W2: async job infra + researcher sub-agent

- src/store/jobs.ts: per-job JSON store in data/jobs (create/get/update/list,
  dedup by toolCallId)
- src/agent/tools/jobs.ts: research tool — client-side (no execute), turn ends
  at the call; input per contracts ResearchToolInput
- src/agent/tools/web.ts: server-side web_search (Google CSE) + web_fetch
  (Readability/Turndown/linkedom, Jina fallback) — errors return as strings,
  never thrown into the agent loop. Deps: @mozilla/readability, linkedom,
  turndown (+@types/turndown dev)
- src/agent/subagents/researcher.ts: isolated ToolLoopAgent (web tools only,
  12-step cap), researcher prompt ported from pi
- src/agent/subagents/runner.ts: spawnPendingJobs hook + runResearchJob —
  fire-and-forget, activity line per tool call, fulfills the part in the
  LATEST chat record (output-available) before flipping job status; failure
  still fulfills the part so the teacher learns the outcome
- src/server/chat-handler.ts: onFinish spawn hook after saveMessages
- app/api/jobs/route.ts: GET ?chatId= polling endpoint
- components/artifacts/job-card.tsx + registry entry: polling activity card
  (2s) → syncFromServer on finish; research-brief card (markdown + sources)
- src/agent/prompts/20-jobs.md: research doctrine for the teacher
- tests/jobs.test.ts: store CRUD, spawn hook via scripted mock teacher,
  runner completion/failure with fake model + stubbed fetch

src/agent/subagents/researcher.ts

@@ -0,0 +1,71 @@
+import { ToolLoopAgent, stepCountIs, type LanguageModel } from "ai";
+import { openrouter } from "@openrouter/ai-sdk-provider";
+import { webTools } from "../tools/web.ts";
+
+/**
+ * The researcher sub-agent (vision §2.5): a SEPARATE ToolLoopAgent instance
+ * from the teacher — an isolated loop with only web_search + web_fetch, so
+ * raw search/fetch churn never touches the teacher's context window.
+ *
+ * System prompt adapted from the pi researcher agent
+ * (~/.pi/agent/extensions/interactive-subagents/agents/researcher.md).
+ * The model is injectable so tests run the loop with a MockLanguageModelV4.
+ */
+
+const DEFAULT_RESEARCHER_MODEL =
+	process.env.LH_RESEARCH_MODEL ?? process.env.LH_MODEL ?? "anthropic/claude-sonnet-4.5";
+
+const INSTRUCTIONS = `You are a research specialist. You work for a teacher agent inside a learning
+application: given a research question, conduct thorough web research and produce a focused,
+well-sourced brief that the teacher can teach from.
+
+You operate in an isolated context with no knowledge of the lesson or any prior conversation.
+All necessary context is in the task description.
+
+Process:
+1. Break the question into 2-4 searchable facets.
+2. Search with web_search using varied angles:
+   - the direct answer query (the obvious one)
+   - an authoritative-source query (official docs, specs, primary sources)
+   - a practical-experience query (case studies, benchmarks, real-world usage)
+   - a recent-developments query (only if the topic is time-sensitive)
+3. Read the results. Identify what's well-covered and what has gaps. If the first round
+   doesn't fully answer the question, search again with refined queries targeting the gaps.
+4. For the 2-3 most promising source URLs, use web_fetch to get the full page content.
+5. Synthesize everything into a brief that directly answers the question.
+
+Evaluation — what to keep vs drop:
+- Official docs and primary sources outweigh blog posts and forum threads.
+- Recent sources outweigh stale ones.
+- Sources that directly address the question outweigh tangentially related ones.
+- Drop SEO filler, outdated info, and beginner tutorials (unless that's the audience).
+
+Tool outputs may be error strings (e.g. search unconfigured, a page that failed to fetch).
+Adapt: try another URL or another search angle; if research is genuinely impossible, say so
+in the brief instead of inventing facts.
+
+Your FINAL assistant message is your entire deliverable — it must stand alone, using this format:
+
+## Summary
+2-3 sentence direct answer.
+
+## Findings
+Numbered findings with inline source citations:
+1. **Finding** — explanation. [Source](url)
+
+## Sources
+- Source Title (url) — why it's relevant
+
+## Gaps
+What couldn't be answered. Suggested next steps.`;
+
+export function createResearcherAgent(model?: LanguageModel) {
+	return new ToolLoopAgent({
+		model: model ?? openrouter(DEFAULT_RESEARCHER_MODEL),
+		instructions: INSTRUCTIONS,
+		tools: webTools,
+		stopWhen: stepCountIs(12),
+	});
+}
+
+export type ResearcherAgent = ReturnType<typeof createResearcherAgent>;