Loading...
Loading...
Found 107 Skills
Cancel an active Ralph Loop. Use when the user wants to stop, cancel, or abort a running ralph loop.
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.
Execute a single Ralph iteration - implement one user story autonomously. Use for manual mode where you want maximum control and fresh context per story. Triggers on: ralph iterate, execute one story, run single iteration, manual ralph.
Create, inspect, validate, explain, and improve Ralph hat collections. Use this skill whenever the user asks to make or refine a `.ralph/hats/*.yml` workflow, debug hat routing, explain event topology, or tune a multi-hat Ralph run.
Self-referential development loop with ultrawork mode - continues until verified task completion
Use when reporting progress in autonomous loop iterations. Triggers at the end of every autonomous loop iteration, when the autonomous-loop skill completes a BUILD phase, when progress reporting is needed for monitoring or exit evaluation, or when producing machine-parseable RALPH_STATUS blocks with exit signal protocol.
Transforms a rough idea into a detailed design document with implementation plan. Follows Prompt-Driven Development — iterative requirements clarification, research, design, and planning.
Autonomous AI coding with spec-driven development. Implements Geoffrey Huntley's iterative bash loop methodology where agents work through specs one at a time, outputting a completion signal only when acceptance criteria are 100% met.
Runs autonomous loop fetching stories from GitHub Issues. Implements and closes issues as done. Triggers on "loop through my PRDs", "work on my issues", "start the autonomous loop", "implement my PRDs", or requests to work through GitHub issues autonomously.
RFC-driven multi-agent DAG execution pattern with quality gates, merge queues, and work unit orchestration.
Use when automating an iterative GitHub Copilot review loop on a PR — triggers Copilot review, addresses its feedback one comment at a time, and re-triggers up to 2 cycles until all critical issues are resolved.
Autonomous TDD development loop with parallel agent swarm, category evolution, and convergence detection. Use when running autonomous game development, quality improvement loops, or comprehensive codebase reviews.