Coordinate adversarial agents to review code for security and quality consensus.
npx skills add https://github.com/aegntic/cldcde --skill red-team-tribunal
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
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.
Run the red-team-tribunal skill to review the file named 'main.py'.
High-intent search queries and answers about installing and using this skill.
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.
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.
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.
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.
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.
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