Loading...
Loading...
Found 48 Skills
Install the Chief into the current project. Uses setup.sh as the primary method, then verifies and fixes manually if needed. Use when the user wants to set up the framework (e.g. "/chief-install" or "/chief-install canary").
Open source harness for generating 3D CAD models from text using AI coding agents with build123d/OpenCascade, exporting STEP/STL/URDF, and previewing in a local CAD Explorer viewer.
Query AI coding agent usage, costs, and token consumption. Supports Claude Code, Codex CLI, OpenClaw, and OpenCode. Ask about spending, token usage, model costs, session history, API call counts. Actions: check usage, show cost, compare models, list sessions, analyze spending, token breakdown. Time ranges: today, this week, this month, this year, last N days, custom dates.
Guide for creating, refactoring, and optimizing AGENTS.md files (and CLAUDE.md files) for AI coding agent repositories. Use when the user wants to create a new AGENTS.md, refactor an existing one, audit their AGENTS.md for bloat or staleness, apply progressive disclosure principles, set up AGENTS.md in a monorepo, or improve how their AI coding agents behave via repository configuration files. Also applies to CLAUDE.md files (Claude Code's equivalent).
Terminal session manager for AI coding agents. Use when user mentions "agent-deck", "session", "sub-agent", "MCP attach", "git worktree", or needs to (1) create/start/stop/restart/fork sessions, (2) attach/detach MCPs, (3) manage groups/profiles, (4) get session output, (5) configure agent-deck, (6) troubleshoot issues, (7) launch sub-agents, or (8) create/manage worktree sessions. Covers CLI commands, TUI shortcuts, config.toml options, and automation.
Manage background coding agents in tmux sessions. Spawn Claude Code or other agents, check progress, get results.
Help generate or update the AGENTS.md file for guiding AI coding agents.
Guide for understanding and contributing to the awesome-skills curated resource list. Use this skill when adding resources, organizing categories, or maintaining README.md consistency (no duplicates).
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.
Fast web browsing and web app testing for AI coding agents via persistent headless Chromium daemon. Browse any URL, read page content, click elements, fill forms, run JavaScript, take screenshots, inspect CSS/DOM, capture console/network logs, and more. Ideal for verifying local dev servers, testing UI changes, and validating web app behavior end-to-end. ~100ms per command after first call. Works with Claude Code, Cursor, Cline, Windsurf, and any agent that can run Bash. No MCP, no Chrome extension — just fast CLI.
Core patterns for AI coding agents based on analysis of Claude Code, Codex, Cline, Aider, OpenCode. Triggers when: Building an AI coding agent or assistant, implementing tool-calling loops, managing context windows for LLMs, setting up agent memory or skill systems, or designing multi-provider LLM abstraction. Capabilities: Core agent loop with while(true) and tool execution, context management with pruning and compression and repo maps, tool safety with sandboxing and approval flows and doom loop detection, multi-provider abstraction with unified API for different LLMs, memory systems with project rules and auto-memory and skill loading, session persistence with SQLite vs JSONL patterns.
Set up or update the agent-first engineering harness for any repository. Implements the complete scaffolding that makes AI coding agents effective: knowledge maps (AGENTS.md as a concise TOC), structured documentation, architecture boundaries, enforcement rules (.harness/*.yml specs), quality scoring, and process patterns for agent-driven development. Use this skill whenever someone wants to make a repo agent-ready, set up AGENTS.md or docs/ structure, define domain boundaries or golden principles, generate .harness/ configuration, audit agent readiness, or update an existing harness. Also trigger when a user reports problems with agent effectiveness, context management, or architectural drift — these are symptoms of a missing or stale harness. Trigger on: "harness this repo", "set up harness", "agent-first setup", "make this agent-ready", "update the harness", "assess agent readiness", "set up AGENTS.md", "organize for agents", or any discussion about structuring a codebase for AI agent workflows.