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/lesson/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/lesson)<a href="https://agentmods.dev/skills/takagoto/rag-learning-academy/lesson"><img src="https://agentmods.dev/badge/skills/takagoto/rag-learning-academy/lesson/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/lesson"><img src="https://agentmods.dev/badge/skills/takagoto/rag-learning-academy/lesson.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 | $0.00008 | $0.01571 |
| Opus 5 | $0.00004 | $0.00785 |
| Sonnet 5 | $0.00002 | $0.00314 |
| Haiku 4.5 | $0.00001 | $0.00157 |
Grade A, and why
lesson 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 — 127 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Lesson: Learn a RAG Concept Step by Step
Scope: This skill teaches new concepts through structured lessons with explanations and exercises. To test what you already know, use
/quiz.
This skill delivers structured curriculum lessons. Each lesson follows a consistent flow that builds understanding through explanation, examples, and hands-on practice.
Language awareness: See
.claude/LANGUAGE_AWARENESS.md.
Step 1: Determine Which Lesson to Load
- If the user provides a module number and lesson name (e.g.,
/lesson 3 chunking-strategies), load that specific lesson. - If no argument is given, read
progress/learner-profile.mdandprogress/module-tracker.mdto find the next incomplete lesson in the learner's track. - If no profile exists, suggest running
/startfirst.
Resuming an incomplete lesson: If the next incomplete lesson is the same one the learner's module-tracker.md shows as their current lesson (i.e., they started it before but it's not marked complete), ask:
"Looks like you started [lesson name] last time but didn't finish. Want to pick up where you left off (I'll give you a quick recap and jump ahead), or start fresh?"
- If they want to resume: give a 2-3 sentence recap of the key points covered so far, then jump to the next undelivered section.
- If they want to start fresh: begin the lesson from the top as normal.
Step 2: Load Lesson Content
Look for the lesson content in .claude/docs/curriculum/. The curriculum is organized as flat module files:
module-01-foundations.md,module-02-document-processing.md, etc.- Each module file contains multiple lesson sections within it.
Load the module file (e.g., .claude/docs/curriculum/module-01-foundations.md) and navigate to the specific lesson section within it. If the module file exists, use it as the primary source. If it does not exist yet, generate the lesson content based on the module topic and RAG curriculum structure.
Pacing: Section-by-Section Delivery
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 · 127 lines · 8 tokens per session scan A 22982845db92
lesson is a skill published in the GitHub repository TakaGoto/rag-learning-academy (18 stars, last pushed 5mo ago), licensed MIT. It adds 8 tokens to every session and 1,571 once invoked, about $0.0000 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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