fix: deliver Claude teaching prose through an output tool

src/agent/subagents/extraction.ts

@@ -28,7 +28,7 @@ import type { GraphStore } from "../../core/ports.ts";
 import { emit } from "../../core/events.ts";
 import { settleGraphLayout } from "../../core/layout-settle.ts";
 import { batchRuns, coverageOf, messageViewLines } from "../../core/coverage.ts";
-import type { LhMessage } from "../../core/native-messages.ts";
+import { failedOutputCallIds, type LhMessage } from "../../core/native-messages.ts";
 import { auditorGraphTools } from "../tools/graph.ts";
 import { runSubmitAgent, healStringifiedArrays } from "./submit-agent.ts";
 
@@ -124,16 +124,20 @@ export function transcriptView(record: ChatRecord): string {
 }
 
 /** The extraction view under the teacher-prose ruling (owner, 2026-09-28):
- *  ONLY the teacher agent's text blocks — no learner messages, no
+ *  ONLY learner-facing teacher prose (text or send_to_user) — no learner
- *  thinking, no tool calls or results, no quiz blocks — each labeled with
+ *  messages, thinking, other tool calls/results, or quiz blocks — labeled with
  *  its ACTUAL message id (owner, 2026-10-13): the view lines ARE
  *  core/coverage.ts messageViewLines ("TEACHER [id] text"), the exact
  *  lines the coverage fingerprints hash, so the extractor can anchor
  *  every proposition to the passage it came from (the session submit's
  *  required messageId). The shared markdown engine stays reserved for the
  *  future user-facing export. */
-function proseView(messages: ReadonlyArray<LhMessage>, title?: string): string {
+function proseView(
-	const lines = messages.flatMap((message) => messageViewLines(message, message.id));
+	messages: ReadonlyArray<LhMessage>,
+	title?: string,
+	failedOutputCalls: ReadonlySet<string> = failedOutputCallIds(messages),
+): string {
+	const lines = messages.flatMap((message) => messageViewLines(message, message.id, failedOutputCalls));
 	const head = title && title.length > 0 ? `# ${title}\n\n` : "";
 	return head + lines.join("\n\n");
 }
@@ -1113,6 +1117,7 @@ export function createExtractionPipeline(deps: ExtractionPipelineDeps): Extracti
 			// stage runs (typed — the trigger skips, routes surface 503).
 			refuseIfStagesUnready();
 			const covered = coverageOf(record.messages, graphStore.readCoverage(), chatId);
+			const failedOutputCalls = failedOutputCallIds(record.messages);
 			if (covered.uncovered.length === 0) {
 				console.info(`[extraction ${chatId}] nothing uncovered — no-op`);
 				return { nodes: 0, chains: 0 };
@@ -1148,14 +1153,14 @@ export function createExtractionPipeline(deps: ExtractionPipelineDeps): Extracti
 							// fingerprints' messageViewLines ("TEACHER [id] text"), one
 							// shared seam.
 							const messages = batch.map((slot) => slot.message);
-							const view = proseView(messages, record.title);
+							const view = proseView(messages, record.title, failedOutputCalls);
 							// The batch's teacher-prose ids — the ONLY anchors this
 							// job's submit may name (validateSessionAnchors at the
 							// submit seam refuses anything else: ids from other
 							// batches — even real ones of this chat — other chats,
 							// and non-prose messages).
 							const batchIds = new Set(
-								messages.filter((m) => messageViewLines(m, m.id).length > 0).map((m) => m.id),
+								messages.filter((m) => messageViewLines(m, m.id, failedOutputCalls).length > 0).map((m) => m.id),
 							);
 							setPhase(jobKey, "queued", "chat", undefined, part);
 							const findings = await withExtractSlot(jobKey, async () => {
@@ -1188,7 +1193,7 @@ export function createExtractionPipeline(deps: ExtractionPipelineDeps): Extracti
 								const batchStats = mergeFindings(chatId, findings, auditResult, { chatStore, graphStore }, {
 									foldedAt,
 									coverage: batch
-										.filter((slot) => messageViewLines(slot.message, slot.message.id).length > 0)
+										.filter((slot) => slot.tokens > 0)
 										.map((slot) => ({ chatId, fp: slot.fp, tokens: slot.tokens, foldedAt })),
 								});
 								// The layout ledger evolves with the merge (sync — the

src/agent/teacher-agent.ts

@@ -15,10 +15,11 @@ import {
 	type TeacherToolContext,
 } from "./tools.ts";
 import { practiceTools, type PracticeToolContext } from "./tools/practice.ts";
-import { healToolRecord } from "./tools/heal.ts";
+import { healToolRecord, withArgumentHeal } from "./tools/heal.ts";
+import { sendToUserTool } from "./tools/send-to-user.ts";
 import { quizInputObject, quizInputProblems } from "../core/question-core.ts";
 import { QUESTION_TOOLS, type EnabledTools } from "../core/pending.ts";
-import { toLlmMessages, nativeInputCause } from "../core/native-messages.ts";
+import { toLlmMessages, nativeInputCause, PRACTICE_PROBLEM_TOOL } from "../core/native-messages.ts";
 import type { ChatGPTRequestCycle } from "./chatgpt-request-cycle.ts";
 import { usageWasAdmitted } from "./subscription-request-cycle.ts";
 
@@ -145,22 +146,27 @@ export interface AgentBuildOptions {
  * belt-and-suspenders HALF for the mixed batch (a question + other calls
  * in one message) that terminate-only semantics would let run on — the
  * learner cannot answer while a turn is in flight (per-chat 409), so a
- * cleanly-posed question MUST always end the turn. maxTurns is gone
+ * cleanly-posed question MUST always end the turn. Practice's problem pose
+ * has the same wait-for-the-learner contract, including mixed output/problem
+ * batches; failed poses must still retry. maxTurns is gone
  * (owner ruling 2026-09-25: no maximum-agent-turns net on the teaching
  * turn).
  */
-function makeQuestionStopper() {
+function makeQuestionStopper(kind: AgentKind) {
 	return (context: {
 		message: { content: Array<{ type: string; id?: string; name?: string }> };
 		toolResults: Array<{ toolCallId: string; isError?: boolean }>;
 	}): boolean => {
 		const called = new Set(
 			context.message.content
-				.filter((c) => c.type === "toolCall" && c.name !== undefined && (QUESTION_TOOLS as readonly string[]).includes(c.name!))
+				.filter((c) => c.type === "toolCall" && c.name !== undefined && (
+					(QUESTION_TOOLS as readonly string[]).includes(c.name) ||
+					(kind === "practice" && c.name === PRACTICE_PROBLEM_TOOL)
+				))
 				.map((c) => c.id!),
 		);
 		if (called.size === 0) return false;
-		// Stop only when every question call of this turn resolved cleanly.
+		// Stop only when every question/problem pose resolved cleanly.
 		for (const result of context.toolResults) {
 			if (called.has(result.toolCallId) && result.isError) return false;
 		}
@@ -174,7 +180,7 @@ function baseAgentOptions(kind: AgentKind, opts: AgentBuildOptions, tools: Agent
 	// conversation-spec resolution as teaching); the cast keeps AgentKind
 	// ("practice" is not a ModelRole) honest about that.
 	const engine = opts.engine ?? piEngineFor(kind as "prober" | "teacher");
-	const stopper = makeQuestionStopper();
+	const stopper = makeQuestionStopper(kind);
 	const systemPrompt = opts.promptSwitches
 		? composeInstructions(kind, opts.promptSwitches)
 		: composedInstructions[kind]!;
@@ -190,7 +196,16 @@ function baseAgentOptions(kind: AgentKind, opts: AgentBuildOptions, tools: Agent
 			systemPrompt,
 			model: engine.model,
 			thinkingLevel: engine.level,
-			tools,
+			// Conditional registry inclusion, like the graph-tool gates: when
+			// closed, neither the tool nor its usage instructions reach the model.
+			// Match Claude across providers (including OpenRouter), not the API
+			// transport. Explicit test registries remain caller-owned.
+			tools: [
+				...tools,
+				...(opts.tools === undefined && engine.model.id.toLowerCase().includes("claude")
+					? [withArgumentHeal(sendToUserTool)]
+					: []),
+			],
 			messages: opts.messages ?? [],
 		},
 		streamFn: engine.streamFn,
@@ -312,10 +327,9 @@ export function bareQuestionTools(): Record<string, AgentTool<any>> {
  * from turn 1 of a kind:"practice" session — no prober→teacher split,
  * no plan tools, no question tools. Its ENTIRE registry is
  * problem + conclude (tools/practice.ts); the doctrine prompt
- * (prompts/practice/) carries the method. The question-stop rule does
+ * (prompts/practice/) carries the method. A successful problem pose ends
- * not apply (problem rides terminate: true natively —
+ * the run, natively for a problem-only batch and via the shared stop hook
- * QUESTION_TOOLS does not include it), so baseAgentOptions's stopper is
+ * for a mixed batch (for example, send_to_user + problem).
- * a no-op here; it stays wired for uniformity.
  */
 export function createPracticeAgent(ctx: PracticeToolContext, opts: AgentBuildOptions = {}) {
 	const tools = opts.tools ?? practiceTools(ctx);

src/agent/tools/send-to-user.ts

@@ -0,0 +1,36 @@
+import { Type } from "typebox";
+import type { AgentTool } from "@earendil-works/pi-agent-core";
+import { SEND_TO_USER_TOOL } from "../../core/native-messages.ts";
+import { serverExecute } from "../tool-execute.ts";
+
+const sendToUserInput = Type.Object({
+	message: Type.String({
+		minLength: 1,
+		pattern: "\\S",
+		description: "The complete content to display to the learner. Markdown and LaTeX are supported.",
+	}),
+});
+
+/** Claude's documented verbatim mid-turn output channel. Availability is
+ * model-gated at the shared conversation-agent construction boundary;
+ * the native call remains in history, and the view renders its message. */
+export const sendToUserTool: AgentTool<typeof sendToUserInput> = {
+	name: SEND_TO_USER_TOOL,
+	label: SEND_TO_USER_TOOL,
+	description:
+		"## REQUIRED OUTPUT CHANNEL — ALWAYS USE `send_to_user`\n\n" +
+		"**ALL learner-facing messages MUST be sent using `send_to_user`.** This includes explanations, teaching, " +
+		"feedback, corrections, hints, introductions, progress messages, and final responses. " +
+		"There is no exception for short messages or the end of a turn.\n\n" +
+		"Ordinary response text may be converted into summarized thinking instead of reaching the learner. " +
+		"**Never rely on ordinary response text to communicate with the learner. Thinking is not delivery.**\n\n" +
+		"Put the complete message in `message`. Markdown and LaTeX are supported. " +
+		"Do not duplicate it in ordinary response text.\n\n" +
+		"Question content still belongs in the appropriate question tool; send any accompanying teaching or " +
+		"commentary through `send_to_user` before calling that tool.\n\n" +
+		"This tool does not pause or end your turn. Continue with other tools when needed. " +
+		"After delivering your final message, end the turn without additional ordinary response text.",
+	parameters: sendToUserInput,
+	executionMode: "sequential",
+	execute: serverExecute(SEND_TO_USER_TOOL, sendToUserInput, () => "Message received for display."),
+};

src/core/coverage.ts

@@ -1,9 +1,9 @@
 /**
  * Extraction coverage — the pure core. THE TEACHER'S PROSE IS THE UNIT
  * (owner ruling, 2026-09-28): the extractor sees ONLY the teacher agent's
- * text blocks — no learner messages, no thinking, no tool calls or
+ * prose — ordinary text blocks and explicit send_to_user messages. No
- * results, no quiz blocks. Everything else is INVISIBLE to coverage: it
+ * learner messages, thinking, other tool calls/results, or quiz blocks.
- * neither opens nor joins a run, so answering a quiz or editing a learner
+ * Everything else is INVISIBLE to coverage: it neither opens nor joins a run, so answering a quiz or editing a learner
  * message triggers nothing. "Covered" is by construction exactly "what
  * the extractor saw": the fingerprint (sha256 of a message's view lines)
  * and the extractor's prompt share ONE selection — the teacher prose.
@@ -22,33 +22,27 @@
 import { createHash } from "node:crypto";
 
 import type { CoverageEntry } from "./contracts/graph.ts";
-import type { LhMessage } from "./native-messages.ts";
+import { failedOutputCallIds, userFacingTextOf, type LhMessage } from "./native-messages.ts";
 
 export type { CoverageEntry };
 
-/** The user-facing text of a native message (string or text blocks). */
-function textOf(content: unknown): string[] {
-	if (typeof content === "string") return content.trim() ? [content] : [];
-	if (!Array.isArray(content)) return [];
-	return content
-		.filter((c): c is { type: "text"; text: string } => (c as { type?: string }).type === "text")
-		.map((c) => c.text)
-		.filter((t) => t.trim().length > 0);
-}
-
 /**
  * The extraction-relevant lines of ONE native message — the shared seam
  * between the extractor's prompt and messageFingerprint (coverage).
  * TEACHER PROSE ONLY (owner, 2026-09-28): an assistant message yields one
- * line per text block; everything else (user messages, tool results,
+ * line per learner-facing prose block; everything else (user messages,
- * markers) yields NOTHING and is invisible to coverage. `mid` is the
+ * tool results, markers) yields NOTHING and is invisible to coverage.
- * message id — part of the hash input, so the same prose in two messages
+ * `mid` is the message id — part of the hash input, so the same prose in two messages
  * is two slots (per-message coverage).
  */
-export function messageViewLines(message: LhMessage, mid: string): string[] {
+export function messageViewLines(
+	message: LhMessage,
+	mid: string,
+	failedOutputCalls: ReadonlySet<string> = failedOutputCallIds([message]),
+): string[] {
 	const lines: string[] = [];
 	if ((message as { role?: string }).role !== "assistant") return lines;
-	for (const text of textOf((message as { content: unknown }).content)) {
+	for (const text of userFacingTextOf((message as { content: unknown }).content, failedOutputCalls)) {
 		lines.push(`TEACHER [${mid}] ${text.trim()}`);
 	}
 	return lines;
@@ -62,9 +56,10 @@ export function messageViewLines(message: LhMessage, mid: string): string[] {
  */
 export function teacherProseBlocks(messages: ReadonlyArray<LhMessage>): string[] {
 	const out: string[] = [];
+	const failedOutputCalls = failedOutputCallIds(messages);
 	for (const message of messages) {
 		if ((message as { role?: string }).role !== "assistant") continue;
-		for (const text of textOf((message as { content: unknown }).content)) out.push(text.trim());
+		for (const text of userFacingTextOf((message as { content: unknown }).content, failedOutputCalls)) out.push(text.trim());
 	}
 	return out;
 }
@@ -79,9 +74,9 @@ export function viewTokens(lines: string[]): number {
  * teacher prose, with the message id as the tag). Changes exactly when
  * the teacher prose of the message changes — nothing else can re-open it.
  */
-export function messageFingerprint(message: LhMessage): string {
+export function messageFingerprint(message: LhMessage, failedOutputCalls?: ReadonlySet<string>): string {
 	const h = createHash("sha256");
-	h.update(JSON.stringify([(message as { role?: string }).role, messageViewLines(message, message.id)]));
+	h.update(JSON.stringify([(message as { role?: string }).role, messageViewLines(message, message.id, failedOutputCalls)]));
 	return h.digest("hex");
 }
 
@@ -95,7 +90,12 @@ export interface CoverageSlot {
 /** Fingerprint a whole transcript, in order (used by the trigger, the run,
  *  and the coverage view — one derivation everywhere). */
 export function coverageSlots(messages: ReadonlyArray<LhMessage>): CoverageSlot[] {
-	return messages.map((message) => ({ message, fp: messageFingerprint(message), tokens: viewTokens(messageViewLines(message, message.id)) }));
+	const failedOutputCalls = failedOutputCallIds(messages);
+	return messages.map((message) => ({
+		message,
+		fp: messageFingerprint(message, failedOutputCalls),
+		tokens: viewTokens(messageViewLines(message, message.id, failedOutputCalls)),
+	}));
 }
 
 /** The covered-fingerprint set for one chat, from the ledger. */
@@ -131,16 +131,14 @@ export function coverageOf(
 	let uncoveredTokens = 0;
 	for (let i = 0; i < slots.length; i++) {
 		const slot = slots[i]!;
-		if (messageViewLines(slot.message, slot.message.id).length === 0) continue; // invisible
+		if (slot.tokens === 0) continue; // invisible (including failed output calls)
 		if (covered.has(slot.fp)) coveredTokens += slot.tokens;
 		else {
 			uncovered.push(i);
 			uncoveredTokens += slot.tokens;
 		}
 	}
-	const visibleCount = slots.length - slots.filter(
+	const visibleCount = slots.filter((s) => s.tokens > 0).length;
-		(s) => messageViewLines(s.message, s.message.id).length === 0,
-	).length;
 	return {
 		slots,
 		uncovered,

src/core/native-messages.ts

@@ -98,6 +98,55 @@ export function asAgentMessages(messages: readonly LhMessage[]): AgentMessage[]
 	return messages as unknown as AgentMessage[];
 }
 
+// ─── explicit learner-facing output ─────────────────────────────────────────
+
+export const SEND_TO_USER_TOOL = "send_to_user";
+
+/** Read the output tool's message without changing the native call. Also
+ * accepts partial arguments while streaming; malformed/empty inputs carry
+ * no prose. This projection is independent of the currently selected model. */
+export function sendToUserText(block: unknown): string | undefined {
+	if (!block || typeof block !== "object") return undefined;
+	const call = block as { type?: unknown; name?: unknown; arguments?: unknown };
+	if (call.type !== "toolCall" || call.name !== SEND_TO_USER_TOOL) return undefined;
+	if (!call.arguments || typeof call.arguments !== "object") return undefined;
+	const message = (call.arguments as { message?: unknown }).message;
+	return typeof message === "string" && message.trim() ? message : undefined;
+}
+
+/** Learner-facing prose, in content order. Only the explicit output tool
+ * joins ordinary text here — thinking and all other tool inputs stay out.
+ * Shared by coverage/extraction and Markdown; native history stays intact. */
+export function userFacingTextOf(content: unknown, failedOutputCalls?: ReadonlySet<string>): string[] {
+	if (typeof content === "string") return content.trim() ? [content] : [];
+	if (!Array.isArray(content)) return [];
+	const out: string[] = [];
+	for (const block of content) {
+		if (!block || typeof block !== "object") continue;
+		if (block.type === "toolCall" && failedOutputCalls?.has(block.id)) continue;
+		const text = block.type === "text" ? block.text : sendToUserText(block);
+		if (typeof text === "string" && text.trim()) out.push(text);
+	}
+	return out;
+}
+
+/** Failed output calls remain retry context, not delivered teaching.
+ * Truncated calls can have valid-looking partial arguments. Failed/aborted
+ * generations do not execute their calls at all, so may have no result. */
+export function failedOutputCallIds(messages: readonly LhMessage[]): ReadonlySet<string> {
+	const failed = new Set<string>();
+	for (const message of messages) {
+		if (message.role === "toolResult" && message.toolName === SEND_TO_USER_TOOL && message.isError) {
+			failed.add(message.toolCallId);
+		} else if (message.role === "assistant" && (message.stopReason === "error" || message.stopReason === "aborted")) {
+			for (const block of message.content) {
+				if (block.type === "toolCall" && block.name === SEND_TO_USER_TOOL) failed.add(block.id);
+			}
+		}
+	}
+	return failed;
+}
+
 // ─── id minting ──────────────────────────────────────────────────────────────
 
 /** The app-wide message id shape (same as the UIMessage-era mint). */

src/core/session-markdown.ts

@@ -22,22 +22,15 @@
 
 import type { LhMessage } from "./native-messages.ts";
 import {
+	failedOutputCallIds,
 	PRACTICE_CONCLUDE_TOOL,
 	PRACTICE_PROBLEM_TOOL,
 	problemInputForConclude,
+	SEND_TO_USER_TOOL,
+	userFacingTextOf,
 } from "./native-messages.ts";
 import type { ToolResultMessage } from "@earendil-works/pi-ai";
 
-/** The user-facing text blocks of a native message (string or text parts). */
-function textOf(content: unknown): string[] {
-	if (typeof content === "string") return content.trim() ? [content] : [];
-	if (!Array.isArray(content)) return [];
-	return content
-		.filter((c): c is { type: "text"; text: string } => (c as { type?: string }).type === "text")
-		.map((c) => c.text)
-		.filter((t) => t.trim().length > 0);
-}
-
 /** The practice join context (owner-approved, 2026-10-06 export round):
  *  practice tool RESULTS are acks — the statement, outcome, and verdict
  *  all live in the assistant's call arguments, and the model solution
@@ -48,6 +41,7 @@ export interface MarkdownContext {
 	messages: ReadonlyArray<LhMessage>;
 	/** toolCallId → the call part's name + arguments. */
 	calls: Map<string, { name: string; args: Record<string, unknown> | undefined }>;
+	failedOutputCalls?: ReadonlySet<string>;
 }
 
 function markdownContext(messages: ReadonlyArray<LhMessage>): MarkdownContext {
@@ -66,7 +60,7 @@ function markdownContext(messages: ReadonlyArray<LhMessage>): MarkdownContext {
 			}
 		}
 	}
-	return { messages, calls };
+	return { messages, calls, failedOutputCalls: failedOutputCallIds(messages) };
 }
 
 /** solvedWithHints → "Solved with hints" — the outcome enum reads as prose. */
@@ -172,16 +166,16 @@ export function messageMarkdown(
 	const parts: string[] = [];
 
 	if (role === "user") {
-		for (const text of textOf((message as { content: unknown }).content)) {
+		for (const text of userFacingTextOf((message as { content: unknown }).content)) {
 			parts.push(`### Learner${anchor}\n\n${text.trim()}`);
 		}
 	} else if (role === "assistant") {
-		for (const text of textOf((message as { content: unknown }).content)) {
+		for (const text of userFacingTextOf((message as { content: unknown }).content, ctx?.failedOutputCalls ?? failedOutputCallIds([message]))) {
 			parts.push(`### Teacher${anchor}\n\n${text.trim()}`);
 		}
 	} else if (role === "toolResult") {
 		const result = message as ToolResultMessage;
-		if (result.isError) return null; // retry context, not learning evidence
+		if (result.isError || result.toolName === SEND_TO_USER_TOOL) return null; // retry context or output ack, not learning evidence
 		const { heading, body } = toolResultBody(result, ctx);
 		parts.push(`### ${heading}${anchor}\n\n${body.join("\n\n")}`);
 	}

src/core/view.ts

@@ -34,7 +34,7 @@
 
 import type { AssistantMessage, ToolResultMessage } from "@earendil-works/pi-ai";
 import type { LhMarkerMessage, LhMessage } from "./native-messages.ts";
-import { modelSolutionForConclude, PRACTICE_CONCLUDE_TOOL, problemInputForConclude } from "./native-messages.ts";
+import { modelSolutionForConclude, PRACTICE_CONCLUDE_TOOL, problemInputForConclude, SEND_TO_USER_TOOL, sendToUserText } from "./native-messages.ts";
 import { activeCompactionOf, type CompactionDetails } from "./compaction.ts";
 import { QUESTION_TOOLS } from "./pending.ts";
 import type { SubagentArtifactData, SubagentResultMeta } from "./contracts/jobs.ts";
@@ -124,6 +124,14 @@ function lastSuccessfulPlanInit(parts: LhViewPart[]): number {
  *  view messages. Pure: the same input always projects to the same list. */
 export function projectView(messages: readonly LhMessage[], live?: LiveTurnState): LhViewMessage[] {
 	const out: LhViewMessage[] = [];
+	// Output calls become text rather than tool parts, so read settled
+	// failures up front: a failed call must retain the normal error path.
+	const outputErrors = new Map<string, ToolResultMessage>();
+	for (const message of messages) {
+		if (message.role === "toolResult" && message.toolName === SEND_TO_USER_TOOL && message.isError) {
+			outputErrors.set(message.toolCallId, message);
+		}
+	}
 
 	const lastAssistant = (): LhViewMessage | undefined => {
 		const last = out[out.length - 1];
@@ -218,6 +226,24 @@ export function projectView(messages: readonly LhMessage[], live?: LiveTurnState
 					reasoning.push({ type: "reasoning", id: `${m.id}-r${reasoningN++}`, text: block.thinking, state: "done" });
 				} else if (block.type === "toolCall") {
 					const part = toolPartOf(block, live, streamingMessage);
+					if (block.name === SEND_TO_USER_TOOL) {
+						// Failed/aborted generations never execute their calls;
+						// the provider error/abort UI already owns that outcome.
+						if (assistant.stopReason === "error" || assistant.stopReason === "aborted") continue;
+						const error = outputErrors.get(block.id);
+						if (error) applyResult(part, error);
+						if (part.state === "output-error") {
+							rest.push(part);
+						} else {
+							const text = sendToUserText(block);
+							if (text !== undefined) {
+								rest.push({ type: "text", id: `${m.id}-t${textN++}`, text, state: "done" });
+							}
+						}
+						// No live tool card or acknowledgement: this channel is
+						// ordinary prose, including while its arguments stream.
+						continue;
+					}
 					// The conclusion's reveal join (owner round, 2026-10-05): the
 					// hero of a conclude card is the modelSolution committed at POSE
 					// time — a record fold, enriched here so the card renders pure.

tests/send-to-user.test.ts

@@ -0,0 +1,366 @@
+/** Explicit Claude output: closed-network synthetic fixtures only. Native
+ * history stays native; UI, extraction, and Markdown read the same prose. */
+import assert from "node:assert/strict";
+import { createHash } from "node:crypto";
+import * as fs from "node:fs";
+import * as os from "node:os";
+import * as path from "node:path";
+import { after, describe, it } from "node:test";
+import { Value } from "typebox/value";
+import {
+	createFauxCore, fauxAssistantMessage, fauxText, fauxThinking, fauxToolCall,
+	type FauxResponseStep,
+} from "@earendil-works/pi-ai";
+import type { PiEngine } from "../src/agent/models.ts";
+import type { AgentBuildOptions } from "../src/agent/teacher-agent.ts";
+import type { LhMessage } from "../src/core/native-messages.ts";
+
+// Set the data/auth seams BEFORE importing app modules. Do not read local
+// keys, recordings, or learner sessions, even if a dev server is running.
+const scratch = fs.mkdtempSync(path.join(os.tmpdir(), "lh-send-to-user-"));
+const originalEnv = process.env;
+const originalFetch = globalThis.fetch;
+process.env = {
+	...(originalEnv.NODE_TEST_CONTEXT ? { NODE_TEST_CONTEXT: originalEnv.NODE_TEST_CONTEXT } : {}),
+	...(originalEnv.NODE_OPTIONS ? { NODE_OPTIONS: originalEnv.NODE_OPTIONS } : {}),
+	NODE_ENV: "test",
+	LH_DATA_DIR: path.join(scratch, "data"),
+	LH_AUTH_FILE: path.join(scratch, "auth.json"),
+	HOME: path.join(scratch, "home"),
+};
+globalThis.fetch = async () => { throw new Error("CLOSED: unexpected network request"); };
+after(() => {
+	process.env = originalEnv;
+	globalThis.fetch = originalFetch;
+	fs.rmSync(scratch, { recursive: true, force: true });
+});
+
+const { sendToUserTool } = await import("../src/agent/tools/send-to-user.ts");
+const { createProberAgent, createTeacherAgent, createPracticeAgent, composeInstructions } = await import("../src/agent/teacher-agent.ts");
+const { SEND_TO_USER_TOOL, activeProblemOf, asAgentMessages, newUserMessage, sendToUserText, toLlmMessages, userFacingTextOf } = await import("../src/core/native-messages.ts");
+const { coverageOf, messageFingerprint, messageViewLines, teacherProseBlocks } = await import("../src/core/coverage.ts");
+const { projectView } = await import("../src/core/view.ts");
+const { sessionMarkdown } = await import("../src/core/session-markdown.ts");
+const { transcriptView } = await import("../src/agent/subagents/extraction.ts");
+const { runSubagent } = await import("../src/agent/subagents/pi-run.ts");
+const { persistTurn } = await import("../src/server/turn-service.ts");
+const { runPiTurn } = await import("../src/server/pi/ui-stream.ts");
+const { SessionModel } = await import("../components/session-core.ts");
+const { chatStore } = await import("../src/store/chats.ts");
+const { jobStore } = await import("../src/store/jobs.ts");
+
+function scripted(provider: string, id: string, steps: FauxResponseStep[] = []) {
+	const faux = createFauxCore({ provider, models: [{ id }] });
+	faux.setResponses(steps);
+	const engine: PiEngine = { model: faux.getModel(), streamFn: faux.streamSimple };
+	return { engine, faux };
+}
+
+const chatId = chatStore.createChat("Synthetic output gate").id;
+const factories = {
+	prober: (opts: AgentBuildOptions) => createProberAgent({ chatId, chatStore, jobStore, deliver: () => {}, spawn: () => {} }, opts),
+	teacher: (opts: AgentBuildOptions) => createTeacherAgent({ chatId, chatStore, jobStore, spawn: () => {} }, opts),
+	practice: (opts: AgentBuildOptions) => createPracticeAgent({ chatId, chatStore }, opts),
+};
+
+function outputCall(message: string | number | null = "An explanation.", id = "send-1") {
+	return { type: "toolCall" as const, id, name: SEND_TO_USER_TOOL, arguments: { message } };
+}
+function assistant(content: unknown[], id = "a1"): LhMessage {
+	return { ...fauxAssistantMessage(""), content, id } as LhMessage;
+}
+function ack(callId = "send-1", isError = false): LhMessage {
+	return {
+		id: `result-${callId}`, role: "toolResult", toolCallId: callId, toolName: SEND_TO_USER_TOOL,
+		content: [{ type: "text", text: isError ? "Invalid tool input" : "Message received for display." }],
+		details: null, isError, timestamp: 1,
+	};
+}
+function prose(messages: ReturnType<typeof projectView>): string[] {
+	return messages.filter((m) => m.role === "assistant").flatMap((m) => m.parts.filter((p) => p.type === "text").map((p) => p.text!));
+}
+
+describe("send_to_user model gate", () => {
+	for (const [provider, id, enabled] of [
+		["anthropic", "claude-opus-5-5", true],
+		["anthropic", "claude-haiku-4-5-20251001", true],
+		["openrouter", "anthropic/claude-opus-5.5", true],
+		["openrouter", "anthropic/claude-sonnet-5.5", true],
+		["amazon-bedrock", "us.anthropic.claude-opus-5-5-v1:0", true],
+		["fixture", "CLAUDE-fixture", true],
+		["openrouter", "z-ai/glm-5.3-flash", false],
+		["openai", "gpt-4o-mini", false],
+		["anthropic", "opaque-alias", false],
+	] as const) {
+		it(`${provider}/${id}: ${enabled ? "includes" : "omits"} tool and description in all conversation agents`, () => {
+			const { engine } = scripted(provider, id);
+			for (const [kind, factory] of Object.entries(factories)) {
+				const agent = factory({ engine });
+				const output = agent.state.tools.find((tool) => tool.name === SEND_TO_USER_TOOL);
+				assert.equal(Boolean(output), enabled, kind);
+				if (enabled) {
+					assert.equal(output!.description, sendToUserTool.description);
+					assert.equal(typeof output!.prepareArguments, "function", "standard argument healing is wired");
+				}
+				assert.equal(agent.state.systemPrompt, composeInstructions(kind as keyof typeof factories));
+				assert.ok(!agent.state.systemPrompt.includes(SEND_TO_USER_TOOL), "no added prompt instructions");
+			}
+		});
+	}
+
+	it("explicitly injected teacher/practice test registries remain unchanged", () => {
+		const { engine } = scripted("anthropic", "claude-opus-5-5");
+		for (const factory of [factories.teacher, factories.practice]) {
+			assert.deepEqual(factory({ engine, tools: {} }).state.tools, []);
+		}
+	});
+
+	it("background agents do not acquire a learner-output tool", async () => {
+		let calls = 0;
+		const { engine } = scripted("anthropic", "claude-opus-5-5", [(context) => {
+			calls++;
+			assert.ok(!context.messages.some((m) => m.role === "system" && m.toolsAdded?.some((t) => t.name === SEND_TO_USER_TOOL)));
+			return fauxAssistantMessage("Synthetic background result.");
+		}]);
+		await runSubagent([], { role: "researcher", engine, systemPrompt: "Synthetic fixture.", prompt: "Finish.", maxTurns: 2 });
+		assert.equal(calls, 1);
+	});
+});
+
+describe("send_to_user mechanics", () => {
+	it("requires nonblank text and acknowledges without echoing or terminating", async () => {
+		assert.equal(sendToUserTool.name, SEND_TO_USER_TOOL);
+		for (const input of [{}, { message: "" }, { message: " \n\t" }, { message: 3 }, { message: null }]) {
+			assert.equal(Value.Check(sendToUserTool.parameters, input), false);
+		}
+		const message = "**A full explanation**\n\n$$a = b$$";
+		assert.equal(Value.Check(sendToUserTool.parameters, { message }), true);
+		const result = await sendToUserTool.execute("send-1", { message });
+		assert.ok(!result.isError);
+		assert.ok(!result.terminate);
+		assert.ok(!JSON.stringify(result).includes(message));
+		assert.deepEqual(result.content, [{ type: "text", text: "Message received for display." }]);
+	});
+
+	it("only extracts the output tool's nonblank message, without modifying it", () => {
+		const message = "  **Keep spacing and math** $x$\n";
+		assert.equal(sendToUserText(outputCall(message)), message);
+		for (const block of [null, {}, { type: "text", text: "ordinary" }, outputCall(2), outputCall("  "), { ...outputCall(), name: "other" }]) {
+			assert.equal(sendToUserText(block), undefined);
+		}
+		assert.deepEqual(userFacingTextOf([null, fauxThinking("Not lesson prose."), fauxText("First"), outputCall(message), fauxToolCall("quiz", { question: "Q?" })]), ["First", message]);
+	});
+});
+
+describe("send_to_user transcript projection", () => {
+	it("renders in place as prose, with thinking unchanged and no tool/ack duplication", () => {
+		const messages = [assistant([
+			fauxText("Before."), outputCall("**The lesson.** $x = 1$"),
+			fauxThinking("Private reasoning."), fauxToolCall("quiz", { question: "Q?" }, { id: "quiz-1" }),
+			fauxText("After."),
+		]), ack()];
+		const before = structuredClone(messages);
+		const view = projectView(messages);
+		assert.deepEqual(view[0]!.parts.map((p) => p.type), ["step-start", "reasoning", "text", "text", "tool-quiz", "text"]);
+		assert.deepEqual(prose(view), ["Before.", "**The lesson.** $x = 1$", "After."]);
+		assert.equal(view[0]!.parts.find((p) => p.type === "reasoning")!.text, "Private reasoning.");
+		assert.deepEqual(view[0]!.parts.filter((p) => p.type === "text").map((p) => p.id), ["a1-t0", "a1-t1", "a1-t2"]);
+		assert.deepEqual(messages, before, "projection never rewrites native content");
+		assert.deepEqual(projectView(JSON.parse(JSON.stringify(messages))), view, "reload is identical, without consulting a provider gate");
+	});
+
+	it("streams available arguments as replacing prose, never as a live tool card", () => {
+		const live = { inFlight: true, streamingIds: new Set(["a1"]), executions: new Map() };
+		for (const text of ["A", "A growing", "A growing explanation."]) {
+			const view = projectView([assistant([outputCall(text)])], live);
+			assert.deepEqual(prose(view), [text]);
+			assert.ok(!view[0]!.parts.some((p) => p.type.startsWith("tool-")));
+		}
+		const empty = projectView([assistant([{ ...outputCall(), arguments: {} }])], live);
+		assert.deepEqual(prose(empty), []);
+		assert.ok(!empty[0]!.parts.some((p) => p.type.startsWith("tool-")));
+	});
+
+	it("malformed messages contain no prose; failures keep the existing error path live and after reload", () => {
+		assert.deepEqual(prose(projectView([assistant([outputCall(3)])])), []);
+		const messages = [assistant([outputCall("Incomplete teaching.")]), ack("send-1", true)];
+		const settled = projectView(messages);
+		assert.deepEqual(prose(settled), []);
+		assert.equal(settled[0]!.parts[1]!.type, "tool-send_to_user");
+		assert.equal(settled[0]!.parts[1]!.state, "output-error");
+		const live = projectView(messages.slice(0, 1), {
+			inFlight: true, streamingIds: new Set(["a1"]),
+			executions: new Map([["send-1", { isError: true, errorText: "Invalid tool input" }]]),
+		});
+		assert.deepEqual(prose(live), []);
+		assert.equal(live[0]!.parts[1]!.state, "output-error");
+	});
+});
+
+describe("send_to_user extraction and Markdown", () => {
+	it("selects output prose once and in order, preserving old fingerprints", () => {
+		const message = assistant([fauxText("First."), outputCall("Second."), fauxThinking("Hidden."), outputCall("Third.", "send-2")]);
+		const messages = [message, ack(), ack("send-2")];
+		assert.deepEqual(messageViewLines(message, "a1"), ["TEACHER [a1] First.", "TEACHER [a1] Second.", "TEACHER [a1] Third."]);
+		assert.deepEqual(teacherProseBlocks(messages), ["First.", "Second.", "Third."]);
+		assert.equal(coverageOf(messages, [], "fixture").uncoveredCount, 1);
+		const md = sessionMarkdown(messages, { anchors: false });
+		assert.equal(md, "### Teacher\n\nFirst.\n\n### Teacher\n\nSecond.\n\n### Teacher\n\nThird.");
+		const record = chatStore.createChat("Synthetic extraction");
+		assert.equal(transcriptView({ ...record, messages }), "# Synthetic extraction\n\nTEACHER [a1] First.\n\nTEACHER [a1] Second.\n\nTEACHER [a1] Third.");
+		const legacy = assistant([fauxText("Old text."), fauxThinking("Old thinking.")], "legacy");
+		const oldFingerprint = createHash("sha256").update(JSON.stringify(["assistant", ["TEACHER [legacy] Old text."]])).digest("hex");
+		assert.equal(messageFingerprint(legacy), oldFingerprint, "no re-extraction/migration of legacy prose");
+	});
+
+	it("does not extract/export failed output calls, including partial calls from truncated responses", () => {
+		const message = assistant([fauxText("Keep this."), outputCall("Do not treat this as delivered.")]);
+		const messages = [message, ack("send-1", true)];
+		assert.deepEqual(teacherProseBlocks(messages), ["Keep this."]);
+		assert.equal(sessionMarkdown(messages, { anchors: false }), "### Teacher\n\nKeep this.");
+		const record = chatStore.createChat("Failed output fixture");
+		assert.ok(!transcriptView({ ...record, messages }).includes("Do not treat"));
+		const coverage = coverageOf([assistant([outputCall()]), ack("send-1", true)], [], "fixture");
+		assert.equal(coverage.uncoveredCount, 0);
+		assert.equal(coverage.uncoveredTokens, 0);
+	});
+});
+
+describe("send_to_user interrupted generations", () => {
+	for (const stopReason of ["error", "aborted"] as const) {
+		it(`${stopReason} without a tool result never becomes delivered teaching; ordinary text stays unchanged`, () => {
+			const message = { ...assistant([fauxText("Keep ordinary text."), outputCall("Unfinished output.")]), stopReason };
+			const messages = [message];
+			assert.deepEqual(prose(projectView(messages)), ["Keep ordinary text."]);
+			assert.deepEqual(prose(projectView(JSON.parse(JSON.stringify(messages)))), ["Keep ordinary text."]);
+			assert.deepEqual(messageViewLines(message, message.id), ["TEACHER [a1] Keep ordinary text."]);
+			assert.deepEqual(teacherProseBlocks(messages), ["Keep ordinary text."]);
+			assert.equal(sessionMarkdown(messages, { anchors: false }), "### Teacher\n\nKeep ordinary text.");
+			const onlyOutput = { ...assistant([outputCall("Unfinished output.")]), stopReason };
+			assert.equal(coverageOf([onlyOutput], [], "fixture").uncoveredCount, 0);
+		});
+	}
+});
+
+describe("send_to_user native flow (offline)", () => {
+	it("output alone continues the loop, so the model receives its native acknowledgement", async () => {
+		const { engine, faux } = scripted("anthropic", "claude-opus-5-5", [
+			fauxAssistantMessage([outputCall("Read this first.")], { stopReason: "toolUse" }),
+			(context) => {
+				assert.ok(context.messages.some((m) => m.role === "toolResult" && m.toolName === SEND_TO_USER_TOOL));
+				return fauxAssistantMessage([fauxText("Final plain reply.")]);
+			},
+		]);
+		const agent = createTeacherAgent(undefined, { engine });
+		await agent.prompt("Synthetic request.");
+		assert.equal(faux.state.callCount, 2);
+	});
+
+	for (const outputFirst of [true, false]) {
+		it(`output + practice problem stops after the pose (${outputFirst ? "output first" : "problem first"})`, async () => {
+			const output = outputCall("Try this practice problem.");
+			const problem = fauxToolCall("problem", {
+				statement: "What is two plus two?", mode: "recall", modelSolution: "Four.",
+			}, { id: "problem-1" });
+			const { engine, faux } = scripted("anthropic", "claude-opus-5-5", [
+				fauxAssistantMessage(outputFirst ? [output, problem] : [problem, output], { stopReason: "toolUse" }),
+				fauxAssistantMessage("Premature continuation must not run."),
+			]);
+			const agent = createPracticeAgent({ chatId, chatStore }, { engine });
+			await agent.prompt("Pose a synthetic problem.");
+			assert.equal(faux.state.callCount, 1, "wait for the learner after a successful mixed-batch pose");
+			const results = agent.state.messages.filter((m) => m.role === "toolResult");
+			assert.equal(results.length, 2);
+			assert.ok(results.every((m) => !m.isError));
+		});
+	}
+
+	for (const stopReason of ["error", "aborted"] as const) {
+		it(`${stopReason} mixed output/problem generation never executes or activates the pose`, async () => {
+			const { engine, faux } = scripted("anthropic", "claude-opus-5-5", [
+				fauxAssistantMessage([
+					outputCall("Undelivered introduction."),
+					fauxToolCall("problem", {
+						statement: "What is two plus two?", mode: "recall", modelSolution: "Four.",
+					}, { id: "unfinished-problem" }),
+				], { stopReason }),
+			]);
+			const agent = createPracticeAgent({ chatId, chatStore }, { engine });
+			await agent.prompt("Pose a synthetic problem.");
+			assert.equal(faux.state.callCount, 1);
+			assert.ok(!agent.state.messages.some((m) => m.role === "toolResult"));
+			const messages = agent.state.messages.map((m, i) => ({ ...m, id: `interrupted-${i}` })) as LhMessage[];
+			assert.equal(activeProblemOf(messages), null);
+			assert.deepEqual(prose(projectView(messages)), []);
+		});
+	}
+
+	it("a rejected mixed-batch practice pose retries, then stops after the successful pose", async () => {
+		const { engine, faux } = scripted("anthropic", "claude-opus-5-5", [
+			fauxAssistantMessage([
+				outputCall("Try this practice problem."),
+				fauxToolCall("problem", { statement: "Incomplete problem.", mode: "recall" }, { id: "bad-problem" }),
+			], { stopReason: "toolUse" }),
+			fauxAssistantMessage([
+				outputCall("Here is the corrected problem.", "send-2"),
+				fauxToolCall("problem", {
+					statement: "What is two plus two?", mode: "recall", modelSolution: "Four.",
+				}, { id: "good-problem" }),
+			], { stopReason: "toolUse" }),
+			fauxAssistantMessage("Premature continuation must not run."),
+		]);
+		const agent = createPracticeAgent({ chatId, chatStore }, { engine });
+		await agent.prompt("Pose a synthetic problem.");
+		assert.equal(faux.state.callCount, 2, "failed authoring retries; successful pose waits for the learner");
+		const results = agent.state.messages.filter((m) => m.role === "toolResult" && m.toolName === "problem");
+		assert.equal(results.length, 2);
+		assert.ok(results[0]?.role === "toolResult" && results[0].isError);
+		assert.ok(results[1]?.role === "toolResult" && !results[1].isError);
+	});
+
+	it("output + question streams, persists natively, replays, and reloads as prose before the question", async () => {
+		const lesson = "**Synthetic lesson:** four is twice two. $2 + 2 = 4$";
+		const quiz = {
+			type: "check", nodeId: "synthetic", question: "What is two plus two?",
+			options: [{ label: "Four", value: "4" }, { label: "Five", value: "5" }],
+			correctAnswer: "4", explanation: "Add two pairs.",
+		};
+		const { engine, faux } = scripted("openrouter", "anthropic/claude-opus-5.5", [
+			fauxAssistantMessage([
+				fauxThinking("Synthetic private thought."), outputCall(lesson),
+				fauxToolCall("quiz", quiz, { id: "quiz-1" }),
+			], { stopReason: "toolUse" }),
+		]);
+		const chat = chatStore.createChat("Synthetic native output flow");
+		const user = newUserMessage("Explain synthetic arithmetic.");
+		chatStore.saveMessages(chat.id, [user]);
+		const agent = createTeacherAgent(undefined, { engine, messages: asAgentMessages([user]) });
+		const handle = runPiTurn({
+			agent,
+			updateFlushMs: 0,
+			onFinish: (messages, aborted) => { persistTurn(chatStore, chat.id, 1, messages, aborted); },
+		});
+		const wire = await new Response(handle.subscribe()).text();
+		assert.ok(wire.endsWith("data: [DONE]\n\n"));
+		assert.equal(faux.state.callCount, 1, "question stops the mixed batch as before");
+		const saved = chatStore.getChat(chat.id)!.messages;
+		const response = saved.find((m) => m.role === "assistant")!;
+		assert.equal(response.role, "assistant");
+		if (response.role !== "assistant") assert.fail("missing assistant");
+		assert.deepEqual(response.content.map((c) => c.type), ["thinking", "toolCall", "toolCall"]);
+		assert.deepEqual(response.content[1], outputCall(lesson));
+		assert.ok(saved.some((m) => m.role === "toolResult" && m.toolName === SEND_TO_USER_TOOL), "native output ack persists");
+		assert.ok(!saved.some((m) => m.role === "toolResult" && m.toolName === "quiz"), "question placeholder remains transient");
+		const providerHistory = toLlmMessages(asAgentMessages(saved));
+		assert.deepEqual(providerHistory.find((m) => m.role === "assistant")!.content, response.content, "next request keeps native call/thinking structure");
+		assert.deepEqual(prose(projectView(saved)), [lesson]);
+		const parts = projectView(saved).flatMap((m) => m.parts);
+		assert.ok(parts.findIndex((p) => p.type === "text") < parts.findIndex((p) => p.type === "tool-quiz"));
+		const client = new SessionModel({ chatId: chat.id, initialMessages: [user], fetch: globalThis.fetch });
+		await client.consumeStream(new Response(wire));
+		assert.deepEqual(prose(client.getState().messages), [lesson], "native event replay shows the lesson exactly once");
+		assert.deepEqual(prose(projectView(JSON.parse(JSON.stringify(saved)))), [lesson], "reload preserves the lesson");
+		assert.deepEqual(teacherProseBlocks(saved), [lesson]);
+		assert.equal(sessionMarkdown(saved).split(lesson).length - 1, 1);
+	});
+});