code-quiz

code-quiz is a skill for Claude Code, Codex from PranitMohnot/repo-learner-suite. It costs 88 tokens per session (1,147 once invoked), scanned A, original, MIT.

An adaptive coding quiz that asks one question at a time about a curriculum section and includes relevant code. It adjusts the questions to test what the learner understands.

In plain words
What is it for?
Use it to practise programming concepts, check your understanding, and receive an honest assessment of your answers.
Why use it?
It reveals gaps in understanding more clearly than simply rereading course material.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

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.

agentmods
npx agentmods add skills/pranitmohnot/repo-learner-suite/code-quiz
Any agent
npx skills add PranitMohnot/repo-learner-suite --skill code-quiz
Clone the repo
git clone --depth 1 https://github.com/PranitMohnot/repo-learner-suite

Made for: Claude Code, Codex.

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 code-quiz

README.md
[![agentmods](https://agentmods.dev/badge/skills/pranitmohnot/repo-learner-suite/code-quiz.svg)](https://agentmods.dev/skills/pranitmohnot/repo-learner-suite/code-quiz)
Your own site
<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>
Per session 88 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,147 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00088 $0.01147
Opus 5 $0.00044 $0.00574
Sonnet 5 $0.00018 $0.00229
Haiku 4.5 $0.00009 $0.00115

Measured 6d ago against content hash 5b78e5d1950b, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

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.

code-quiz/SKILL.md · 114 lines

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

  1. Resolve the section: explicit ID (/learn quiz 1.3), --full for the whole curriculum, or default to the next unchecked section.
  2. Load the section's questions from the bank, the section text from curriculum.md, and the source files it cites.
  3. 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 default timeout for httpx.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_size from 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 ValidationError on 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 merge and join into two methods?" "Why does FastAPI use dependency injection for auth rather than middleware?"

Read the full file on GitHub · 114 lines

Files

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.

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. 6d ago First seen · 114 lines · 88 tokens per session scan A 5b78e5d1950b

Subscribe to this mod's changes

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.

Related

Other skills, from other repositories

learning-codebases

Use when the user wants to learn, understand, study, map, onboard to, or walk through an unfamiliar codebase or software project, especially when explanations should suit a beginner with basic Python knowledge.

Eijnewgnaw/learning-codebases · 44 tokens

lov-hanzi-lens

Explain one Chinese character through verified pronunciation, Unicode and glyph structure, historical lexicography, classical usage, semantic relationships, and an evidence-led professional infographic. Use when the user asks "解释这个字", "这个字什么意思", "一图讲清这个汉字", "汉字字源信息图", "explain this Chinese character", or "Chinese…

lovstudio/skills · 82 tokens

lov-subtitle-freedom

Create learner-friendly English subtitles with level-aware glosses and optional spoiler-safe subtitle sidecars.

lovstudio/skills · 25 tokens

lov-thesis-polish

Polish and elevate MBA thesis / dissertation to national outstanding thesis quality (全国优秀论文). Performs comprehensive improvement: academic language, argument structure, logical rigor, innovation highlights, and formatting. Input: markdown thesis text. Output: polished full text. Also trigger when the user mentions…

lovstudio/skills · 90 tokens

learning-assistant

互动式主题学习助手,依赖知识库结构化学习任务并交互引导完成学习过程.

cafe3310/public-agent-skills · 26 tokens

reading-notes

Process a book or article into structured progressive summary notes saved to the resources folder. Use when the user has finished reading something and wants to capture structured notes — 'I just finished reading X', 'take notes on this book'. Do NOT use for: fetching and summarizing a URL now (use summarize)…

onebrain-ai/onebrain · 80 tokens