adversarial-review

Run adversarial code reviews via opposite-model CLIs and synthesize severity-ordered verdicts.

Updated May 15, 2026
One-click install
npx skills add https://github.com/JBonfim/skill-developer --skill adversarial-review-jbonfim
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: adversarial-review
Source: https://github.com/JBonfim/skill-developer/tree/main/.agents/skills/adversarial-review
Command: npx skills add https://github.com/JBonfim/skill-developer --skill adversarial-review-jbonfim

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

It reduces the risk of shipping flawed or overconfident changes by forcing an adversarial review that attacks from multiple critical lenses and then consolidates the results.

Core Features & Use Cases

  • Opposite-model adversarial reviewing: Spawns 1–3 reviewers that run on the opposite model via their required CLI, ensuring the critique is not produced by the same underlying reasoning path.
  • Principle-guided challenge: Uses brain principles from brain/principles.md plus dedicated reviewer lenses from references/reviewer-lenses.md to drive specific, evidence-based findings.
  • Severity-structured verdict synthesis: Produces a single verdict (PASS | CONTESTED | REJECT) with deduplicated findings ordered by severity, plus a final lead judgment that may accept or reject individual findings.

Quick Start

Ask the system to run an adversarial review on your latest work and produce a synthesized verdict without making any changes.

Frequently Asked Questions about adversarial-review

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

FAQPage Schema
How do I run an adversarial code review to find boundary breaks and missing validations before shipping a refactor?▼

Adversarial code review challenges recent diffs and large refactors using multiple critical lenses from the opposite model. It executes via `codex exec` or `claude -p` to stress-test intent alignment and structural correctness, producing a severity-ordered synthesized verdict with deduplicated findings.

What is the best way to use model switching to stress-test planning artifacts and code quality?▼

Model switching ensures critique is not produced by the same underlying reasoning path by spawning 1–3 reviewers on the opposite model. This principle-guided challenge uses dedicated reviewer lenses to identify real defects and verify planning artifacts before changes ship.

Can I use opposite-model execution to review code without applying any automatic changes?▼

Yes, you can ask the system to run an adversarial review on your latest work and produce a synthesized verdict without making any changes. The review yields a final lead judgment that may accept or reject individual findings based on severity.

Does the adversarial review process require both the Codex and Claude CLIs?▼

Opposite-model adversarial reviewing requires executing the opposite model via its required CLI, specifically `codex exec` or `claude -p`. This ensures the critique is generated independently from the original model's reasoning path.

How does the severity-structured verdict synthesis work for risk assessment in software architecture?▼

The severity-structured verdict synthesis produces a single PASS, CONTESTED, or REJECT verdict. It consolidates deduplicated findings ordered by severity, plus a final lead judgment that may accept or reject individual findings to reduce the risk of shipping flawed changes.

When should I not use an adversarial review approach for my codebase?▼

Adversarial review targets recent diffs, large refactors, and planning artifacts where intent alignment and structural correctness must be stress-tested. It is designed for pre-shipment risk assessment rather than routine syntax correction or formatting tasks.