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Found 89 Skills
Run agentlint CLI after code changes to catch patterns for AI evaluation. Activate when finishing code modifications, before committing, or when the developer asks to lint, scan, or review code with agentlint. Covers agentlint check, agentlint list, agentlint review, agentlint init, inline suppression, and output interpretation.
Spawn and manage parallel AI coding agents via tmux. Use when you need to orchestrate workers, delegate sub-tasks, run multi-agent improvement loops, or manage agent lifecycles with orca CLI commands like spawn, list, kill, steer, logs, and daemon.
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.
Gemini CLI consultation workflow for coding agents. Use when technical tasks need Gemini consultation for decisions, planning, debugging, problem-solving, or pre-implementation guidance.
Use this skill whenever a user wants to run, install, configure, or understand open-ralph-wiggum (ralph). This skill can be used by any AI assistant or IDE agent (GitHub Copilot, Claude Code, Cursor, Windsurf, etc.). Triggers on: "ralph", "ralph wiggum", "agentic loop", "iterative AI loop", "autonomous coding loop", "how to install ralph", "how to use ralph with Claude Code / Codex / Copilot / OpenCode", "ralph --agent", "ralph --tasks", "ralph --status", "--max-iterations", "--rotation", "how do I run ralph in VS Code / Cursor / JetBrains / Neovim", or any question about looping an AI coding agent until a task is done. Even if the user doesn't say "ralph" explicitly — if they want to run an AI agent in a loop until a promise tag appears in its output, use this skill.