cross-review

Enforce adversarial cross-model code review with mutation-based test verification.

3|2|Updated Mar 17, 2026
One-click install
npx skills add https://github.com/broomva/skills --skill cross-review-broomva
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: cross-review
Source: https://github.com/broomva/skills/tree/main/skills/governance/cross-review
Command: npx skills add https://github.com/broomva/skills --skill cross-review-broomva

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires git, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This skill solves the problem of single-model echo chambers where an AI model fails to identify its own blind spots during the planning, implementation, and review phases of software development.

Core Features & Use Cases

  • Adversarial Review Gate: Enforces a mandatory review by a different model or a fresh-context subagent to ensure code quality meets a strict anti-slop rubric.
  • Mutation-Proof Testing: Validates that test suites actually discriminate against code changes by neutering the target and verifying the test fails.
  • Use Case: Before pushing a substantive pull request, use this skill to trigger a cross-vendor or adversarial review that scores the code against a 10-point anti-slop rubric, ensuring only high-quality, well-tested code is merged.

Quick Start

Run the cross-review pre-push command to validate your current changes against the adversarial gate before submitting your pull request.

Frequently Asked Questions about cross-review

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How does adversarial code review prevent AI blind spots in software implementations?▼

Adversarial code review prevents AI blind spots by enforcing a mandatory review through a different model or a fresh-context subagent. This cross-vendor verification ensures code quality meets a strict anti-slop rubric by actively identifying systematic blind spots that single-model echo chambers miss.

How do I validate my test suite discriminates against code changes before a pull request?▼

To validate your test suite before a pull request, use mutation-based test verification. This technique neutering the target code to verify the test fails, applying multi-strata evaluation to ensure your tests actively discriminate against code changes rather than passing silently.

Can I use cross-vendor verification without the optional codex CLI dependency?▼

Cross-vendor verification can utilize a fresh-context subagent as an alternative to the optional codex CLI. The skill requires git and bash for core adversarial review operations, while the codex CLI specifically enhances cross-vendor validation but remains an optional dependency.

What is the best way to enforce an anti-slop rubric for AI-generated code?▼

The best way to enforce an anti-slop rubric for AI-generated code is triggering an adversarial review gate before pushing substantive pull requests. This gate scores the implementation against a 10-point rubric, ensuring only high-quality, well-tested code passes multi-strata evaluation.

When should I not use adversarial cross-model review for my pull requests?▼

You should avoid adversarial cross-model review for non-substantive pull requests. This process is designed specifically for high-integrity validation of substantive changes and design plans, requiring multi-strata evaluation and mutation-based test verification that may be excessive for trivial modifications.