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Found 211 Skills
Investigates the context economics of your own coding-agent sessions in LangWatch. Reads real sessions to find where carrying a fat context stops paying for itself, measured in cache rebuilds, compactions and cost per turn, and delivers a report with the context size your sessions should stay under, with example sessions behind every claim. Use when coding-agent sessions feel expensive or degrade as they grow.
Control Herdr, a terminal multiplexer for coding agents. Use only when the user explicitly mentions Herdr or asks to use Herdr to inspect or control panes, tabs, workspaces, commands, or another agent. Do not use merely because a task could benefit from a background terminal, delegation, or parallel work. Requires HERDR_ENV=1.
Interactive plan and diff review for AI coding agents. Visual browser UI for annotating agent plans — approve or request changes with structured feedback. Supports code review, image annotation, and auto-save to Obsidian/Bear Notes.
Generate and use a pre-edit structure brief so coding agents learn likely owners, consumer surfaces, and unsafe edit locations before implementing.
Install and use Supabase Agent Skills (`supabase/agent-skills`) with AI coding agents. Covers install modes, skill selection, plugin path, verification, and safe fallback for direct Supabase CLI/database workflows.
Code review closeout for Claude Code, Codex, OpenCode, and DeepSeek TUI: local dirty changes, branch vs main, parallel tests.
assign a task to an external coding agent and monitor it. Pipes the prompt via stdin to dodge quoting failures and auto-approves permissions to avoid silent hangs. Triggers: run a task with an external agent, hand off to OpenCode, Claude Code, or similar, execute a plan non-interactively. Flags: --agent <name> (default opencode), --model <model>, and --dir <path>.
Orchestrate parallel AI coding agents across git worktrees for autonomous CI fixes, code reviews, and PR management
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.
Structured software development framework for coding agents. Composable skills enforcing planning, testing, and systematic execution. Prevents code-first chaos.
Coding Agent Session Search - unified CLI/TUI to index and search local coding agent history from Claude Code, Codex, Gemini, Cursor, Aider, ChatGPT, Pi-Agent, Factory, and more. Purpose-built for AI agent consumption with robot mode.
Use when the user explicitly asks to invoke another coding agent CLI as a subagent. Triggers include phrases like 'get a second opinion from Codex', 'have Gemini review this', 'run this through Claude Code', 'ask another agent', or 'use a different model for this'. Supports Claude Code, Codex CLI, and Gemini CLI. Never invoke autonomously.