Agent skill · Documentation

ralph

Specification-first AI development powered by Ouroboros. Socratic questioning exposes hidden assumptions before writing code. Evolutionary loop (Interview → Seed → Execute → Evaluate → Evolve) runs until ontology converges. Ralph mode persists until verification passes — the boulder never stops. Use when user says \"ralph\", \"ooo\", \"don't stop\", \"must complete\", \"until it works\", \"keep going\", \"interview me\", or \"stop prompting\".

majiayu000github.com/majiayu000GitHub ↗
claude-codecan modify filesMIT
Install
npx skills add majiayu000/claude-skill-registry --skill ralph-aiskillstore-marketplace --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 2
SKILL.md size: 16 KB
Bundled scripts: none
Version: 3.0.0
Allowed tools: ReadWriteBashGrepGlobWebFetch
Path: skills/agent/ralph-aiskillstore-marketplace/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 534
Language: HTML

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# ralph (Ouroboros) — Specification-First AI Development > **Stop prompting. Start specifying.** > > *"The beginning is the end, and the end is the beginning."* > The serpent doesn't repeat — it evolves. --- ## When to use this skill - **Before writing any code** — expose hidden assumptions with Socratic interviewing - **Long-running tasks** that need autonomous iteration until verified - **Vague requirements** — crystallize them into an immutable spec (Ambiguity ≤ 0.2) - **Tasks requiring guaranteed completion** — loop until verification passes - **When stuck** — 5 lateral thinking personas break through stagnation - **Drift detection** — measure how far execution has deviated from original spec --- ## Core Architecture: The Loop ``` Interview → Seed → Execute → Evaluate ↑ ↓ └──── Evolutionary Loop ────┘ ``` Each cycle **evolves**, not repeats. Evaluation output feeds back as input for the next generation until the system converges. ### Double Diamond ``` ◇ Wonder ◇ Design ╱ (diverge) ╱ (diverge) ╱ explore ╱ create ╱ ╱ ◆ ──────────── ◆ ──────────── ◆ ╲ ╲ ╲ define ╲ deliver ╲ (converge) ╲ (converge) ◇ Ontology ◇ Evaluation ``` The first diamond is **Socratic**: diverge into questio

What's inside
Steps it walks through
  1. When to use this skill
  2. Core Architecture: The Loop
  3. Double Diamond
  4. 1. Commands (Full Reference)
  5. 2. Interview → Specification Flow
  6. Philosophy: From Wonder to Ontology
  7. Step 1: Interview (expose hidden assumptions)
  8. Step 2: Seed (crystallize into immutable spec)
  9. Step 3: Run (execute via Double Diamond)
  10. Step 4: Evaluate (3-stage verification)
  11. 3. Ralph — Persistent Loop Until Verified
  12. How Ralph Works
  13. State File
  14. Loop Logic
Ships with 1 file
  • metadata.json
Commands it runs
Install
claude plugin marketplace add Q00/ouroboros
claude plugin install ouroboros@ouroboros
One-time setup
ooo setup
Use
ooo interview "I want to build a task CLI"
ooo seed
ooo run
ooo evaluate <session_id>
More from claude-skill-registry
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About this skill
What does the ralph skill do?

Specification-first AI development powered by Ouroboros. Socratic questioning exposes hidden assumptions before writing code. Evolutionary loop (Interview → Seed → Execute → Evaluate → Evolve) runs until ontology converges. Ralph mode persists until verification passes — the boulder never stops. Use when user says \"ralph\", \"ooo\", \"don't stop\", \"must complete\", \"until it works\", \"keep going\", \"interview me\", or \"stop prompting\".

How do I install it?

Run `npx skills add majiayu000/claude-skill-registry --skill ralph-aiskillstore-marketplace --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

Keep going