      max_select: LLM 单次最多挑几个技能。
+      user_query: 用户在素材确认卡输入框写的自然语言（可能包含技能名 / 来源 / 补充意图）。
+    """
+
+    def __init__(
+        self,
+        llm_select: Callable,
+        *,
+        emit_step: Optional[EmitStepFn] = None,
+        max_select: int = 5,
+        user_query: str = "",
+    ) -> None:
+        self._llm_select = llm_select
+        self._emit_step = emit_step or (lambda _step: None)
+        self._max_select = max_select
+        self._user_query = (user_query or "").strip()
+        self._errors: list[str] = []
+        # 单次 researcher 调用内复用结果，避免每个 keyword 都问一次 LLM
+        self._selected_cache: list[dict] | None = None
+        self._enabled_skills: list | None = None
+        # 跨 keyword 调用时同一个 skill 只暴露一次
+        self._yielded_skills: set[str] = set()
+
+    @property
+    def errors(self) -> list[str]:
+        return list(self._errors)
+
+    def _load_enabled_skills(self) -> list:
+        if self._enabled_skills is not None:
+            return self._enabled_skills
+        try:
+            from deerflow.skills import get_or_new_skill_storage
+            storage = get_or_new_skill_storage()
+            skills = storage.load_skills(enabled_only=True)
+        except Exception as e:
+            logger.exception("ai_writing.skill_search: 加载启用技能失败")
+            self._errors.append(f"skill list error: {e}")
+            skills = []
+        self._enabled_skills = skills
+        self._emit_step({
+            "type": "list_skills",
+            "message": f"发现 {len(skills)} 个可用技能",
+            "skill_names": [s.name for s in skills],
+        })
+        return skills
+
+    async def _select_skills(self, query: str, user_intent: str) -> list[dict]:
+        """让 LLM 从启用的技能中按相关度排序选出若干个。同一次检索复用结果。"""
+        if self._selected_cache is not None:
+            return self._selected_cache
+
+        skills = self._load_enabled_skills()
+        if not skills:
+            self._selected_cache = []
+            return []
+
+        skill_list_text = "\n".join(
+            f"- {s.name}: {s.description or '(无描述)'}" for s in skills
+        )
+        try:
+            result = await self._llm_select(
+                _SELECT_SKILLS_SYSTEM,
+                _SELECT_SKILLS_USER.format(
+                    user_intent=user_intent or query,
+                    user_query=self._user_query or "(无)",
+                    keywords=query,
+                    skill_count=len(skills),
+                    skill_list=skill_list_text,
+                    max_select=self._max_select,
+                ),
+                fallback={"selected_skills": [s.name for s in skills[: self._max_select]]},
+            )
+        except Exception as e:
+            logger.exception("ai_writing.skill_search: LLM 选择技能失败")
+            self._errors.append(f"skill select error: {e}")
+            result = {"selected_skills": [s.name for s in skills[: self._max_select]]}
+
+        wanted_names = result.get("selected_skills") or []
+        if not isinstance(wanted_names, list):
+            wanted_names = []
+        by_name = {s.name: s for s in skills}
+        chosen: list[dict] = []
+        for name in wanted_names:
+            if not isinstance(name, str):
+                continue
+            sk = by_name.get(name.strip())
+            if sk:
+                chosen.append({"skill": sk, "reason": result.get("reason", "")})
+            if len(chosen) >= self._max_select:
+                break
+
+        self._emit_step({
+            "type": "select_skills",
+            "message": f"按相关度排序，候选 {len(chosen)} 个技能（将按顺序调用）",
+            "skill_names": [c["skill"].name for c in chosen],
+            "reason": result.get("reason", ""),
+        })
+        self._selected_cache = chosen
+        return chosen
+
+    @staticmethod
+    def _read_skill_content(skill) -> str:
+        try:
+            return skill.skill_file.read_text(encoding="utf-8")
+        except Exception as e:
+            logger.warning("ai_writing.skill_search: 读 SKILL.md 失败 %s: %s", skill.name, e)
+            return skill.description or ""
+
+    def _to_search_result(self, skill, reason: str) -> SearchResult:
+        raw = self._read_skill_content(skill)
+        summary = _summarize_skill_content(raw, limit=500)
+        category_value = skill.category.value if hasattr(skill.category, "value") else str(skill.category)
+        return SearchResult(
+            title=skill.name,
+            content=summary or (skill.description or skill.name),
+            source=f"技能库 / {category_value}",
+            published_at="",
+            url="",
+            relevance_score=1.0,
+            source_type="skill",
+            recUuid="",
+            extra_metadata={
+                "skill_name": skill.name,
+                "skill_description": skill.description or "",
+                "skill_path": skill.skill_path,
+                "container_path": skill.get_container_file_path(),
+                "category": category_value,
+                "select_reason": reason,
+                # 完整 SKILL.md 内容，供 writer_draft 节点按需注入到 prompt
+                "skill_full_content": raw,
+            },
+        )
+
+    async def search(
+        self,
+        query: str,
+        max_results: int = 5,
+        date_from: str = "",
+        date_to: str = "",
+        user_intent: str = "",
+    ) -> List[SearchResult]:
+        """按相关度顺序产出候选 skills 对应的 SearchResult。
+
+        说明：每个 skill 直接产出一条 SearchResult。researcher 节点上游会按
+        skill_name 去重，所以同一个 SkillSearchProvider 多次调用本方法时不会
+        产出重复 skill 素材（_yielded_skills 兜底）。
+        """
+        chosen = await self._select_skills(query, user_intent=user_intent)
+        if not chosen:
+            return []
+
+        results: List[SearchResult] = []
+        for entry in chosen:
+            sk = entry["skill"]
+            if sk.name in self._yielded_skills:
+                continue
+            self._emit_step({
+                "type": "invoke_skill",
+                "message": f"调用技能：{sk.name}",
+                "skill_name": sk.name,
+                "matched_count": len(self._yielded_skills) + 1,
+            })
+            results.append(self._to_search_result(sk, entry.get("reason", "")))
+            self._yielded_skills.add(sk.name)
+            if len(results) >= max_results:
+                break
+        return results
+
+    async def health_check(self) -> bool:
+        try:
+            return bool(self._load_enabled_skills())
+        except Exception:
+            return False

offline-backend-20260512/backend/packages/harness/deerflow/agents/ai_writing/state.py

@@ -3,21 +3,43 @@ import operator
 
 # ── 素材 ──────────────────────────────────────────────────────────────────────
 
-class Material(TypedDict):
+class Material(TypedDict, total=False):
     id: str
     title: str
     content: str           # 截断到 500 字
     source: str
     published_at: str
     relevance_score: float
-    source_type: str       # "internet" | "intranet"
+    source_type: str       # "internet" | "intranet" | "skill"
     url: str
     recUuid: str
+    # skill 类素材附带的元信息（skill_name / container_path / category），其他类型为空
+    extra_metadata: dict
 
-class MaterialPackage(TypedDict):
+class SkillStep(TypedDict, total=False):
+    """技能检索过程的单步记录，用于前端时间线展示。
+
+    type=match_skills：根据用户输入流式分析有没有匹配技能（无 skill_names）
+    type=list_skills：列出可用技能
+    type=select_skills：LLM 从中选出的相关技能
+    type=invoke_skill：实际调用某一个技能检索
+    type=stop_early：达到素材阈值，提前停止后续技能调用
+    """
+    type: str
+    message: str
+    skill_names: List[str]
+    skill_name: str
+    matched_count: int
+    reason: str
+
+class MaterialPackage(TypedDict, total=False):
     keywords: List[str]
     materials: List[Material]
     summary: str
+    # 是否本次素材来自技能检索（覆盖式替换 web 检索）
+    skill_search_used: bool
+    # 技能检索的步骤记录（前端展示"使用了 X 技能"卡片）
+    skill_search_steps: List[SkillStep]
 
 # ── 大纲 ──────────────────────────────────────────────────────────────────────
 # 三级结构:章节(##) → 小节(###) → 子要点(bullet -)。
@@ -72,10 +94,13 @@ class ReviewResult(TypedDict):
 
 # ── 用户干预 ──────────────────────────────────────────────────────────────────
 
-class UserInterventionPayload(TypedDict):
+class UserInterventionPayload(TypedDict, total=False):
     action: str
     approved_material_ids: List[str]
     extra_keywords: List[str]
+    # PAUSE-1 素材确认 / enable_skill_search 共用：用户在单输入框里填的自然语言
+    # （可能是要使用的技能名、想检索的来源、或者一段补充检索意图）。
+    user_query: str
     edited_outline: Optional[Outline]
     outline_feedback: str
     user_revision_notes: str