red-team-tribunal

Name: red-team-tribunal
Availability: InStock
Author: aegntic

Coordinate adversarial agents to review code for security and quality consensus.

11|3|Updated Jun 30, 2025

Search Tags:#quality assurance #code review #security audit #multi-agent #consensus #adversarial testing

Ready to run

npx skills add https://github.com/aegntic/cldcde --skill red-team-tribunal

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: red-team-tribunal
Source: https://github.com/aegntic/cldcde/tree/main/.claude/skills/red-team-tribunal
Command: npx skills add https://github.com/aegntic/cldcde --skill red-team-tribunal

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill addresses the risk of "confident mistakes" in code by implementing a rigorous, multi-agent adversarial review process that ensures thorough validation before approval.

Core Features & Use Cases

Multi-Agent Review: Employs specialized agents (Skeptic, User Proxy, Optimizer) to scrutinize code from different perspectives.
Consensus-Based Approval: Requires agreement among agents for code to be approved, preventing single-point-of-failure reviews.
Use Case: Before merging a critical security update to your payment processing module, you can use the Red Team Tribunal to ensure it's free from vulnerabilities, user-impacting bugs, and performance bottlenecks.

Quick Start

Run the red-team-tribunal skill to review the file named 'main.py'.

Frequently Asked Questions about red-team-tribunal

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

FAQPage Schema

How does multi-agent adversarial code review work for security audits?▼

Multi-agent adversarial code review simulates specialized agents, such as a Skeptic, User Proxy, and Optimizer, to scrutinize code from different perspectives. It requires agreement among these agents for code approval, preventing single-point-of-failure reviews.

How do I run a consensus-based code review on a Python file?▼

Consensus-based code review is executed by running the skill against a target file like 'main.py'. The system uses a Python execution environment with asyncio and subprocess capabilities to coordinate specialized agents and manage review tasks.

Can I use this adversarial testing approach for critical payment processing modules?▼

Adversarial testing suits critical payment processing modules by simulating security audits, user interactions, and performance analysis. This multi-agent process ensures the code is free from vulnerabilities, user-impacting bugs, and performance bottlenecks before approval.

What is the best way to prevent confident mistakes in code before merging?▼

Preventing confident mistakes before merging requires a rigorous, multi-agent adversarial review process. By employing specialized agents that must reach a consensus, the system ensures thorough validation of software quality and security before any code is approved.

Do I need asyncio and subprocess capabilities to run multi-agent code reviews?▼

Asyncio and subprocess capabilities are required for agent coordination and task management in multi-agent code reviews. The Python execution environment relies on these capabilities to simulate specialized agents and reach a consensus on code approval.