Loading...
Loading...
Found 13,283 Skills
Harness patterns for coding agents — memory, permissions, context engineering, delegation, skills, hooks, bootstrap.
Meta-router and multi-agent conductor for design work that needs skill selection or a multi-stage pipeline — visual frontend (web pages, landing pages, product UI, mobile screens), data visualization, HTML deliverables (reports/diagrams/plans), artifacts, motion polish, and module/API interface design. The STABLE unified entry point — member skills churn underneath, this router discovers them live, picks one direction authority, delegates image-generation stages to Codex workers, and closes every pipeline with an evidence-first anti-slop quality loop. Do NOT invoke for a one-line CSS/copy tweak, for backend-only work, or when the user explicitly names a single member skill for a single-skill-sized task — those go direct.
Use when assessing whether a repo is ready for autonomous AI agents (pylot workers) — produces a scored, actionable Agent Readiness Report as a GitHub issue in the assessed repo.
Mechanics library for running AI coding CLIs as managed tmux workers via agent-tmux <cli> <command> (plus tmux-agent-sessions and the other bundled tools). Entry point is the using-tmux-agent-tools router skill — route through it first; read this skill for wrapper mechanics it defers to. Covers start/send-wait/status/result/stop, structured result.json completion, multi-worker watch, profiles for custom CLIs, and bounded dialogue/fanout. Not for general tmux config, theming, non-tmux headless CLI use, or human team debate.
Meta-router for the tmux-agent-tools plugin. Invoke BEFORE choosing a wrapper or delegating any tmux-agent work — it decides inline vs worker, picks the right script, and points at the canonical capability table. Even a 1% chance this applies means invoke it.
Fill-in-the-blank prompt templates for delegating work to subagents or tmux workers - SEARCH/LOCATE, IMPLEMENT, REFACTOR, RESEARCH, REVIEW/VERIFY. Invoke BEFORE writing any delegation prompt (Agent tool, agent-tmux worker, or fanout task) so the prompt ships with explicit GOAL, ACCEPTANCE, and REPORT sections instead of a vague ask. Not for deciding WHETHER to delegate or for driving workers after launch (see the tmux-delegate agent and the tmux-agent-tools skill for those).
Build, test, publish, invoke, schedule, and update Railcode managed agents with the Railcode CLI. Use when creating an organization or personal managed agent, editing an agent manifest (JSON or YAML), running a draft or saved agent, investigating a run, managing its cron schedule, running it from Slack (@Railcode $agent), pairing it with a companion app, processing files in its sandbox, or using personal connectors (Gmail, Slack, ...) on behalf of one owner. Do not use for static Railcode apps, in-app LLM tool loops (llm.generate({ tools }) — see create-railcode-app), or general organization administration.
CodeRabbit CLI local code reviews and .coderabbit.yaml configuration. Run AI reviews on uncommitted/committed changes before pushing or opening a PR, parse --agent findings, iterate fix-and-verify loops within hourly rate limits, and tune repo config for low-noise high-signal reviews. Use when reviewing local changes pre-push/pre-PR, installing or driving the coderabbit/cr CLI, creating or tuning .coderabbit.yaml, or reducing CodeRabbit review noise. Not for PR-side review loops and thread handling (git-pr), commits (git-commit), or CI status (git-ci)
Design lightweight eval harnesses for coding or workflow agents, especially when testing whether agents follow steering docs, use tools correctly, preserve user edits, recover from failures, and produce the intended artifact.
Use when an agent is asked "what did I (or my team) work on yesterday / this week / today" across provider data in a relayfile mount (Linear, GitHub, Notion, Slack, Confluence, Jira, etc.). Tells the agent to consult the pre-computed `digests/yesterday.md` (and sibling digest files) at the workspace root BEFORE doing manual exploration with `ls`/`grep`/`find`. The digest is deterministic, exhaustive over the window, and costs one file read instead of dozens of provider queries.
The canonical way to run agent-relay - self-bootstrap the local broker and autonomously spawn, monitor, and coordinate a team of worker agents without human intervention. Covers infrastructure startup, agent spawning, lifecycle monitoring, message-based reading via the relay MCP, and team coordination.
Audit an ENTIRE codebase with multiple agents in parallel — map the repo, partition it into review slices, fan out one (or more, multi-lens) reviewer subagent per slice, reduce with a cross-cutting/architecture critic + a completeness check, then triage, fix, and report with an honest coverage ledger. Use when asked to 'audit the whole codebase', 'full security/quality review of the repo', 'review the entire project', 'do a deep/comprehensive code audit', 'scan everything for bugs or vulnerabilities', when onboarding/inheriting an unfamiliar repo, or for a periodic deep sweep. Whole-repo scoped and scales agent count to repo size — NOT a diff review (for changed lines use dual-agent-review).