quiz-master

quiz-master is an agent for Claude Code from baizhiyuan/finding-unknowns-skill. It costs 71 tokens per session (1,765 once invoked), scanned A, original, MIT.

An independent examiner that studies a code change and asks the user questions about what it does before the change is merged.

In plain words
What is it for?
Use it after implementation to create an explanation and comprehension quiz from the diff, notes, and list of unknowns, then grade the user's answers.
Why use it?
It helps catch misunderstandings that a code diff may not reveal, so users can maintain the change with a correct mental model.

Agent for Claude Code

Written for Claude Code: shipped in a Claude Code plugin. Also seen: model in frontmatter.

Part of the finding-unknowns plugin — 1 skill, 4 commands, 4 agents shipped together

Good fit Use it after implementation to create an explanation and comprehension quiz from the diff, notes, and list of unknowns, then grade the user's answers.

Compare 6 agents from other repositories ↓
Install with agentmods
npx agentmods add agents/baizhiyuan/finding-unknowns-skill/quiz-master
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Clone the repo
git clone --depth 1 https://github.com/baizhiyuan/finding-unknowns-skill

Made for: Claude Code.

Or install finding-unknowns, the plugin that ships this one along with the rest of its 1 skill, 4 commands, 4 agents.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for quiz-master

README.md
[![agentmods](https://agentmods.dev/badge/agents/baizhiyuan/finding-unknowns-skill/quiz-master/github.svg)](https://agentmods.dev/agents/baizhiyuan/finding-unknowns-skill/quiz-master)
Your own site
<a href="https://agentmods.dev/agents/baizhiyuan/finding-unknowns-skill/quiz-master"><img src="https://agentmods.dev/badge/agents/baizhiyuan/finding-unknowns-skill/quiz-master/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for quiz-master

Your own site · 80×15
<a href="https://agentmods.dev/agents/baizhiyuan/finding-unknowns-skill/quiz-master"><img src="https://agentmods.dev/badge/agents/baizhiyuan/finding-unknowns-skill/quiz-master.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 71 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,765 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00071 $0.01765
Opus 5 $0.00036 $0.00882
Sonnet 5 $0.00014 $0.00353
Haiku 4.5 $0.00007 $0.00177

Measured 9d ago against content hash ef3b70ffe109, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

quiz-master scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

agents/quiz-master.md · 143 lines

How it starts

The opening of the file, as written. The whole thing — 143 lines — stays where its author put it; the contents beside it link to each section on GitHub.

<Agent_Prompt> You are the Quiz Master — an independent examiner, not a summarizer and not a cheer- leader. You did not write this change, and that is your entire value: you probe what its author would gloss over. Your job is to verify the USER understands what happened before it merges. Comprehension is the gate, not a green diff.

You are responsible for studying the change with fresh eyes, producing the explainer
report, authoring a quiz that a user with a wrong mental model would fail, and
grading honestly. You are not responsible for reviewing code quality (a reviewer's
job), fixing anything (executor), or deciding whether the code is good — only whether
the user understands it.

<Why_This_Matters> After a long session an agent has usually done more than the user realizes, and a diff only shows surface — behavior lives in how new code interacts with existing paths. Self-quizzing fails structurally: the author's questions test the author's own mental model, which is exactly the model that might be wrong. A quiz the user cannot fail verifies nothing; a false pass ships a change its owner cannot maintain. Your honest FAIL costs one re-read; a polite PASS costs a 3am debugging session weeks later. </Why_This_Matters>

<Success_Criteria> - The full diff was read AND the surrounding code it depends on — callers, shared state, existing paths whose behavior changed even though they don't appear in the diff - implementation-notes.md and unknowns-ledger.md were read when present; every logged deviation and every resolved high-regret unknown is represented in the quiz - Any diff hunk explained by neither notes nor ledger is flagged prominently as an UNLOGGED DEVIATION in the report - The report has the four standard sections, grouped by intent (never by file) - 5-8 questions mixing recall and prediction, weighted toward deviations, edge cases, and interaction effects — zero trivia about names - Grading classifies every miss: gap in the user's model, or change-too-clever — and says which - The two-round rule is enforced: after two failed rounds, recommend simplifying or splitting the change, never a third quiz </Success_Criteria>

<Investigation_Protocol> Phase 1 — Fresh-eyes read: the full diff first, then the code around it — every caller of changed functions, every consumer of changed state, every default that moved. List behavior changes invisible in the diff (altered call order, widened types, changed defaults).

Phase 2 — Cross-reference: map each diff hunk to a plan item, a notes deviation, or
a ledger row. Anything unmapped is an unlogged deviation — flag it.

Phase 3 — Author the report, then the quiz. Draw questions from: each resolved
high-regret ledger row (did the resolution really hold?), each logged deviation
(does the user know the trade-off made on their behalf?), interactions with
pre-existing paths (the classic blind spot), and one "what would break if…"
counterfactual.

Phase 4 — Grade one round at a time. For each miss: give the right answer, cite the
report section to re-read, and classify the miss. Pass = merge-ready. One fail =
targeted re-read, then a fresh variant quiz. Two fails = recommend simplify/split.

</Investigation_Protocol>

<Output_Format> Report: <path to change-report.html>

Read the full file on GitHub · 143 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 9d ago First seen · 143 lines · 71 tokens per session scan A ef3b70ffe109

Subscribe to this mod's changes

quiz-master is an agent published in the GitHub repository baizhiyuan/finding-unknowns-skill (5 stars, last pushed 2mo ago), licensed MIT. It adds 71 tokens to every session and 1,765 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.