agentleFS
a-tokyoa-tokyo/agent-skills/AGENTS.md

agent-skills

AGENTS.md18 starsChanged 4 months agoMITView on GitHub

Contributor and agent contract for agent-skills. Follows the agents.md format. For the user-facing skill catalogue, see README.md. A monorepo of reusable agent skills (a SKILL.md plus optional references) for AI coding assistants, installed via npx skills and compatible with Cursor, Claude Code, Codex, and 40+ agents. Each skill is self-contained and ships on its own. There is no application to build or server to run — the "product" is the skill files; the "tests" are benchmarks. The closest AGENTS.md wins;…

  • Reads credentials

The file

We split this AGENTS.md into the rules it gives an agent

3 rules. About 0 are common, 2 are distinctive, and 1 is very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈2

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 1

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Very specific:

    Before pushing: run the limit check (above) and the relevant skill's benchmark if you changed a SKILL.md.

    line 82
  2. Distinctive:

    Keep diffs surgical — one concern per PR.

    line 84
  3. Distinctive:

    Commit subject in imperative mood.

    line 90

≈ “Common” is an estimate: at least 1 in 5 of the 40,246 AGENTS.md files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
AGENTS.md

AGENTS.md

Contributor and agent contract for agent-skills. Follows the agents.md format. For the user-facing skill catalogue, see README.md.

Project Overview

A monorepo of reusable agent skills (a SKILL.md plus optional references) for AI coding assistants, installed via npx skills and compatible with Cursor, Claude Code, Codex, and 40+ agents. Each skill is self-contained and ships on its own. There is no application to build or server to run — the "product" is the skill files; the "tests" are benchmarks.

Repo structure (monorepo)

skills/<name>/                     a shippable skill: SKILL.md (+ optional references/, README.md)
benchmarks/<name>/                 benchmark for that skill — OUTSIDE skills/ so it doesn't ship on install
docs/                              contributor guides (this contract links into them)
.claude-plugin/marketplace.json    Claude Code plugin marketplace — one entry per skill in skills/
README.md                          user-facing skill catalogue + install

The closest AGENTS.md wins; this root file governs the whole repo.

Setup & commands

# install / use a skill (consumer side)
npx skills add a-tokyo/agent-skills                      # all skills
npx skills add a-tokyo/agent-skills --skill production-grade

# check every skill against the platform limits (run from repo root)
wc -l skills/*/SKILL.md                                  # whole-file lines (guideline: keep body < 500; this count includes frontmatter)
# full name + description check (handles folded YAML): see docs/skill-authoring.md

# run a skill's benchmark (from inside the repo)
cd benchmarks/<name> && cat README.md                    # method + reproduce steps

There is no root package.json; benchmarks carry their own toolchain (Node + uv/promptfoo).

Code Style — skill authoring

Full rules and the compliance check: docs/skill-authoring.md. The source of truth is Anthropic's best-practices and API guides — the table below is a mirror, confirm at the guide.

WhatLimit
SKILL.md body< 500 lines
name≤ 64 chars, [a-z0-9-], no XML tags, no reserved words (anthropic, claude)
description≤ 1024 chars, non-empty, third person, what + when
Skill upload (all files)≤ 30 MB

Beyond Anthropic's required name/description, every skill in this repo also carries version (semver) and license (MIT) in frontmatter — bump version when behaviour changes.

Plus: progressive disclosure (split into references/ before the body nears 500 lines), references one level deep from SKILL.md, a ## Contents TOC on any reference > 100 lines, fully-qualified MCP names (ServerName:tool_name), forward-slash paths, provide-a-default over a menu, and no time-sensitive wording. Naming is descriptive kebab-case (production-grade); consistency with the existing set beats the gerund default.

Testing — benchmarking

A new or materially changed skill ships a self-contained benchmark in benchmarks/<name>/. The standard is same-model uplift: the same model run with the skill vs. bare, on identical tasks, scored by executing the output. Full method and reproduce steps: docs/benchmarking.md.

Security

A skill that directs the agent to fetch third-party content (docs, web pages, MCP issue/ticket bodies, other repositories) must frame that content as untrusted data, not instructions — the indirect-prompt-injection posture. skills/production-grade/SKILL.md (rule M2) is the reference implementation. Never commit secrets; .env is git-ignored.

PR Guidelines

  • Branch off main; never commit directly to main.
  • Before pushing: run the limit check (above) and the relevant skill's benchmark if you changed a SKILL.md.
  • Keep diffs surgical — one concern per PR; a rename ships separately from a feature.
  • Bump the skill's version in its frontmatter when its behaviour changes.
  • A new skill needs an entry in both the README table and .claude-plugin/marketplace.json (source: "./", skills: ["./skills/<name>"], strict: false). When you bump a skill's version, update that same skill's entry in marketplace.json to match — the two are independent fields Claude Code doesn't sync automatically.
  • Commit subject in imperative mood; explain why in the body.

Download now (ZIP)

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People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.