Create, validate, and improve Ralph hat collection YAML workflows.
npx skills add https://github.com/mikeyobrien/ralph-orchestrator --skill ralph-hats
Please help me install this Agent Skill. Skill: ralph-hats Source: https://github.com/mikeyobrien/ralph-orchestrator/tree/main/skills/ralph-hats Command: npx skills add https://github.com/mikeyobrien/ralph-orchestrator --skill ralph-hats
Designing multi-agent orchestration workflows in Ralph requires correctly wiring hat triggers, published events, and routing rules in YAML, where mistakes like reserved triggers or ambiguous routing break the run. This Skill guides the full lifecycle of authoring, inspecting, validating, and refining .ralph/hats/*.yml collections.
.ralph/hats/ with correct schema, semantic delegated events, and per-hat instructions.ralph hats graph, inspect single hats with ralph hats show, and catch routing errors with ralph hats validate.work.start as the starting event, validates routing, and renders a mermaid graph of the event flow.Ask the assistant to create a Ralph hat collection in .ralph/hats/ for a plan-build-review workflow and validate it with ralph hats validate.
High-intent search queries and answers about installing and using this skill.
Create a YAML file under `.ralph/hats/` defining an `event_loop` with a starting event and a `hats` map where each hat declares triggers, publishes, and instructions. Then validate it with `ralph hats validate -c ralph.yml -H .ralph/hats/<name>.yml`.
Run `ralph hats validate` to catch reserved triggers, ambiguous routing, and orphan events. Use `ralph hats graph --format mermaid` or `--format ascii` to visualize the event topology, and `ralph hats show <hat>` to inspect one hat.
Ralph reserves `task.start` and `task.resume` for coordinator coordination, so assigning them as hat triggers is rejected. Use a semantic delegated event like `work.start` or `review.start` and set it as `event_loop.starting_event`.
Hats files support only the top-level keys `name`, `description`, `events`, `event_loop`, and `hats`. Runtime settings like `max_iterations` or `required_events` belong in the core `-c` config, not the hats overlay.
Use a linear pipeline when work flows one way from planning to completion. Use a review loop with a closer hat that publishes either a follow-up event or the completion promise when the workflow needs iteration and rejection cycles.
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