agentleFS
ZhouYinLong-labZhouYinLong-lab/Dog-Skills/vercel-labs-skills/AGENTS.md

Dog-Skills / vercel-labs-skills

AGENTS.md7 starsChanged 5 months agoMITView on GitHub

This file provides guidance to AI coding agents working on the skills CLI codebase. skills is the CLI for the open agent skills ecosystem. Aliases: skills a works for add. skills i, skills install (no args) restore from skills-lock.json. skills ls works for list. skills experimental_install restores from skills-lock.json. skills experimental_sync crawls node_modules for skills.

  • Reads credentials
  • Installs packages

The file

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

5 rules. About 0 are common, 1 is distinctive, and 4 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈1

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 4

    Very specific

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

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

    Read ~/.agents/.skill-lock.json for installed skills

    line 85
  2. Distinctive:

    If reading an older lock file version, it's wiped.

    line 96
  3. Very specific:

    Add the agent definition to src/agents.ts

    line 170
  4. Very specific:

    Run pnpm run -C scripts validate-agents.ts to validate

    line 171
  5. Very specific:

    Run pnpm run -C scripts sync-agents.ts to update README.md and package keywords

    line 172

≈ “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

This file provides guidance to AI coding agents working on the skills CLI codebase.

Project Overview

skills is the CLI for the open agent skills ecosystem.

Commands

CommandDescription
skillsShow banner with available commands
skills add <pkg>Install skills from git repos, URLs, or local paths
skills use <pkg>@<skill>Use one skill without installing
skills experimental_installRestore skills from skills-lock.json
skills experimental_syncSync skills from node_modules into agent dirs
skills listList installed skills (alias: ls)
skills update [skills...]Update skills to latest versions
skills init [name]Create a new SKILL.md template

Aliases: skills a works for add. skills i, skills install (no args) restore from skills-lock.json. skills ls works for list. skills experimental_install restores from skills-lock.json. skills experimental_sync crawls node_modules for skills.

Architecture

src/
├── cli.ts           # Main entry point, command routing, init/check/update
├── cli.test.ts      # CLI tests
├── add.ts           # Core add command logic
├── add-prompt.test.ts # Add prompt behavior tests
├── add.test.ts      # Add command tests
├── constants.ts      # Shared constants
├── find.ts           # Find/search command
├── list.ts          # List installed skills command
├── list.test.ts     # List command tests
├── remove.ts         # Remove command implementation
├── remove.test.ts    # Remove command tests
├── agents.ts        # Agent definitions and detection
├── installer.ts     # Skill installation logic (symlink/copy) + listInstalledSkills
├── skills.ts        # Skill discovery and parsing
├── skill-lock.ts    # Global lock file management (~/.agents/.skill-lock.json)
├── local-lock.ts    # Local lock file management (skills-lock.json, checked in)
├── sync.ts          # Sync command - crawl node_modules for skills
├── source-parser.ts # Parse git URLs, GitHub shorthand, local paths
├── git.ts           # Git clone operations
├── telemetry.ts     # Anonymous usage tracking
├── types.ts         # TypeScript types
├── mintlify.ts      # Mintlify skill fetching (legacy)
├── plugin-manifest.ts # Plugin manifest discovery support
├── prompts/         # Interactive prompt helpers
│   └── search-multiselect.ts
├── providers/       # Remote skill providers (GitHub, HuggingFace, Mintlify)
│   ├── index.ts
│   ├── registry.ts
│   ├── types.ts
│   ├── huggingface.ts
│   ├── mintlify.ts
│   └── wellknown.ts
├── init.test.ts     # Init command tests
├── use.ts           # Use command - generate a skill prompt or launch an agent
├── use.test.ts      # Use command tests
└── test-utils.ts    # Test utilities

tests/
├── cross-platform-paths.test.ts # Path normalization across platforms
├── full-depth-discovery.test.ts # --full-depth skill discovery tests
├── openclaw-paths.test.ts       # OpenClaw-specific path tests
├── plugin-manifest-discovery.test.ts # Plugin manifest skill discovery
├── sanitize-name.test.ts     # Tests for sanitizeName (path traversal prevention)
├── skill-matching.test.ts    # Tests for filterSkills (multi-word skill name matching)
├── source-parser.test.ts     # Tests for URL/path parsing
├── installer-symlink.test.ts # Tests for symlink installation
├── list-installed.test.ts    # Tests for listing installed skills
├── skill-path.test.ts        # Tests for skill path handling
├── wellknown-provider.test.ts # Tests for well-known provider
├── xdg-config-paths.test.ts   # XDG global path handling tests
└── dist.test.ts               # Tests for built distribution

Update Checking System

How skills check and skills update Work

  1. Read ~/.agents/.skill-lock.json for installed skills
  2. Filter to GitHub-backed skills that have both skillFolderHash and skillPath
  3. For each skill, call fetchSkillFolderHash(source, skillPath, token). Optional auth token is sourced from GITHUB_TOKEN, GH_TOKEN, or gh auth token to improve rate limits.
  4. fetchSkillFolderHash calls GitHub Trees API directly (/git/trees/<branch>?recursive=1 for main, then master fallback)
  5. Compare latest folder tree SHA with lock file skillFolderHash; mismatch means update available
  6. skills update reinstalls changed skills by invoking the current CLI entrypoint directly (node <repo>/bin/cli.mjs add <source-tree-url> -g -y) to avoid nested npm exec/npx behavior

Lock File Compatibility

The lock file format is v3. Key field: skillFolderHash (GitHub tree SHA for the skill folder).

If reading an older lock file version, it's wiped. Users must reinstall skills to populate the new format.

Key Integration Points

FeatureImplementation
skills addsrc/add.ts - full implementation
skills experimental_syncsrc/sync.ts - crawl node_modules
skills checksrc/cli.ts + fetchSkillFolderHash in src/skill-lock.ts
skills updatesrc/cli.ts direct hash compare + reinstall via skills add

Development

# Install dependencies
pnpm install

# Build
pnpm build

# Test locally
pnpm dev add vercel-labs/agent-skills --list
pnpm dev experimental_sync
pnpm dev check
pnpm dev update
pnpm dev init my-skill

# Run all tests
pnpm test

# Run specific test file(s)
pnpm test tests/sanitize-name.test.ts
pnpm test tests/skill-matching.test.ts tests/source-parser.test.ts

# Type check
pnpm type-check

# Format code
pnpm format

# Check formatting
pnpm format:check

# Validate and sync agent metadata/docs
pnpm run -C scripts validate-agents.ts
pnpm run -C scripts sync-agents.ts

Code Style

This project uses Prettier for code formatting. Always run pnpm format before committing changes to ensure consistent formatting.

# Format all files
pnpm format

# Check formatting without fixing
pnpm format:check

CI will fail if code is not properly formatted.

Publishing

# 1. Bump version in package.json
# 2. Build
pnpm build
# 3. Publish
npm publish

Adding a New Agent

  1. Add the agent definition to src/agents.ts
  2. Run pnpm run -C scripts validate-agents.ts to validate
  3. Run pnpm run -C scripts sync-agents.ts to update README.md and package keywords

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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.