red-team-tribunal

name	red-team-tribunal
description	Multi-agent adversarial verification system. Use when you need thorough code review, security auditing, or quality validation. Spawns three specialized agents (Skeptic, User Proxy, Optimizer) that must reach consensus before code can be approved. Use when this capability is needed.
metadata	{"author":"aegntic"}

Red Team Tribunal: Adversarial Verification

Overview

The Red Team Tribunal uses Opus 4.6 Agent Teams to create an adversarial review loop that prevents "confident mistakes." Three specialized sub-agents work in parallel to find issues from different perspectives.

The Tribunal Structure

🤔 The Skeptic (Security/Logic)

• Role: Security auditor and logic validator
• Goal: Find at least one valid issue (must find something)
• Focus: Security flaws, logic errors, edge cases, race conditions
• Confidence Target: >80%

👤 The User Proxy (UX/Edge Cases)

• Role: End-user simulator
• Goal: Break the feature from a user's perspective
• Focus: Usability, invalid inputs, confusing flows, accessibility
• Tools: Browser automation, form fuzzing

⚡ The Optimizer (Performance)

• Role: Performance engineer
• Goal: Identify efficiency bottlenecks
• Focus: Algorithmic complexity, memory usage, database queries, caching
• Metrics: O(n) complexity, response times, resource usage

When to Use

Activate the Tribunal for:

• Critical code changes (auth, payments, security)
• Before merging pull requests
• When adding new features
• Security-sensitive implementations
• Performance-critical code
• Code that affects multiple users

Usage

Trigger Tribunal Review

# Review a file
python3 /a0/usr/plugins/red-team-tribunal/red-team-tribunal.py --target <file>

# Review a PR
python3 /a0/usr/plugins/red-team-tribunal/red-team-tribunal.py --pr <number>

# Review a commit
python3 /a0/usr/plugins/red-team-tribunal/red-team-tribunal.py --diff <hash>

Understanding Verdicts

CONSENSUS OPTIONS:

1. APPROVED (All agents pass)

   • Code meets all quality standards
   • Ready to merge

2. CONDITIONAL (Concerns raised)

   • Minor issues found
   • Address concerns before merge
   • Can proceed with fixes

3. REJECTED (Critical issues)

   • Security vulnerabilities or major flaws
   • Must fix before reconsideration
   • Returns detailed recommendations

Review Process

Step 1: Agent Assembly

Three agents spawn in parallel:

agents = ["skeptic", "user_proxy", "optimizer"]
tasks = [spawn_agent(agent, target) for agent in agents]
results = await asyncio.gather(*tasks)

Step 2: Individual Analysis

Each agent analyzes from their specialty:

• Skeptic: Scans for vulnerabilities, logic gaps
• User Proxy: Attempts to break UX, finds edge cases
• Optimizer: Reviews complexity, resource usage

Step 3: Consensus Building

Agents debate and produce unified verdict:

• Unanimous approval required for pass
• Any rejection blocks merge
• Concerns must be addressed

Step 4: Report Generation

JSON output includes:

{
  "consensus": "APPROVED|CONDITIONAL|REJECTED",
  "verdicts": [
    {"agent": "skeptic", "verdict": "pass", "confidence": 0.85},
    {"agent": "user_proxy", "verdict": "pass", "confidence": 0.90},
    {"agent": "optimizer", "verdict": "concerns", "confidence": 0.75}
  ],
  "recommendations": [
    "Add input validation",
    "Optimize database query",
    
  

Sample Output

🏛️  RED TEAM TRIBUNAL
Target: src/auth/login.ts

📋 AGENT VERDICTS:
  🤔 Skeptic:     ⚠️  CONCERNS (85%)
  👤 User Proxy:  ✅ PASS (90%)
  ⚡ Optimizer:   ⚠️  CONCERNS (75%)

📊 CONSENSUS: CONDITIONAL - Address Concerns

💡 RECOMMENDATIONS:
  1. Add null check at line 45
  2. Implement memoization for expensive calc
  3. Add rate limiting to prevent brute force

CI/CD Integration

Add to GitHub Actions:

- name: Red Team Tribunal Review
  run: |
    python3 red-team-tribunal.py --pr ${{ github.event.pull_request.number }}

Success Metrics

• Detection Rate: % of real issues found
• False Positive Rate: % of invalid concerns
• Time to Review: Average review duration
• Consensus Time: Time to reach agreement

Troubleshooting

Agents Not Spawning

Check Agent Teams feature is enabled:

export CLAUDE_CODE_EXPERIMENTAL_AGENT_TEAMS=1

Timeout Issues

Increase timeout for complex reviews:

subprocess.run(..., timeout=120)  # 2 minutes

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