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.
npx agentmods add skills/pranitmohnot/repo-learner-suite/code-quiznpx skills add PranitMohnot/repo-learner-suite --skill code-quizgit clone --depth 1 https://github.com/PranitMohnot/repo-learner-suiteWrote 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.
[](https://agentmods.dev/skills/pranitmohnot/repo-learner-suite/code-quiz)<a href="https://agentmods.dev/skills/pranitmohnot/repo-learner-suite/code-quiz"><img src="https://agentmods.dev/badge/skills/pranitmohnot/repo-learner-suite/code-quiz.svg" alt="Measured on agentmods" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00088 | $0.01147 |
| Opus 5 | $0.00044 | $0.00574 |
| Sonnet 5 | $0.00018 | $0.00229 |
| Haiku 4.5 | $0.00009 | $0.00115 |
Grade A, and why
code-quiz 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 6d 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.
How it starts
The opening of the file, as written. The whole thing — 114 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Code Quiz
Adaptive quiz on a curriculum section. Pulls from
learn/internals/quiz-bank.md; generates fresh questions from source when
the bank is exhausted or the user has seen the existing ones.
The quiz bank is a working document. APPEND new questions when generated. EDIT existing questions or answers when the user gives a reasonable answer the "correct" answer doesn't cover. Treat the bank as a living resource that improves with each session.
Entering a session
- Resolve the section: explicit ID (
/learn quiz 1.3),--fullfor the whole curriculum, or default to the next unchecked section. - Load the section's questions from the bank, the section text from curriculum.md, and the source files it cites.
- Plan 5–7 questions for a single section, more for
--full.
Question palette (mix; do not name the types to the user)
Pull from several of these in any quiz. The user should experience a varied, well-crafted set — not a labeled taxonomy. Never say "this is a conceptual question" or announce the type; just ask.
Examples below span several libraries deliberately — the palette is domain-agnostic. Draw real questions from the codebase being quizzed.
- Recall — vocabulary. "What does
Session.execute()return in SQLAlchemy 2.x?" "What's the defaulttimeoutforhttpx.Client?" Fast confidence-builders. - Conceptual — mental model. "Why does pydantic validate at
construction time instead of on access?" "What invariant does
Session.begin()preserve about transaction state?" - Predictive — cause and effect. "If you drop
pool_sizefrom 5 to 1 under concurrent load, what changes?" "What happens on the first call to an@lru_cache'd function vs the second?" - Diagnostic — error model. Show plausibly broken code: "This pydantic
model raises
ValidationErroron construction. What's wrong?" - Applied — transfer. "You want to add request signing to every call
on an existing
httpx.AsyncClient. Sketch how." - Architectural — design intent. "Why does pandas split
mergeandjoininto two methods?" "Why does FastAPI use dependency injection for auth rather than middleware?"
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 6d ago First seen · 114 lines · 88 tokens per session scan A 5b78e5d1950b
code-quiz is a skill published in the GitHub repository PranitMohnot/repo-learner-suite (4 stars, last pushed 3mo ago), licensed MIT. It adds 88 tokens to every session and 1,147 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.
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