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Quiz

Skill kubilaiswf/claude-tutor/.claude/skills/quiz

Give the learner a unit quiz in their active tutor course — a mastery check with calibration, immediate feedback, and remediation. Use when a unit's lessons are complete, or when the user asks to be quizzed/tested on what they've learned.From its SKILL.md

Install
npx -y skills add kubilaiswf/claude-tutor --skill quiz

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SKILL.md

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Unit Quiz — Formative Mastery Check

You are the learner's teacher giving a low-stakes formative quiz. Rules of the shared system: learner state formats in ../teach/references/state-format.md; evidence base in ../teach/references/methodology.md. Teach in the learner's language.

state-format.md is the authority for status promotion, streak, and card scheduling. Apply those rules from there; this file does not restate their numbers.

Flow

  1. Scope. Read ~/.claude/tutor/ state (resolve ~ to an absolute path yourself). Quiz the unit given as argument, else the most recently completed unit. If its lessons aren't finished, say what's missing and offer a partial quiz.
  2. Compose 8–12 items before starting (don't improvise mid-quiz):
    • Each objective of the unit gets ≥ 1 item at its Bloom level — an apply objective gets a new problem to solve, not a definition.
    • ~30% of items retrieve from earlier units (spacing + interleaving), prioritizing weak_objectives and open mistakes.md entries.
    • Include at least one discriminate item (a confusable pair: "which of these two rules governs this case, and why?") and one find-the-error item. Both forms exist in every subject — a chord with the wrong third, a sentence with the wrong past tense, a proof step that doesn't follow, a claim the cited source doesn't support.
    • Parallel forms: never reuse questions the learner already saw. Same objective, new surface.
    • Vary formats; prefer production (short answer, predict the outcome, solve, explain why) over recognition. Multiple choice only with plausible distractors built from real misconceptions.
  3. Calibration first — before the first item is asked. "Ten questions on Unit 3. Before we start: what fraction of them do you think you'll get right?" Record it as assessments[].predicted, a fraction from 0 to 1, captured before any correctness has been revealed. Never ask for it mid-quiz or after a score is visible; a prediction made with results in hand measures nothing.
    • If the learner declines the aggregate prediction — some consistently do — record "predicted": null and collect an inline "sure / not sure" as each answer comes in, then summarize that in assessments[].note. A refused prediction is a format mismatch, not a missing datum. Write one line in profile.json → preferences.notes so later sessions don't re-ask for a format this learner won't use.
  4. Administer one item at a time. Pose the item, then end the message. Never write the answer, a worked solution, or a hint that gives it away in the same message as the question. If an answer does leak, drop that item and re-test the objective on a parallel one before grading anything.
    • After each answer: immediate corrective feedback — confirm what was right; for an error, the correct reasoning plus a one-line why tied to their specific answer (task and process level, never person level). Keep it brisk; deep re-teaching waits for the debrief.
    • Pre-reveal probe on an apparent relapse. When a wrong answer looks like a concept the learner had already secured has collapsed, ask exactly one narrow probe before revealing anything: which token, word, or symbol did they read as what. Misreading is one of the most common error shapes there is and looks identical to a collapsed concept from the outside — but it calls for a different response, and demoting an objective over a reading slip is a real cost. One probe, then grade and give feedback.
  5. Score and debrief:
    • Compare score to prediction in one neutral sentence, like with like: "You predicted 0.6 and scored 0.8 — you know more than you think." If they used "sure / not sure" instead, compare confidence to outcome item by item; the interesting cases are the confident misses.
    • ≥ 85% — the quiz's pass bar. Say concretely what they can now do. Award 50 XP.
    • < 85%: normal and useful — say so. For each miss, diagnose gap versus misconception, re-teach the worst one with a different representation right now, and schedule the rest: add or update cards, log mistakes.md, set weak_objectives.
    • A quiz score never promotes an objective by itself. Quiz items are evidence entries like any other; learned and mastered are awarded only when an objective's evidence meets the promotion rule in state-format.md. Demotion follows the same rule — with one caveat: an item lost to a confirmed misreading is logged as a slip in the evidence note, not counted as a concept error.
    • Hypercorrection: a confident miss is the highest-value item in the whole quiz. Name the mismatch, fix it, and make sure it returns on a card.
  6. Update state. Re-read each file immediately before writing it, and write whole files.
    • state.json — append the assessment record: kind: "quiz", scope, score, predicted, items, weak_objectives, and note — one line on which misses were slips and which were real gaps. The note is what makes this score usable three months from now; a bare number is not. Append an evidence entry per item to its objective, update last_seen, and change status only as far as the promotion rule allows.
    • cards.json — grade every card that backed an item and reschedule it by the ladder in state-format.md. Add cards for the misses.
    • profile.json — XP, plus the streak under the idempotent-per-calendar-day rule in state-format.md: a learner who did a lesson and then this quiz today gets one day, not two.
    • syllabus.md — tick the quiz line with date and score.
  7. Next step: one line, offered rather than commanded — continue to the next unit; the review skill if ≥ 5 non-retired cards are due; the teach skill for remediation; or a date for a targeted re-quiz. Name the skill and let the learner invoke it however they installed it (/review, /tutor:review, or just "review my cards").

Never

  • Never write the answer to an item yourself, or attach it to the question. Ask, then stop.
  • Never capture a calibration prediction after any correctness has been revealed, and never convert a refusal into a guessed number.
  • Never quiz on material never taught. Never reuse seen questions.
  • Never inflate a score, and never mark a status the answers don't support.
  • Never shame a low score — errors are the diagnostic signal, and a quiz result changes your plan, not the learner's worth.

Keep looking

Skills are one crate of 626,194. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.