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 Enterwell/agent-skills --skill generate-agents-mdgit clone --depth 1 https://github.com/Enterwell/agent-skillsWrote 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/enterwell/agent-skills/generate-agents-md)<a href="https://agentmods.dev/skills/enterwell/agent-skills/generate-agents-md"><img src="https://agentmods.dev/badge/skills/enterwell/agent-skills/generate-agents-md/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/enterwell/agent-skills/generate-agents-md"><img src="https://agentmods.dev/badge/skills/enterwell/agent-skills/generate-agents-md.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 | $0.00041 | $0.03003 |
| Opus 5 | $0.00020 | $0.01502 |
| Sonnet 5 | $0.00008 | $0.00601 |
| Haiku 4.5 | $0.00004 | $0.00300 |
Grade A, and why
generate-agents-md 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 8d 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 — 406 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill: Generate a Project-Specific AGENTS.md
Purpose
Use this skill to create or improve a root-level AGENTS.md file for a software project. The file should help future AI coding agents understand how to work safely and effectively in the repository.
AGENTS.md is not a replacement for README.md. It should contain concise, durable, repo-specific instructions for agents: how to set up the project, run tests, understand the structure, follow conventions, and avoid risky changes.
When to use this skill
Use this skill when the user asks to:
- Create an
AGENTS.mdfile. - Improve or audit an existing
AGENTS.mdfile. - Generate AI-agent instructions for a repository.
- Convert repo setup, testing, and contribution knowledge into agent-facing documentation.
- Prepare a project for local AI coding agents such as Codex, Claude Code, Cursor agents, or similar tools.
Inputs
Expected inputs may include:
- Access to the project repository.
- Existing
README.md, docs, or contribution guides. - Package manager files.
- Build, test, lint, formatter, framework, Docker, and CI configuration files.
- Source and test directory structure.
- Existing agent instruction files such as
AGENTS.md,CLAUDE.md,.cursorrules, Cursor rules, Copilot instructions, or similar.
If running inside the project, inspect the repository directly. If the repository is not available, ask the user for the relevant files or produce a template clearly marked as needing verification.
Core principles
- Do not invent facts.
- Prefer exact commands over vague descriptions.
- Keep instructions practical and repo-specific.
- Avoid duplicating the README unless the information is useful for coding agents.
- Mark uncertain items as
Verify:rather than guessing. - Do not include secrets, tokens, credentials, or sensitive internal values.
- Keep the document concise, usually under about 150 lines.
- Preserve useful existing instructions, but remove outdated or speculative content.
- Align the final checklist with CI whenever CI configuration exists.
- Document safety boundaries around generated files, migrations, destructive commands, external services, and production data.
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.
- 8d ago First seen · 406 lines · 41 tokens per session scan A 6cdd21a8e9a1
generate-agents-md is a skill published in the GitHub repository Enterwell/agent-skills (2 stars, last pushed 3mo ago), licensed MIT. It adds 41 tokens to every session and 3,003 once invoked, about $0.0002 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 2026-08-31.
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