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Found 71 Skills
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).
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").
Write, audit, and improve AGENTS.md files for AI coding agents. Use when creating or improving agent context for a codebase.
Manage background coding agents in tmux sessions. Spawn Claude Code or other agents, check progress, get results.
Run a free 35B AI coding agent on Apple Silicon Macs using local LLMs via llama.cpp or MLX with web search, shell, and file tools.
Production-grade engineering skills for AI coding agents - lifecycle commands, workflow automation, and best practices for software development.
Run a coding agent in an autonomous loop via a /ralph command, gated by a preflight check that every CLI is installed, linked, and authenticated. Use when driving long-running autonomous development from a wide, outcome-focused prompt.
Configure AI coding agents like Cursor, GitHub Copilot, or Claude Code with project-specific patterns, coding guidelines, and MCP servers for consistent AI-assisted development.
Scaffold development rules for AI coding agents. Auto-invoked when user asks about setting up rules, coding conventions, or configuring their AI agent environment.
Write effective AGENTS.md files that give coding agents the context they need to work in a repository. Use when creating a new AGENTS.md, improving an existing one, setting up a repo for AI coding agents, or onboarding agents to a codebase. Triggers on: "write AGENTS.md", "create AGENTS.md", "agent instructions", "set up repo for agents", "configure coding agent", "onboard agent to codebase", "agent context file".
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.
Add persistent memory to AI coding agents using agentmemory - remembers context, preferences, and decisions across sessions