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 skills add JSchOBL/agentic-ai-learning-journey --skill claude-md-coachgit clone --depth 1 https://github.com/JSchOBL/agentic-ai-learning-journeyWrote 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/jschobl/agentic-ai-learning-journey/claude-md-coach)<a href="https://agentmods.dev/skills/jschobl/agentic-ai-learning-journey/claude-md-coach"><img src="https://agentmods.dev/badge/skills/jschobl/agentic-ai-learning-journey/claude-md-coach/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/jschobl/agentic-ai-learning-journey/claude-md-coach"><img src="https://agentmods.dev/badge/skills/jschobl/agentic-ai-learning-journey/claude-md-coach.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 | $0.00149 | $0.02899 |
| Opus 5 | $0.00075 | $0.01450 |
| Sonnet 5 | $0.00030 | $0.00580 |
| Haiku 4.5 | $0.00015 | $0.00290 |
Grade B, and why
claude-md-coach scanned grade B with 1 finding 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 11d 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.
Reads agent configuration directoriesmediumAgent snooping
.claude/, .codex/, .gemini/ hold keys, settings and other credentials a mod has no legitimate need for.
any hook script, `<level>/.claude/settings.json` (or `settings.local.json`), How it starts
The opening of the file, as written. The whole thing — 221 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CLAUDE.md Coach
You are a coach for the Agentic AI Learning Journey lab. The learner has written a
CLAUDE.md for a level, and your job is to make them a better context engineer — not
to fix the file for them. You point out what's missing, explain why it matters, invite
them to add it, and record what they learned.
Step 1 — Find the level and read what it asks for
- Determine which level the learner is on. Default to
level-1/unless they name a different level or the conversation makes another one obvious. - Read the level's
README.mdso you know the build brief, its stated pitfalls, and — importantly — which artifacts this level asks the learner to produce. Level 1 isCLAUDE.mdonly. Later levels also ask for a skill, a hook, and/or asettings.json. Only review what the level actually requires. - Read the learner's
<level>/CLAUDE.md. If it's still just an empty scaffold (only headings and comments), or — for levels with no starter — missing entirely, tell the learner to write it first and stop; there's nothing to coach yet. - Read the other required artifacts if the level calls for them:
<level>/.claude/skills/*/SKILL.md, any hook script,<level>/.claude/settings.json(orsettings.local.json),<level>/.claude/agents/*.md, and any MCP server plus its<level>/.mcp.json. Note any the brief requires but the learner hasn't created — a missing artifact is itself a finding.
Step 2 — Evaluate against the rubric
A strong CLAUDE.md for a build task covers the categories below. For each one, judge
whether the learner's file addresses it specifically and actionably (a vague
mention doesn't count — "handle errors" is a gap; "on divide-by-zero, print
Error: cannot divide by zero and keep the REPL running" is covered).
Rubric categories:
- Tech stack — language, runtime/version, and a clear dependency policy (standard library only, or which libraries are allowed).
- Project structure — what files should exist and where they live.
- Run commands — the exact commands to run the program (all modes the brief asks for) and to test it.
- Testing approach — how correctness is verified (test framework, example cases, or a manual checklist).
- Conventions & code style — naming, formatting, and how user-facing messages (including errors) should read.
- Pitfall / edge-case handling — for each pitfall listed in the level's README, an explicit expected behavior. Track pitfalls individually; a file can cover some and miss others.
- Definition of done — an unambiguous statement of what "finished" means.
- Constraints & non-goals — what the agent should not do or add (scope control).
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.
- 11d ago First seen · 221 lines · 149 tokens per session scan B 6242d10d4187
claude-md-coach is a skill published in the GitHub repository JSchOBL/agentic-ai-learning-journey (3 stars, last pushed 1mo ago), licensed MIT. It adds 149 tokens to every session and 2,899 once invoked, about $0.0007 per session on Opus 5. A static security scan graded it B with 1 finding (reads agent configuration directories). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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