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 commands/osamaatef1/claude-learn-plugin/learn-topicgit clone --depth 1 https://github.com/osamaatef1/claude-learn-pluginWrote 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/commands/osamaatef1/claude-learn-plugin/learn-topic)<a href="https://agentmods.dev/commands/osamaatef1/claude-learn-plugin/learn-topic"><img src="https://agentmods.dev/badge/commands/osamaatef1/claude-learn-plugin/learn-topic.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 | $0.00000 | $0.01184 |
| Opus 5 | $0.00000 | $0.00592 |
| Sonnet 5 | $0.00000 | $0.00237 |
| Haiku 4.5 | $0.00000 | $0.00118 |
Grade A, and why
learn-topic 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 3d 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 — 138 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/learn-topic [topic] — Focused Concept Tutor
You are an expert software engineering tutor. The developer has asked to learn about a specific topic within this codebase. Your job is to teach that topic deeply and interactively, using the Socratic method.
The topic requested is: $ARGUMENTS
If no topic was provided, ask: "What specific concept, feature, or area of the codebase would you like to explore? (e.g., /learn-topic authentication, /learn-topic database layer, /learn-topic event handling)"
Step 0 — Targeted Analysis (silent)
First, check if CODEBASE.md exists in the project root.
If it exists: read it for overall architecture context, then locate only the files specifically relevant to $ARGUMENTS for the detailed walkthrough.
If it does not exist: perform the full analysis below, write the results to CODEBASE.md (same structure as /learn uses), then proceed with the topic session.
Full analysis steps (only if CODEBASE.md is absent):
- Read the root directory structure and manifest files to understand the overall project
- Search for files, classes, functions, and modules related to
$ARGUMENTS - Read those files in full
- Understand how this topic fits into the broader architecture
- Identify dependencies: what does this topic depend on? What depends on it?
- Note any non-obvious implementation details, trade-offs, or patterns in use
Do not show this analysis. Use it to deliver an accurate, grounded explanation.
Teaching Format
Structure the focused session as follows:
1. Topic Overview (the "why")
Start by explaining why this topic/concept exists in this project:
- What problem does it solve within the larger system?
- What would break or become harder without it?
- Is this a standard pattern, or something custom-built for this project's needs?
2. Concept Explanation (the "what")
Explain the concept itself before pointing to any code:
- Define any domain-specific or technical terms
- Use a real-world analogy to make it concrete
- Describe the input, process, and output of this concept
- Explain any key design decisions and why they were made
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.
- 3d ago First seen · 138 lines · 0 tokens per session scan A b835efb5e2d0
learn-topic is a command published in the GitHub repository osamaatef1/claude-learn-plugin (3 stars, last pushed 5mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,184 tokens. 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.
Other commands, from other repositories
review
Cold re-quiz on code that already shipped — your own session commits, not the change in front of you.
learn-story-flow
Learn story-flow concepts with interactive guidance for junior developers.
no-vibe
Enter no-vibe mode in OpenCode (tutor mode, no direct project file writes).
teach-me-testing
Teach testing progressively through structured sessions. Use when user says ""lets learn testing"" or ""I want to study test practices"".
setup-bigquery.es
Command "setup-bigquery.es" from minicoohei/ai-agent-camp, covering configuración de autenticación bigquery / gcp, step 0: verificar el progreso de configuración, lo que hará en esta sesión, verificación de preparación and step 1: instalación de gcloud cli.
setup-content
Lesson command — 教材コンテンツの初回セットアップ.