feat(suggest): 新增 fetchSuggestionContext 聚合函数 + 类型定义

- 4 路并行拉取智能上下文：用户画像、痛点、经验、技能匹配
- 500ms 超时保护 + 静默降级（失败不阻断建议生成）
- Tauri 不可用时直接返回空上下文

desktop/src/lib/suggestion-context.ts

@@ -0,0 +1,131 @@
+/**
+ * Suggestion context enrichment — fetches intelligence data for personalized suggestions.
+ * All fetches are optional; failures silently degrade to empty context.
+ */
+
+import { invoke } from '@tauri-apps/api/core';
+import { createLogger } from './logger';
+
+const log = createLogger('SuggestionContext');
+
+const CONTEXT_FETCH_TIMEOUT = 500;
+
+/** Pain point from butler intelligence layer. */
+interface PainPoint {
+  summary: string;
+  category: string;
+  confidence: number;
+  status: string;
+  occurrence_count: number;
+}
+
+/** Brief experience from the experience store. */
+interface ExperienceBrief {
+  pain_pattern: string;
+  solution_summary: string;
+  reuse_count: number;
+}
+
+/** Pipeline/skill match candidate. */
+interface PipelineCandidateInfo {
+  id: string;
+  display_name: string;
+  description: string;
+  category: string | null;
+  match_reason: string | null;
+}
+
+/** Route intent response (only NoMatch variant has suggestions). */
+interface RouteResultResponse {
+  type: 'Matched' | 'Ambiguous' | 'NoMatch' | 'NeedMoreInfo';
+  suggestions?: PipelineCandidateInfo[];
+}
+
+/** Aggregated suggestion context from all intelligence sources. */
+export interface SuggestionContext {
+  userProfile: string;
+  painPoints: string;
+  experiences: string;
+  skillMatch: string;
+}
+
+function isTauriAvailable(): boolean {
+  return typeof window !== 'undefined' && '__TAURI_INTERNALS__' in window;
+}
+
+function withTimeout<T>(promise: Promise<T>, ms: number): Promise<T | null> {
+  return Promise.race([
+    promise,
+    new Promise<null>(resolve => setTimeout(() => resolve(null), ms)),
+  ]);
+}
+
+async function fetchUserProfile(agentId: string): Promise<string> {
+  const profile = await invoke<string>('identity_get_file', {
+    agentId,
+    file: 'userprofile',
+  });
+  if (!profile || profile.trim().length === 0) return '';
+  const text = profile.trim();
+  return text.length > 200 ? text.slice(0, 200) : text;
+}
+
+async function fetchPainPoints(agentId: string): Promise<string> {
+  const points = await invoke<PainPoint[]>('butler_list_pain_points', { agentId });
+  if (!Array.isArray(points) || points.length === 0) return '';
+
+  const active = points
+    .filter(p => p.confidence >= 0.5 && p.status !== 'Solved' && p.status !== 'Dismissed')
+    .sort((a, b) => b.confidence - a.confidence)
+    .slice(0, 3);
+
+  if (active.length === 0) return '';
+  return active
+    .map((p, i) => `${i + 1}. [${p.category}] ${p.summary}（出现${p.occurrence_count}次）`)
+    .join('\n');
+}
+
+async function fetchExperiences(agentId: string, query: string): Promise<string> {
+  const experiences = await invoke<ExperienceBrief[]>('experience_find_relevant', {
+    agentId,
+    query,
+  });
+  if (!Array.isArray(experiences) || experiences.length === 0) return '';
+
+  return experiences.slice(0, 2)
+    .map(e => `上次解决"${e.pain_pattern}"的方法：${e.solution_summary}（已复用${e.reuse_count}次）`)
+    .join('\n');
+}
+
+async function fetchSkillMatch(userInput: string): Promise<string> {
+  const result = await invoke<RouteResultResponse>('route_intent', { userInput });
+  const suggestions = result?.suggestions;
+  if (!Array.isArray(suggestions) || suggestions.length === 0) return '';
+
+  const best = suggestions[0];
+  return `你可能需要：${best.display_name} — ${best.description}`;
+}
+
+const EMPTY_CONTEXT: SuggestionContext = { userProfile: '', painPoints: '', experiences: '', skillMatch: '' };
+
+/**
+ * Fetch all intelligence context in parallel for suggestion enrichment.
+ * Returns empty strings for any source that fails — never throws.
+ */
+export async function fetchSuggestionContext(
+  agentId: string,
+  lastUserMessage: string,
+): Promise<SuggestionContext> {
+  if (!isTauriAvailable()) {
+    return EMPTY_CONTEXT;
+  }
+
+  const [userProfile, painPoints, experiences, skillMatch] = await Promise.all([
+    withTimeout(fetchUserProfile(agentId).catch(e => { log.warn('User profile fetch failed:', e); return ''; }), CONTEXT_FETCH_TIMEOUT),
+    withTimeout(fetchPainPoints(agentId).catch(e => { log.warn('Pain points fetch failed:', e); return ''; }), CONTEXT_FETCH_TIMEOUT),
+    withTimeout(fetchExperiences(agentId, lastUserMessage).catch(e => { log.warn('Experiences fetch failed:', e); return ''; }), CONTEXT_FETCH_TIMEOUT),
+    withTimeout(fetchSkillMatch(lastUserMessage).catch(e => { log.warn('Skill match fetch failed:', e); return ''; }), CONTEXT_FETCH_TIMEOUT),
+  ]);
+
+  return { userProfile: userProfile ?? '', painPoints: painPoints ?? '', experiences: experiences ?? '', skillMatch: skillMatch ?? '' };
+}