Pi-style ack-and-steer sub-agent protocol: dispatch mid-turn, steer via server wake turn

The job tools (research/demo/visual) switch from client-side turn-breaking
calls to pi's model: execute resolves IMMEDIATELY with a fire-and-forget
ack, the teacher's turn continues, and the result arrives later as an
injected user-role steer message that wakes the teacher in a new
server-side turn.

- contracts.ts: THE ASYNC PROTOCOL rewritten (ack now, steer later); steer
  types (SubagentSteerMessage, metadata.subagentResult + data-subagent-
  artifact part), pure buildSubagentSteer/steerDelivered/isSubagentFailure
- tools/jobs.ts: jobTools(ctx) factory — server-side execute creates the
  job (deduped by toolCallId), fires spawn with the dispatch-time input
  (the part isn't persisted yet at execute — a transcript scan would race)
- runner.ts: runJob(jobId, input?) builds the steer and hands it to the
  injected deliver seam; pipeline owns the done/error flip (a polling
  client re-syncs once, at the end); failures still steer
- server/jobs.ts (new pipeline): per-chat serialized queues on globalThis,
  idle gates (turn liveness + pending question, 1.5s grace), 409 retry
  with backoff, idempotent per jobId, stale-job recovery sweep (re-deliver
  or re-spawn); wake turns run through the same handleChatRequest
  composition via setTurnRunner injection
- chat-handler.ts: wires runner+deliver+tools ctx; drops spawnTurnJobs
  from onFinish; teacher default registry = question tools only
- plan.ts: PlanToolContext split out (plan tools need no job wiring)
- visual-maker: edit_svg added (pi parity — exact-match single
  replacement, fuzzy context on a miss); researcher: pi's kept/dropped
  source accounting restored
- prompts 20-jobs/40-demos: async discipline rewritten (announce and keep
  teaching, no waiting/polling/fabricating, parallel dispatch, teach with
  the artifact when it arrives)
- tests: jobs.test.ts rewritten (dispatch ack mid-turn, runner steers,
  wake pipeline: deferral/409/idempotency/failure), demos.test.tsx runner
  tests ported to runJob + fake deliver; 222 green

FLAGGED surgical touches outside the stream's owned files, for master
review at merge: src/core/contracts.ts (protocol doc + steer types),
src/core/ui-message.ts (job tool + data-part types), src/server/
chat-handler.ts (wiring), src/server/turn-service.ts (spawnTurnJobs
retirement), src/agent/teacher-agent.ts (default tools), src/agent/tools/
plan.ts (context type split).

Verified live on PORT=3003 with real models: teacher dispatched research
mid-turn, researcher ran real searches/fetches, steer injected on quiz
answer, wake turn wove the brief in citing its sources, job flipped done;
a client/wake race correctly 409'd.

src/core/ui-message.ts

@@ -1,18 +1,29 @@
 import type { UIMessage } from "ai";
+import type { DemoToolInput, ResearchToolInput, SubagentArtifactData, VisualToolInput } from "./contracts.ts";
 import type { AskToolInput, QuestionAnswerData, QuizToolInput } from "./question-core.ts";
 
 /**
  * The typed UI message for the teacher chat — gives the frontend typed tool
- * parts ("tool-quiz" / "tool-ask_user_question" with typed input/output)
- * without importing the server-side agent into the client bundle.
+ * parts ("tool-quiz" / "tool-ask_user_question" / "tool-research" / …) without
+ * importing the server-side agent into the client bundle.
  *
- * Declared explicitly (not via InferUITools) because a client-side tool has
- * no execute function, so its OUTPUT type lives only here: the structured
- * answer record the client builds and sends via addToolOutput.
+ * Question tools are CLIENT-SIDE (no execute): their OUTPUT type is the
+ * structured answer record the client builds and sends via addToolOutput.
+ * Job tools are SERVER-EXECUTED: their output is the plain-string dispatch
+ * acknowledgement (the result later arrives as a steer message — see
+ * SubagentSteerMessage in contracts.ts, whose artifact rides the
+ * data-subagent-artifact part typed here as DATA_PARTS).
  */
 export type TeacherUITools = {
 	quiz: { input: QuizToolInput; output: QuestionAnswerData };
 	ask_user_question: { input: AskToolInput; output: QuestionAnswerData };
+	research: { input: ResearchToolInput; output: string };
+	demo: { input: DemoToolInput; output: string };
+	visual: { input: VisualToolInput; output: string };
 };
 
-export type TeacherUIMessage = UIMessage<unknown, never, TeacherUITools>;
+export type TeacherUIDataParts = {
+	"subagent-artifact": SubagentArtifactData;
+};
+
+export type TeacherUIMessage = UIMessage<unknown, TeacherUIDataParts, TeacherUITools>;