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Found 42 Skills
Expert AGENTS.md file assistant. Use when users want to create, verify, or improve AGENTS.md files. Helps with creating minimal, focused AGENTS.md files following progressive disclosure principles, verifying existing files for issues (bloat, contradictions, stale info), and refactoring bloated files.
Generate comprehensive AGENTS.md documentation for backend projects with complete API specifications, business rules, data models, and data flows. Use when (1) Creating AGENTS.md from existing CLAUDE.md, (2) Documenting backend API modules with FastAPI routes, (3) Migrating documentation to AGENTS.md/CLAUDE.md symlink structure, (4) Adding complete API interface documentation to existing specs, (5) Creating module-level AGENTS.md for specific features (mcp, teamo_code, file_system, etc.)
Cross-tool compatibility workflow. Use when generating AGENTS.md files for compatibility with other AI coding tools, or creating tool-specific instruction files from CLAUDE.md.
Bootstrap AGENTS.md as a short table-of-contents plus a structured docs/ directory (architecture, product specs, acceptance tests, ADRs, exec plans, quality grades). Use when AGENTS.md is missing, when asked to "create AGENTS.md", "bootstrap project for agents", or "set up agent context".
Analyze repository structure and generate or update standardized AGENTS.md files that serve as contributor guides for AI agents. Supports both single-repo and monorepo structures. Measures LOC to determine character limits and produces structured documents covering overview, folder structure, patterns, conventions, and working agreements. Update mode refreshes only the standard sections while preserving user-defined custom sections. Use when setting up a new repository, onboarding AI agents to an existing codebase, updating an existing AGENTS.md, or when the user mentions AGENTS.md.
Optimize AGENTS.md and rules for token efficiency. Auto-invoked when user asks about improving agent instructions, compressing AGENTS.md, or making rules more effective.
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.
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.
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.
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.
Write or revise AGENTS.md per embedded output contract. Use when creating Agent entry for new projects, auditing existing AGENTS.md, or adopting the AI Cortex entry format.