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Quiz me

Skill lusipad/zhizhi/skills/quiz-me

Quiz-me (考考我) — after a large change, or any change the user didn't author themselves (AI-written code), generates a report explaining the context, intuition, and mechanics of what changed — then quizzes the user on it and grades the answers. Recommends merging only when the user passes completely. Use when the user says "quiz me", "考考我", "测测我", "我不放心这次改动", "do I actually understand this change", "explain what happened then test me", or after a long working session before merge.From its SKILL.md

Install
npx -y skills add lusipad/zhizhi --skill quiz-me

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SKILL.md

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Quiz Me

After a long session, more happened than the user realizes. Reading diffs gives only a light understanding, because much of the new behavior depends on existing code paths the diff never shows. This skill closes that gap: explain, then verify the explanation landed. The user merges only after passing.

Language: write the report, quiz questions, and verdicts in the language the user is speaking. The verdict keywords PASS / NOT YET stay in English in every language — they are the trust anchor. File names and code identifiers stay in English.

Step 1 — Scope what "the change" really is

Don't stop at the diff:

  • The diff itself
  • The existing code paths the new code calls into or is called from
  • Behavior that changed without its code changing (a config default now taking effect, a caller now hitting a different branch)
  • What the change relies on continuing to be true (invariants, ordering, formats)

Step 2 — Write the report

Sections, in order:

  1. Why — the problem this change solves, one paragraph
  2. Mental model — the intuition: how to think about the new behavior in one diagram or metaphor. If the user keeps one idea, it's this one.
  3. What changed — a guided walk through the diff, grouped by intent rather than by file
  4. What it stands on — the pre-existing code paths and invariants the change depends on; the part diffs never show
  5. Where it could break — the inputs, states, or future edits most likely to hurt it

For small changes, sections may be a sentence or two and Why / What changed may merge — but never thin out "What it stands on" or "Where it could break"; they are the point.

Default to Markdown. If the user asks for HTML (or the change is big enough that navigation helps), produce a single self-contained HTML file with the quiz at the bottom.

Write the report to a file, not only into chat — grading spans multiple turns, and the report is the answer key; it must survive context compaction. Put it in the project's working-docs home or a gitignored directory in the repo — not a session temp dir (grading may resume in a fresh session), and never loose in the source tree.

Step 3 — Quiz

3–8 questions at the bottom of the report, scaled to the change's conceptual surface. The no-trivia rule below outranks the count: write fewer questions rather than pad. For substantial changes include at least one of each; drop a category the change genuinely doesn't have rather than invent trivia:

  • A question about behavior that depends on pre-existing code (not visible in diff)
  • A failure mode: "what happens if <input/state X>?"
  • A tracing question: "a request comes in with Y — walk me through what runs"
  • A design question: "why was alternative Z not used?"

Format for low friction — a quiz nobody takes verifies nothing:

  • Default to multiple choice (at least two-thirds of the questions), with distractors built from plausible misconceptions, not filler. A user who actually holds the misconception must find its distractor attractive.
  • At most one short-answer question per three questions (the tracing question is usually the one), answerable in a handful of keywords or arrows — say so explicitly.
  • Number questions and letter the options so the whole quiz can be answered in one line ("1B 2A 3C"). If the host provides a structured choice UI, use it.
  • No trivia — every question's answer should matter for operating or reviewing this code.

Step 4 — Grade strictly

  • Grade each answer; partial credit is a fail for that question. For short answers, judge the concept, not the prose — terse keyword answers are fine.
  • For each miss: re-explain with a file/line reference, then ask a variant of the question (not the same one — the user can echo, that's not understanding).
  • Repeat until everything passes — or the user stops. Stopping early is always allowed and always a NOT YET, never a reluctant PASS.

End with an explicit verdict:

  • PASS — you understand this change; safe to merge from an understanding standpoint.
  • NOT YET — misses on: <topics>. Re-quiz when ready.

Never soften the verdict. The whole value of the skill is that the user can trust a PASS. Everything after the dash is written in the user's language; the PASS / NOT YET keywords stay English.

What ships with it

Read from the repository

Just SKILL.md. No reference files, no scripts.

Gives 1 of the 12 instructions most study practice skills give in ~1.0k tokens

Counted across 85 of the 97 authors here whose files we hold, read 2026-09-06

  • Ask one question at a timein 17 of 85
  • Give immediate feedback after each answerin 7 of 85
  • Write five to eight quiz questionshere, and in 6 of 85
  • Ask one question per messagein 4 of 85
  • Wait for each answer before continuingin 4 of 85
  • Wait for the user's answer before feedbackin 4 of 85
  • Present multiple-choice via AskUserQuestion with exactly four optionsin 4 of 85
  • Treat pass as merge-readyin 2 of 85
  • Present one word at a timein 2 of 85
  • Verify a story project exists before startingin 2 of 85, across 1 file
  • Clarify the revision pass type firstin 2 of 85, across 1 file
  • Read chapter and continuity context before editingin 2 of 85, across 1 file

Said here and by no other author read

  • Scope the change beyond the diff
  • Cover pre-existing code paths the change relies on
  • Write report and quiz in the user's language
  • Keep PASS and NOT YET keywords in English
  • Write the report to a file
  • Default the report to Markdown

Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.

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