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TimCodes04TimCodes04/second-brain/.claude/skills/quiz/SKILL.md

quiz

Skill1 starsChanged 51 days agoMITView on GitHub

Run an interactive LLM-graded retrieval quiz in the terminal over one course or a set of lessons, then update mastery, write the quiz log, and spawn targeted flashcards from every error.

14 other projects use a version of this.

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  • remenoscodesSkill

    progress

    Longitudinal language learning progress report with metrics, trends, and insights

    Also in 4 projects that use this

The file

We split this skill into the rules it gives an agent

7 rules. 0 are common, 3 are distinctive, and 4 are very specific to this project.

  • 0

    Common

    Most of the 13 edited versions we read keep these.

  • 3

    Distinctive

    This author's own choices. Worth a look.

  • 4

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Very specific:

    Default: interleaved mix across the course's status: read|quizzed|mastered lessons, weighted toward low mastery and staleness.

    line 15
  2. Very specific:

    Read the scoped lessons AND their concept notes to ground questions.

    line 16
  3. Distinctive:

    Before asking, privately write a 10-point rubric for the question.

    line 20
  4. Distinctive:

    Ask conversationally. Mix formats per pedagogy.md: free recall, explain-why, worked problems (user answers in text/LaTeX-ish), transfer …

    line 21
  5. Distinctive:

    Every 2–3 questions, ask for a confidence rating (1–5) before grading — flag high-confidence misses.

    line 22
  6. Very specific:

    All rules below are defined in docs/vault-schema.md (lesson type) — apply them exactly.

    line 28
  7. Very specific:

    Write the quiz log per templates/quiz-log.md at courses/<slug>/quizzes/YYYY-MM-DD Quiz <scope>.md — per-question record, weak_concepts …

    line 31

“Common” is measured: kept by at least 6 in 10 of the 13 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

/quiz [<course-slug>] [--lessons 1,3] [--weak] [--n <questions>]

Interactive retrieval practice — the core of the testing effect. Read docs/pedagogy.md (quiz rules) and docs/vault-schema.md (mastery update rule, quiz-log schema) first. Vault: <vault>.

Scope selection

  • --lessons: exactly those lessons of the course.
  • --weak: lessons with mastery < 60, plus stale ones (last_quizzed > 21 days, mastery < 85).
  • Default: interleaved mix across the course's status: read|quizzed|mastered lessons, weighted toward low mastery and staleness. No course given → mix across all active courses (max interleaving).
  • Read the scoped lessons AND their concept notes to ground questions. Default length: 6–10 questions (--n overrides).

Session loop (one question at a time)

  1. Before asking, privately write a 10-point rubric for the question.
  2. Ask conversationally. Mix formats per pedagogy.md: free recall, explain-why, worked problems (user answers in text/LaTeX-ish), transfer questions. Never multiple choice.
  3. Every 2–3 questions, ask for a confidence rating (1–5) before grading — flag high-confidence misses.
  4. Grade /10 against the rubric with partial credit. Give elaborative feedback: correct answer, why, misconception note if relevant, link to the concept note. If the missed knowledge is encoded in the user's mind palace (grep palace/ for a link to the concept), add the location as a retrieval cue ("this lives in your palace — <room>, <spot>") — cue the place, never recite their image. Then next question.
  5. The user can stop anytime ("stop", or the equivalent in their language) — finish the session bookkeeping with what was answered.

After the last question

All rules below are defined in docs/vault-schema.md (lesson type) — apply them exactly.

  1. Overall score /100 (weighted by rubric points), plus a lesson score (0–100) for each covered lesson from its own questions only.
  2. Write the quiz log per templates/quiz-log.md at courses/<slug>/quizzes/YYYY-MM-DD Quiz <scope>.md — per-question record, weak_concepts (anything graded ≤ 5, plus high-confidence misses), and the per-lesson ## Result table. A session spanning several courses writes one log per course. If the filename already exists, append (2), (3), … — never overwrite a log.
  3. Update each covered lesson's frontmatter, reading last_quizzed before overwriting it: mastery (first quiz, i.e. last_quizzed empty → lesson score; else round(0.4×old + 0.6×lesson score)), then last_quizzed = today, then status (mastered iff mastery ≥ 85 and the last two lesson scores — this one and the previous quiz log's — are ≥ 80, else quizzed; this also demotes a slipped mastered). Recompute each affected course's lessons_done. Set each involved concept note's mastery to 10 × its most recent question grade.
  4. For every failed item (≤ 5/10): append 1–2 new targeted cards to the relevant lesson's card file (or concepts/Inbox Cards.md, deck #flashcards/inbox, if courseless), attacking exactly the gap. New cards have no SR comment → due immediately. Never touch existing card lines with <!--SR: comments; bump card_count.
  5. Report: score, per-lesson mastery changes, cards spawned, and what /study should prioritize tomorrow.

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