Borrowing it
Nothing to install: this file belongs to TakaGoto/rag-learning-academy. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/TakaGoto/rag-learning-academy/main/.claude/skills/challenge/SKILL.mdgit clone --depth 1 https://github.com/TakaGoto/rag-learning-academyWrote 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/takagoto/rag-learning-academy/challenge)<a href="https://agentmods.dev/skills/takagoto/rag-learning-academy/challenge"><img src="https://agentmods.dev/badge/skills/takagoto/rag-learning-academy/challenge/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.
<a href="https://agentmods.dev/skills/takagoto/rag-learning-academy/challenge"><img src="https://agentmods.dev/badge/skills/takagoto/rag-learning-academy/challenge.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00010 | $0.01133 |
| Opus 5 | $0.00005 | $0.00566 |
| Sonnet 5 | $0.00002 | $0.00227 |
| Haiku 4.5 | $0.00001 | $0.00113 |
Grade A, and why
challenge 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.
How it starts
The opening of the file, as written. The whole thing — 105 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Challenge: Real-World RAG Challenges
Scope: This skill presents open-ended, multi-component challenges that require design decisions. For step-by-step guided construction of individual components, use
/build.
Present the learner with a realistic RAG challenge that tests their skills across multiple components. Challenges are more open-ended than /build exercises — they require design decisions, not just implementation.
Language awareness: See
.claude/LANGUAGE_AWARENESS.md.
Step 1: Select a Challenge
If the user specifies a difficulty or topic (e.g., /challenge advanced or /challenge multilingual), filter accordingly. Otherwise, recommend a challenge based on their progress.
Beginner Challenges
- FAQ Bot: Build a RAG system that answers questions from a FAQ document (provided). Must handle exact and paraphrased questions.
- Recipe Finder: Index a collection of recipes and build a retriever that finds recipes by ingredients, cuisine, or dietary restrictions.
- Book Q&A: Load a public-domain book, chunk it, and build a system that can answer questions about characters, plot, and themes.
Intermediate Challenges
- Multi-Document Synthesis: Build a RAG system that can answer questions requiring information from multiple documents. Test with a set of related articles.
- Conversational RAG: Add conversation history to a RAG pipeline so follow-up questions work correctly (e.g., "What about the second one?").
- Metadata-Filtered Search: Build a RAG system for product documentation where users can filter by product version, category, and date.
- Citation Generator: Build a RAG system that not only answers questions but provides exact source citations with page/paragraph references.
Advanced Challenges
- Multilingual RAG: Build a system that handles documents in multiple languages and queries in any of those languages.
- Legal Document Analyst: Build a RAG system for legal contracts that can answer questions about specific clauses, compare terms across contracts, and flag potential issues.
- Code Documentation Assistant: Build a RAG system over a codebase that can answer questions about architecture, find relevant functions, and explain code patterns.
- Real-Time RAG: Build a system that handles a continuously updating corpus (e.g., news articles) with minimal re-indexing latency.
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.
- 9d ago First seen · 105 lines · 10 tokens per session scan A bd32ee01eddc
challenge is a skill published in the GitHub repository TakaGoto/rag-learning-academy (18 stars, last pushed 5mo ago), licensed MIT. It adds 10 tokens to every session and 1,133 once invoked, about $0.0001 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 2026-08-30.
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