Individual skill
peer-review-loop
Peer Review Ralph Loop — combines Cavekit kits with a Ralph Loop and true cross-model peer review using Codex (OpenAI). Claude builds from specs; Codex reviews adversarially. Primary path: Codex CLI delegation via codex-review.sh (fast, no MCP overhead). Legacy fallback: Codex as MCP server when CLI delegation is unavailable. Covers setup, iteration patterns, convergence detection, and completion criteria. Triggers: "peer review loop", "ralph loop with codex", "cavekit ralph", "peer review build loop", "cross-model loop", "codex peer reviewer", "cavekit to ralph loop"
plugins/JuliusBrussee/blueprint/skills/peer-review-loop/SKILL.md
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- Last checked
- Nov 4, 2026
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- Repository last updated
- Nov 6, 2026
- License
- Apache-2.0
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# Peer Review Loop — Cavekit + Ralph Loop + Codex Peer reviewer
Run a Cavekit cavekit through a Ralph Loop where Claude builds and Codex adversarially reviews.
This is the most rigorous automated quality process available: every few iterations, a completely
different model (different training data, different biases, different blind spots) challenges
your implementation.
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## Why This Works
| Factor | Single-Model Loop | Peer Review Loop |
|--------|-------------------|------------------|
| Blind spots | Same model, same blind spots every iteration | Two models catch different classes of issues |