Files
learnharness/src/agent/tools/probe.ts
T
amosblomqvist b87a6925af Wave A: pi-native tool layer — delete LhTool/toPiTool, TypeBox everywhere, terminate on questions
- src/agent/lh-tool.ts deleted: the zod-wrapped LhTool + toPiTool bridge
  (z.toJSONSchema per call, clientQuestion flag, hand-rolled result mapping)
  is gone. Tools are pi-agent-core native AgentTools now.
- New src/agent/tool-execute.ts owns what the wrapper added: the abort guard
  (runWithAbortGuard: run signal + 30s per-call timeout + 250ms grace,
  'Operation aborted' / timeout wording preserved), ToolInputError (the
  retryable '- problem at path' format), result mapping (string verbatim /
  object JSON / image parts, details rides the record's tool part output),
  and questionResult() — placeholder + terminate:true (owner Option A:
  belt of terminate + slim makeQuestionStopper with the clean-question
  rule; maxTurns deleted from the teaching turn entirely per owner).
- All 11 tool files + tools.ts registries converted to TypeBox parameters
  (typebox@1.3.7, pinned to pi-agent-core's copy). zod refinements
  (quizInputProblems, askOptionProblems, live-nodeId) moved from schemas
  into execute — the model sees the same retryable error shape.
- question-core + contracts/probe TypeBox-authored (single source shared
  with the UI); tool-parts parse seam runs the boundary's full chain
  (Convert → Check → Clean → refinement), fixing the live-smoke lockout:
  pi's boundary Value.Converts correctAnswer: 17 → '17' but the record
  keeps raw args, so a parse without Convert rejected a posed quiz
  (invisible pending question, turn ended). Pinned with the real smoke
  emission shape.
- Subagents converted: demo-builder/researcher AgentTool-native,
  visual-maker/pdf-reader declaration-only pi-ai Tools with local execute
  fns, extraction submit schemas re-authored in TypeBox (owner option 2:
  zod defaults → Type.Optional + fill at the submit seam).
- Accepted delta, flagged: TypeBox-native schemas skip pi's JSON-Schema
  primitive coercion fast path... (boundary still Value.Converts), and
  prober-quiz unknown keys ride through (Value.Clean strips at display).
- Tests: 988 passing (was 967 at the recon baseline); tool-abort and
  read-tool rewritten against the native seams; question-core/question-
  tools/tool-parts/demos/web-search/graph-tools/plan-tree/probe-done/
  tool-toggles converted to Value.Check/execute pins.

Live smoke (PORT=3004, real model): native ls turn streams end-to-end; a
real quiz pose (first attempt missing correctAnswer → tool-input-error →
model retry → posed) terminates the turn cleanly and persists pending.
2026-09-25 23:32:13 +03:00

91 lines
4.3 KiB
TypeScript

import type { AgentTool } from "@earendil-works/pi-agent-core";
import { serverExecute } from "../tool-execute.ts";
import { probeDoneInputSchema, type ProbeDoneResult } from "../../core/contracts.ts";
import type { UIMessage } from "ai";
import { findPendingToolCall } from "../../core/pending.ts";
import type { ChatStore } from "../../core/ports.ts";
import { buildProbeHandoffSteer, type ProbeHandoffSteerMessage } from "../../core/contracts.ts";
/** What the probe_done tool closes over. */
export interface ProbeDoneContext {
chatId: string;
/** The storage port (open-question + already-concluded checks). */
chatStore: ChatStore;
/** Queue the handoff steer (the wake pipeline — src/server/jobs.ts).
* Injected so this module never imports the server seam. */
deliver: (steer: ProbeHandoffSteerMessage) => void;
}
/** Does the transcript already carry a concluded probe (any state)? */
function probeConcluded(messages: UIMessage[]): boolean {
for (const m of messages) {
if (m.parts.some((p) => p.type === "tool-probe_done")) return true;
}
return false;
}
/**
* probe_done — the probe→planning seam (docs/probe-teach-split.md §2).
*
* SERVER-SIDE. The prober concludes the probe by authoring the learner
* assessment (the tool INPUT — it streams to the learner live and is
* durable in the transcript as the tool part itself). Three outcomes:
*
* ok:false + error — a question is still open ("resolve it first"), or
* the probe is already concluded. The refusal returns to the prober as
* a tool result; it fixes course and retries (the return-to-agent
* doctrine, same as nodeId validation).
* ok:true — the assessment is recorded, and the HANDOFF is queued: a
* steer through the wake pipeline that fires the teacher's first turn
* (plan authoring) the moment the prober's turn ends. Auto-wake is the
* user-decided trigger — the learner experiences assessment → plan as
* one continuous flow.
*
* The first probe_done in the transcript is also the construction seam:
* from that message on, every request builds the TEACHER agent.
*/
export function probeDoneTool(ctx: ProbeDoneContext): Record<string, AgentTool<any>> {
return {
probe_done: {
name: "probe_done",
label: "probe_done",
description:
"Conclude the probing phase and hand off to the teaching phase. Call this ONCE, when the probe is " +
"complete: every strand the lesson depends on is bracketed (a floor he reliably gets right AND a " +
"ceiling where it runs out), and his learning goal is concrete. The input IS the learner assessment — " +
"one strand per dependency the lesson will rest on, with your read of where his edge sits on it " +
"(floor, ceiling, misconceptions, what to build from). It streams to the learner live and becomes " +
"the handoff artifact the teacher plans from. Refused while a question is still open, and after " +
"the probe is already concluded. After it succeeds, say your closing sentence and end your turn.",
// The core-owned schema (contracts/probe.ts) — the SAME schema the UI
// parse seam (tool-parts.ts) runs, so boundary-valid ⇔ consumer-parseable.
parameters: probeDoneInputSchema,
execute: serverExecute("probe_done", probeDoneInputSchema, async (input): Promise<ProbeDoneResult> => {
const record = ctx.chatStore.getChat(ctx.chatId);
if (!record) return { ok: false, error: `Chat not found: ${ctx.chatId}` };
if (findPendingToolCall(record.messages) !== null) {
return {
ok: false,
error:
"A question is still open — resolve it (or let him answer) before concluding the probe. " +
"probe_done only fires with no question outstanding.",
};
}
if (probeConcluded(record.messages)) {
return { ok: false, error: "The probe is already concluded — probe_done fires exactly once." };
}
try {
ctx.deliver(buildProbeHandoffSteer(ctx.chatId));
} catch (err) {
console.error(`[chat ${ctx.chatId}] probe handoff queueing failed:`, err);
// The handoff is recoverable-by-design (the next client message
// constructs the teacher off the transcript seam) — record the
// assessment anyway; the wake is an optimization, not a gate.
}
return { ok: true, assessment: input.assessment };
}),
},
};
}