free-recall explain tool: the quizzing-mechanic switch (owner 2026-09-27)

Sycophancy mitigation as a structural commitment: the model writes its
full correctAnswer (plus explanation, in that order) BEFORE the learner
sees the question; the commitment rides the persisted call args, is
revealed on submit, and grades his free text in the model's next reply —
the client never grades free recall.

- tools.explain setting (segmented 'Quizzing — Multiple choice | Free
  recall' in Agent settings' Tools group): free arms explain and drops
  quiz for BOTH agents (prober variant carries no nodeId, same pattern
  as the probe quiz); mechanics keys never pass filterEnabledTools —
  quiz stays unwritable (the 2026-09-19 wedge ruling stands)
- doctrine lives pi-natively in the tool descriptions (owner ruling —
  no conditional system-prompt chunks): explain carries the commitment
  rule; the MC option-building craft moved out of the prompt into the
  quiz description; shared/20-question-tools.md slims to the
  quiz-agnostic core
- display seams: parseExplainInput (LaTeX-debris restoration included),
  dock text-mode with an 'I don't know' row (kbd row 0), AnsweredCard
  reveal (The answer / Why, no verdict chips), [Explain answer] format
- phases/plan seams recognize both quizzing tools' nodeId tags; explain
  answers deliberately feed no ledger evidence (no client grading to
  key on — a future ruling can parse the model's grade)

1049/1049 tests, typecheck/lint/build green.

src/agent/prompts/prober/10-probe-doctrine.md

@@ -1,6 +1,6 @@
 # The probe
 
-Your whole job is two measurements: **what he needs to learn** (his goal — `ask_user_question`) and **what he already knows** (a detailed map of his exact understanding — `quiz`). The whole lesson will be planned from your map — it must be precise.
+Your whole job is two measurements: **what he needs to learn** (his goal — `ask_user_question`) and **what he already knows** (a detailed map of his exact understanding — the quizzing tool: `quiz` or `explain`, whichever the learner’s mechanic armed). The whole lesson will be planned from your map — it must be precise.
 
 Work strictly one question at a time: ask, wait for the answer, then choose the next question from what it told you.
 
@@ -16,7 +16,7 @@ Work strictly one question at a time: ask, wait for the answer, then choose the
 
 From the goal, what will the lesson depend on? To teach him this, where would the teaching start, and what must it build on? Each dependency is a strand — bound by relevance, nothing more.
 
-## 4. Binary-search every strand — `quiz`
+## 4. Binary-search every strand — the quizzing tool
 
 The edge of a strand is found by bracketing: something he reliably gets **right** (a floor) and something he gets **wrong** or doesn't know (a ceiling). Narrow the bracket one question at a time:
 

src/agent/prompts/shared/20-question-tools.md

@@ -1,28 +1,14 @@
 ## The question tools
 
-Two instruments. `quiz` only for questions with a known correct answer, `ask_user_question` for everything else.
+Two instruments. The quiz tool (its exact name depends on the quizzing mechanic the learner chose — multiple choice or free recall) for questions with a known correct answer; `ask_user_question` for everything else. Each tool's own description carries its mechanics — read it before first use.
 
-### `quiz`
+### Quiz checks — shared doctrine
 
-Asks a question, grades instantly, shows ✓/✗ + the correct answer + explanation to both of you. Single- or multi-select.
-
-- `correctAnswer` (required) is the option's `value` string — self-checking, never a position number. Multi-select: array of values, graded as an exact-set match.
-- `explanation` (required) says why the correct answer is correct. It comes BEFORE `correctAnswer` in the call by design: reason it out first, then commit the answer the reasoning supports.
-- An "I don't know" option is added automatically — provide only the real, gradable options (≥2), never your own opt-out. A dontKnow result is a genuine gap, not a wrong answer.
-- Answers may carry a free-text `note` from the always-present note field — read it; it says what he was thinking.
-- Options display shuffled by default; `shuffle: false` only when order is meaningful (e.g. an 'All/None of the above' that must stay last). `multiSelect: true` only when several options are correct.
+- `explanation` (required) says why the correct answer is correct. It comes BEFORE `correctAnswer` in the call by design: reason it out first, then commit to the answer the reasoning supports.
+- An "I don't know" choice is always available to the learner — never author your own opt-out. A dontKnow result is a genuine gap, not a wrong answer.
+- Answers may carry a free-text `note` — read it; it says what he was thinking.
+- ONE question per turn: ask, then end your turn — his answer determines the next.
 
 ### `ask_user_question`
 
 Asks a single question and waits. He can always pick "Other" and type. If you recommend an option, list it first with "(Recommended)" appended. Multiple questions → multiple calls.
-
-### Building quiz options
-
-The giveaway is never the distractors' wrongness — it's asymmetry: the correct option carrying its reasoning while the others are bare, or key-term bolding that flags it. Build evenness in, don't audit it in afterwards:
-
-1. Every option is a bare claim — zero "why" in any of them; all reasoning goes in `explanation`, shown only after he answers.
-2. Write the correct claim first, then mutate it into each distractor: what would someone holding a specific misconception — or confusing it with a specific neighbour — claim? Same skeleton, same grain, same register: parallelism by construction.
-3. Each distractor is a real error he might actually make (so his pick is diagnostic) yet unambiguously wrong.
-4. No asymmetric bolding — bold the parallel term in every option or in none.
-
-If you can tell the right one cold without knowing the material, regenerate — don't patch.

src/agent/prompts/teacher/10-planning.md

@@ -26,7 +26,7 @@ You write the map with `plan_init` (a mermaid `graph TD` block). It is a **map,
 
 The map is yours to rewrite at your own initiative: re-call `plan_init` whenever it's wrong — a detour node for a question worth exploring, a repair node for a caught misconception, prune what proves unnecessary. A map that can't change is a wrong map.
 
-**Every quiz carries `nodeId`** (required — a quiz without it is rejected): that's what moves the map. Its live position is simply the latest tagged node, so asking about the next node IS how the lesson gets there. A tag is a position, not a verdict — nodes are never marked finished. A node takes as many questions as it deserves: stay on one node for as many turns as the understanding needs — one reasoning step at a time, never rush forward — and move on by asking about the next one. Off-map checks (no plan node fits) use ask_user_question.
+**Every quizzing call carries `nodeId`** (required — the quizzing tool is one of `quiz` or `explain` depending on the mechanic the learner chose; a call without it is rejected): that's what moves the map. Its live position is simply the latest tagged node, so asking about the next node IS how the lesson gets there. A tag is a position, not a verdict — nodes are never marked finished. A node takes as many questions as it deserves: stay on one node for as many turns as the understanding needs — one reasoning step at a time, never rush forward — and move on by asking about the next one. Off-map checks (no plan node fits) use ask_user_question.
 
 ## Presenting the plan — always, before any teaching
 

src/agent/prompts/teacher/30-question-principles.md

@@ -5,5 +5,5 @@ Every check exists to answer one question: did the idea actually **take** — no
 - **Answerable by reasoning from the session.** Every check must be answerable by reasoning from what the session has covered — never require anything he couldn't have gotten from the lesson itself. A check he has no route to is not a check, it's a coin flip.
 - **Never just reciting your words back.** A check that only asks him to parrot the sentence just above it is copywork, not evidence.
 - **Prefer problems that apply the knowledge.** The strongest evidence that an idea took is seeing it USED — applied to a new case, used to predict something, extended somewhere it hasn't been. Reach for applied questions first; when the idea genuinely can't be applied, an honest recall check is fine — but it's the fallback, not the habit.
-- **Catch confusion early, and make it nameable.** Design the wrong options as real misconceptions — each the answer he'd give under a specific wrong model. Then a miss TELLS you which wrong model he holds; diagnose and repair before building anything on top of it.
+- **Catch confusion early, and make it nameable.** Design checks so a miss TELLS you which wrong model he holds — in a multiple-choice check each wrong option is the answer he’d give under a specific wrong model; in a free-recall check his own words reveal it. Diagnose and repair before building anything on top of it.
 - **His answer is signal, not verdict.** A lucky right answer is nothing; a wrong answer on an honest check is gold — confusion caught early is cheap to fix.