Agent Skills

Use when creating or updating AGENTS.md files, .github/copilot-instructions.md, or other AI agent rule files, onboarding AI agents to a project, standardizing agent documentation, or when anyone mentions AGENTS.md, agent rules, project onboarding, or codebase documentation for AI agents.

Install

npx skills add https://github.com/netresearch/agent-rules-skill --skill agent-rules
SKILL.md

AGENTS.md Generator Skill

Generate and maintain AGENTS.md files following the agents.md convention. AGENTS.md is FOR AGENTS, not humans.

When to Use

  • Creating or updating AGENTS.md for new/existing projects
  • Scaffolding a new repository — ship AGENTS.md with the initial commits; retrofitting later needs full re-verification
  • Standardizing agent documentation across repositories
  • Checking AGENTS.md freshness after code changes
  • Onboarding AI agents to an unfamiliar codebase

Scripts

Call every script by its full path: bash ${CLAUDE_SKILL_DIR}/scripts/<name> PATH. Calling one relative to the working directory is not covered by the frontmatter rule and raises a permission prompt per call.

Script Purpose
generate-agents.sh PATH Generate AGENTS.md files
validate-structure.sh PATH Validate structure compliance
check-freshness.sh PATH Check if files are outdated
verify-content.sh PATH Verify documented files/commands match codebase
verify-commands.sh PATH Verify documented commands execute
score-agents.sh PATH Grade AGENTS.md quality, worst-first
detect-project.sh PATH Detect language, version, build tools
detect-scopes.sh PATH Identify directories needing scoped files
extract-commands.sh PATH Extract commands from build configs
extract-ci-rules.sh PATH Extract CI quality gates and version matrix
extract-architecture-rules.sh PATH Extract module boundaries
extract-adrs.sh PATH Extract architectural decision records
extract-github-rulesets.sh PATH Extract GitHub rulesets and merge rules

See references/scripts-guide.md for full options.

Workflow

  1. Detect: detect-project.sh + detect-scopes.sh — stacks and subsystems
  2. Extract: extract-commands.sh, extract-ci-rules.sh — gather facts
  3. Generate: generate-agents.sh --style=thin (default) or --verbose
  4. Verify: verify-content.sh + verify-commands.sh -- MANDATORY before done

--update preserves curated content outside <!-- GENERATED --> markers.

Core Principles

  • Structured over Prose -- tables parse faster than paragraphs
  • Never Fabricate -- only document what exists; verify every command and path
  • Pointer Principle -- point to files, don't duplicate content
  • Auto Symlinks -- CLAUDE.md/GEMINI.md by default (ai-tool-compatibility.md)

References

File Contents
verification-guide.md Verification steps, anti-bloat, preservation check
fleet-sync-sweep.md Fleet-wide AGENTS.md sweeps
scripts-guide.md Script options, validation checklist
quality-rubric.md Grading rubric
ai-tool-compatibility.md 16-agent compatibility matrix
output-structure.md Root/scoped sections
git-hooks-setup.md Hook framework setup
examples/ Complete examples
ai-contribution-guidelines.md "3 Cs" AI-contribution framework
directory-coverage.md Scoped-file coverage rationale
feedback-memory-schema.md Approved-learning file format

Templates

Root: assets/root-thin.md (default) or root-verbose.md. Scoped: assets/scoped/, one per stack (Go/PHP/Python/TYPO3/Symfony/Oro/CLI/TS/skill-repo).

Supported Projects

Go, PHP (Composer/Laravel/Symfony/TYPO3/Oro), TypeScript (React/Next/Vue/Node), Python (pip/poetry/ruff/mypy), skill repos, hybrid.

See Also

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