code-assist
Guides implementation of code tasks using test-driven development in an Explore, Plan, Code, Commit workflow. Acts as a Technical…
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.
Claude Code
$ npx -y skills add mikeyobrien/ralph-orchestrator --skill ralph-loop --agent claude-code
Codex
$ npx skills add mikeyobrien/ralph-orchestrator --skill ralph-loop -a codex -y
Cursor
$ npx skills add mikeyobrien/ralph-orchestrator --skill ralph-loop -a cursor -y
Gemini CLI
$ npx skills add mikeyobrien/ralph-orchestrator --skill ralph-loop -a gemini-cli -y
GitHub Copilot
$ npx skills add mikeyobrien/ralph-orchestrator --skill ralph-loop -a github-copilot -y
OpenCode
$ npx skills add mikeyobrien/ralph-orchestrator --skill ralph-loop -a opencode -y
Windsurf
$ npx skills add mikeyobrien/ralph-orchestrator --skill ralph-loop -a windsurf -y
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."
Use this skill to operate Ralph loops from the outside.
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.
scratchpad as the primary state model.
dead.
called out explicitly when used.
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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