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Found 270 Skills
Audit all filename and naming conventions in the codebase against AGENTS.md standards and common patterns. Use when user asks to check naming conventions, audit filenames, find naming inconsistencies, or validate file naming patterns.
Use when the requested deliverable includes creating, reviewing, moving, splitting, or updating a repository AGENTS.md; produces scoped repo guidance. Do not trigger for standalone skills, prompts, non-AGENTS instruction files, READMEs, changelogs, or architecture docs.
Interactive workflow to generate a full-lifecycle AGENTS.md using semantic AST/LSP analysis and chained user interviews.
Project setup. Explore the codebase, ask about strategy and aims, write persistent context to AGENTS.md. Run when starting or when aims shift.
Scaffold and audit OSS documentation for open source projects. Use for "add OSS docs", "create README", "setup contributing", "add changelog", "prepare for open source", or "add AGENTS.md".
Set up hierarchical Intent Layer (AGENTS.md files) for codebases. Use when initializing a new project, adding context infrastructure to an existing repo, user asks to set up AGENTS.md, add intent layer, make agents understand the codebase, or scaffolding AI-friendly project documentation.
Best Practice Advisor for AGENTS.md / CLAUDE.md. It is used when users ask about the format, structure, and best practices of agents markdown, AGENTS.md, CLAUDE.md, Claude Code memory, and AI coding agent instruction files; it also supports reviewing, diagnosing, rewriting, optimizing, or creating agent instruction files such as AGENTS.md, CLAUDE.md, CLAUDE.local.md, and .claude/rules from scratch. It is not suitable for general README writing unless the goal is to provide project context for AI coding agents.
Create, optimize, update, and validate AGENTS.md files with maximum token efficiency. Use when the user asks to (1) create new AGENTS.md files for any repository, (2) optimize/condense existing AGENTS.md to reduce token count, (3) update/refresh AGENTS.md to sync with codebase changes, (4) validate AGENTS.md quality and completeness, or (5) improve AGENTS.md files to be more effective for AI agents. Always generates token-efficient, condensed output focused on actionable commands and patterns while maintaining model-agnostic language.
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.
Syncs skill metadata to AGENTS.md Auto-invoke sections. Trigger: When updating skill metadata (metadata.scope/metadata.auto_invoke), regenerating Auto-invoke tables, or running ./skills/skill-sync/assets/sync.sh (including --dry-run/--scope).
Write, audit, and improve AGENTS.md files for AI coding agents. Use when creating or improving agent context for a codebase.
Install groove backends, companions, and AGENTS.md bootstrap. Run once per repo.