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Found 63 Skills
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.
Use when creating, rewriting, pruning, or reviewing `AGENTS.md` or `CLAUDE.md`, especially to remove repo summaries, stale rules, and other low-signal global instructions. Trigger when deciding what belongs in always-on agent files versus a task-specific skill.
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.
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.
Generate AGENTS.md file and docs/ knowledge base skeleton in the project root directory, and establish a document governance system for agent-first repositories. Manually triggered, writes the template after checking for existence.
Harness Engineering Phase 1 Step 2: Conduct in-depth analysis of project code and fill in the substantive content of each file in the docs/ knowledge base. Use this skill after the directory skeleton is created by harness-step1-create-agents-md. Immediately trigger this skill when the user says "fill document content", "improve docs/ files", "add substantive content to documents", "analyze project and write architecture document", "write ARCHITECTURE.md", or "write technical decision document". Prerequisite: The project already has AGENTS.md and the docs/ directory skeleton (created by harness-step1).
Feature-complete companion for the actual CLI, an ADR-powered CLAUDE.md/AGENTS.md generator. Runs and troubleshoots actual adr-bot, status, auth, config, runners, and models. Covers all 5 runners (claude-cli, anthropic-api, openai-api, codex-cli, cursor-cli), all model patterns, all 3 output formats (claude-md, agents-md, cursor-rules), and all error types. Use when working with the actual CLI, running actual adr-bot, configuring runners or models, troubleshooting errors, or managing output files.
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.
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.
Sets up or repairs the AGENTS.md source-of-truth pattern for any project. Creates a well-structured AGENTS.md with real stack info auto-detected from the project, then wires all AI config satellites (.claude/CLAUDE.md, .github/copilot-instructions.md, .agents/rules/, MEMORY.md) to point to it. Eliminates duplication. Always runs in plan mode — asks before acting. Use this skill whenever the user mentions AGENTS.md, agent config, source of truth for AI rules, setting up Claude/Copilot/Cursor for a project, fixing duplicate AI instructions, or wants to consolidate AI configuration files. Trigger even if the user just says "set up agents" or "fix my AI config".
Audit and prune bloated CLAUDE.md or AGENTS.md context files using evidence-based criteria from research on what actually helps coding agents. Use when a user asks to trim, audit, review, or improve their CLAUDE.md, AGENTS.md, or any repository context file for AI coding agents.
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.