Ralph Docs
Introspect, explain, and improve Ralph Orchestrator using its published llms.txt doc map.
Install
npx skills add mikeyobrien/ralph-orchestrator --skill ralph-docs -g -a claude-code -y- Repository
- mikeyobrien/ralph-orchestrator3.2k
- Category
- Testing
- Updated
- 5d ago
- License
- MIT
- Context cost
- Lightabout 1,319 tokens
- Runs scripts
- No, instructions only
What it does
Introspect, explain, and improve Ralph Orchestrator using its published llms.txt doc map. Use this skill whenever the user asks questions about Ralph's behavior, wants to understand how a Ralph internal works (event loop, hats, memories, tasks, backends, presets), debug an unfamiliar failure mode, or propose a code change to the ralph-orchestrator repo. The skill teaches the agent to discover authoritative answers from the live docs via llms.txt before guessing, and to scope improvements through the published architecture rather than the local checkout alone.
Ralph Docs
Introspect Ralph Orchestrator the same way the framework expects a smart agent to, consult the published documentation map at https://mikeyobrien.github.io/ralph-orchestrator/llms.txt, fetch only the sections relevant to the question, and answer from authoritative sources.
Use this skill to behave like an internal Ralph contributor rather than a guess-first assistant.
Use This Skill For
- Answering "how does Ralph do X?" questions about the event loop, hats, memories, tasks, presets, backends, CLI, TUI, diagnostics, waves, or API.
- Explaining an observed behavior ("why did my loop terminate with max_iterations?", "why didn't my hat fire?") from first principles in the docs, not pattern-matching.
- Proposing and scoping an improvement to the
ralph-orchestratorcodebase, locating the right crate, the relevant concept doc, and the existing test surface before writing code. - Triaging a ralph bug report: map symptoms to likely subsystem, pull in the concept + reference docs for that subsystem, identify the probable file path in the repo.
- Onboarding: answer a new user's setup/quick-start questions from the official Getting Started pages instead of the agent's stale training data.
Core Principle: llms.txt Is The Router
Ralph's llms.txt is a curated map, not a full-text dump. The workflow is:
