quiz · takagoto — Claude Code skill: what it does, how to install
Generates interactive RAG quizzes with question-by-question scoring. Identifies knowledge gaps before you build retrieval pipelines.
npx skills add TakaGoto/rag-learning-academy --skill quiz -a claude-codeWhat quiz does
This skill generates a 5 to 10 question quiz on a selected RAG topic or checks progress/module-tracker.md for the latest completed lesson. Questions fall into four categories: conceptual reasoning, code reading, scenario analysis, and true-or-false statements that require an explanation.
Questions appear one at a time. The agent waits for your response, marks it, clarifies any misconceptions, and proceeds to the next prompt. When the quiz ends, total scores and identified gaps are appended to progress/quiz-results.md. If no tracking file exists yet, the skill redirects you to /start or /lesson.
What it helps with
- test understanding of RAG mechanics before implementation
- pinpoint gaps in chunking or retrieval strategies
- log assessment scores into
progress/quiz-results.md - receive follow-up command suggestions based on test results
Example prompts for the agent
- /quiz chunking
- Test my understanding of RAG retrieval strategies
- /quiz
How to install quiz
1Skills CLI (Vercel)
npx skills add TakaGoto/rag-learning-academy --skill quiz -a claude-code2Manually: put the files in place
~/.claude/skills/quiz/SKILL.mdCopy the whole skill folder; for one project use .claude/skills/quiz/
1Skills CLI (Vercel)
npx skills add TakaGoto/rag-learning-academy --skill quiz -a codex2Manually: put the files in place
.agents/skills/quiz/SKILL.mdFor all projects use ~/.agents/skills/
1Skills CLI (Vercel)
npx skills add TakaGoto/rag-learning-academy --skill quiz -a cursor2Manually: put the files in place
.cursor/skills/quiz/SKILL.mdCursor also reads .agents/skills/ and .claude/skills/
1GitHub CLI
gh skill install TakaGoto/rag-learning-academy quiz2Manually: put the files in place
.github/skills/quiz/SKILL.md1Skills CLI (Vercel)
npx skills add TakaGoto/rag-learning-academy --skill quiz -a gemini-cli2Platform CLI
gemini skills install https://github.com/TakaGoto/rag-learning-academy --path .claude/skills/quizManually: put the files in place
.devin/skills/quiz/SKILL.mdThe legacy .windsurf/skills/ path still works
Skills CLI (Vercel)
npx skills add TakaGoto/rag-learning-academy --skill quiz -a opencodeClaude.ai
Zip the folder and upload it in Settings → Capabilities → Skills
Step by step, with commands for each platform: How to install skills in Claude Code: five ways
Questions about quiz
How to install quiz in Claude Code?
Run npx skills add TakaGoto/rag-learning-academy --skill quiz -a claude-code.
What does the quiz skill do?
It administers a 5 to 10 question assessment on RAG topics, evaluates answers individually, and writes results to progress/quiz-results.md.
What happens if quiz runs without a specified topic?
It inspects progress/module-tracker.md for your most recent lesson. If no tracker file is present, it prompts you to run /start or /lesson first.
Source text
SKILL.md · MIT
--- name: quiz description: "Test your understanding of a RAG concept" --- # Quiz: Test Your RAG Knowledge > **Scope:** This skill **tests your understanding** with questions and scoring. For guided teaching of new concepts, use `/lesson`. Generate and administer a quiz on a specific RAG topic to help learners assess their understanding. Quizzes reinforce learning and surface gaps. ## Step 1: Determine the Topic - If the user specifies a topic (e.g., `/quiz chunking`), use that topic. - If no topic is given, read `progress/module-tracker.md` to find the most recently completed lesson and quiz on that. - If no progress exists, suggest running `/start` or `/lesson` first. ## Step 2: Generate Questions Create 5-10 questions that mix the following types: ### Conceptual Questions (2-3) Test understanding of "why" and "how" things work. Example: "Why might fixed-size chunking lose important context at chunk boundaries?" ### Code Reading Questions (2-3) Show a code snippet and ask what it does, what is wrong with it, or what the output would be. Example: Show a retrieval function and ask why it might return irrelevant results. ### Scenario-Based Questions (2-3) Present a real-world situation and ask the learner to choose the best approach. Example: "You have a corpus of legal contracts averaging 50 pages each. Which chunking strategy would you start with and why?" ### True/False with Justification (1-2) A statement the learner must evaluate and explain. Example: "Larger chunk sizes always improve retrieval quality. True or false? Explain." ## Step 3: Administer the Quiz Present questions one at a time. Wait for the learner's answer before moving to the next question. Do not reveal the correct answer until the learner has responded. For each question: 1. Present the question clearly 2. Wait for the learner's response 3. Evaluate the response — is it correct, partially correct, or incorrect? 4. Provide the correct answer with a clear explanation 5. If incorrect, explain the misconception and link it back to the relevant concept ## Step 4: Score and Review After all questions are answered, present a summary: ``` Quiz Results: [Topic] Score: [X]/[Total] ([percentage]%) --- Strengths: [areas where the learner did well] Gaps: [areas that need review] Recommendation: [what to study next] ``` ## Step 5: Track Results Save the quiz results to `progress/quiz-results.md` with the date, topic, score, and any identified gaps. Append to the file if it already exists. ## Step 6: Suggest Next Steps Based on the score, suggest 2-3 relevant next steps using slash commands: - **90-100%**: Congratulate them. - `/challenge` — put your mastery to the test with a real-world challenge - `/build` — apply your knowledge by building a hands-on component - `/lesson` — continue to the next lesson in your track - **70-89%**: Good progress. Recommend reviewing the specific gaps. - `/build` — reinforce your understanding by building what you just learned - `/lesson` — continue to the next lesson or revisit a weak area - `/explain` — get a deeper explanation of any concepts that felt shaky - **Below 70%**: Encourage them. - `/lesson` — revisit the lesson to strengthen your foundations - `/explain` — get a deep-dive explanation on the weak areas - `/glossary` — review key terms you may have missed ## Guidelines - Questions should be practical and relevant, not trivia - Accept reasonable alternative answers — RAG is a field with multiple valid approaches - When answers are wrong, be straightforward: explain what's actually going on without sugarcoating. "Not quite — here's the thing" beats "Great try! You're on the right track!" - Vary difficulty within the quiz (start easier, build up)
© TakaGoto · MIT · TakaGoto/rag-learning-academy
Similar skills
All skills for AI and ML →quiz by other authors comes first.