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/ralph-loop

Run, monitor, resume, merge, and debug Ralph loops. Use this skill whenever the user asks to operate `ralph run` or `ralph loops`, inspect loop state, recover suspended loops, analyze diagnostics, or unblock merge queue issues.

From plugin
ralph-orchestrator
3.2k17 skills3 agents

Claude Code

$ npx -y skills add mikeyobrien/ralph-orchestrator --skill ralph-loop --agent claude-code

SKILL.md

ralph-loop.SKILL.md
name: ralph-loop
description: "Operate Ralph loops: run, monitor, measure, resume, merge, debug. Use for `ralph run` or `ralph loops`, headless runs, A/B comparing hat collections, suspended loops, or merge queue issues."

Ralph Loop

Use this skill to operate Ralph loops from the outside.

Use This Skill For

  • Starting or continuing a Ralph run with the right `-c` and `-H` inputs
  • Inspecting loop state, worktrees, logs, history, and diffs
  • Resuming a hook-suspended loop
  • Merging or discarding completed worktree loops
  • Debugging unexpected loop behavior with current diagnostics files
  • Running a loop headlessly, measuring its cost and iterations, or A/B comparing two hat collections

Workflow

1. Start with `ralph loops list` or `ralph loops list --json` to establish the current state. 2. If the user wants execution, run `ralph run ...` with the right core config and hats source. 3. If the loop is stuck or suspicious, inspect `logs`, `history`, and `diff` before changing state. 4. If the loop is suspended, read `.ralph/suspend-state.json` and use `ralph loops resume <id>`. 5. If a loop is queued or in `needs-review`, inspect the diff first, then use `merge`, `process`, `retry`, or `discard` as appropriate. 6. Use diagnostics when you need detailed evidence about hats, events, tool calls, parse errors, or performance. 7. For an unattended run, or to report what a run did and cost, follow `references/headless-runs.md`: isolate the workspace, launch with `--autonomous`, watch the events file, and measure from the run log.

Guardrails

  • Prefer the CLI over direct edits to `.ralph` state files.
  • Treat tasks and memories as the canonical runtime systems; do not center

scratchpad as the primary state model.

  • Inspect diffs before merging.
  • Only remove lock or queue artifacts when the underlying process is confirmed

dead.

  • Manual edits under `.ralph/` are last-resort recovery steps and should be

called out explicitly when used.

Read These References When Needed

  • For command recipes and operator flows: `references/commands.md`
  • For diagnostics files and suspend-state details: `references/diagnostics.md`
  • For headless launch, monitoring, measuring, A/B comparison, and when to step in: `references/headless-runs.md`
Read more
@mikeyobrien
Ships withralph-orchestrator

A hat-based orchestration framework that keeps AI agents in a loop until the task is done. "Me fail English? That's unpossible!" - Ralph Wiggum

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Questions about ralph-loop.

Which coding agents can use ralph-loop?
ralph-loop installs in Claude Code, Codex, Cursor, Gemini CLI, GitHub Copilot, OpenCode and Windsurf with the skills CLI, using each agent's flag shown on this page. Flowy's auto-invocation, which fires a skill when your prompt matches, runs in Claude Code only.