GitHub PR Review Agent

An agent that reviews pull requests with governance, preventing malicious code suggestions and security vulnerabilities.

What This Example Shows

Real-world GitHub integration via GitHub API
Output sanitization policies to prevent credential leakage
Shadow mode for testing policies before enforcement
Trust score decay on bad suggestions or policy violations

Use Case

A code review agent that:

Analyzes pull requests for security issues
Suggests improvements
Never suggests code with hardcoded secrets
Blocks suggestions that violate security policies
Tracks trust score based on suggestion quality

Architecture

┌────────────────────────────────────────────────────────────┐
│              GitHub PR Review Agent                        │
│                                                            │
│  ┌──────────────────────────────────────────────────────┐ │
│  │ AgentMesh Governance                                 │ │
│  │ • Output sanitization (no secrets in suggestions)   │ │
│  │ • Shadow mode testing                                │ │
│  │ • Trust score tracking                               │ │
│  └──────────────────────────────────────────────────────┘ │
│                         │                                  │
│  ┌──────────┬──────────┴──────────┬──────────────────┐   │
│  │ GitHub   │ LLM Code            │  Security        │   │
│  │ API      │ Analysis            │  Scanners        │   │
│  └──────────┴─────────────────────┴──────────────────┘   │
└────────────────────────────────────────────────────────────┘

Quick Start

# Set GitHub token
export GITHUB_TOKEN="your_token_here"

# Install dependencies
pip install -r requirements.txt

# Run the agent
python main.py --repo owner/repo --pr 123

Key Features

1. Output Sanitization

Prevents agent from suggesting code with secrets:

# This would be blocked by policy
suggestion = "API_KEY = 'sk-abc123...'"  # ✗ Blocked

# This would be allowed
suggestion = "API_KEY = os.getenv('API_KEY')"  # ✓ Allowed

2. Shadow Mode

Test policies without blocking:

governance:
  shadow_mode: true  # Log violations but don't block

3. Trust Score Tracking

Agent's trust score changes based on:

Quality of suggestions (upvoted/downvoted)
Policy compliance
Security issues found vs. false positives

Security Policies

No hardcoded secrets in suggestions
No SQL injection patterns
No XSS vulnerabilities in web code
No path traversal vulnerabilities

Example Output

🔍 Reviewing PR #123: Add user authentication

✓ Scanned 5 files
✓ Found 2 security issues
  • Hardcoded API key in config.py (critical)
  • Missing input validation in auth.py (medium)

💡 Suggestions:
  1. Use environment variables for API keys
  2. Add input validation with regex

📋 Policy checks: All passed
⭐ Trust score: 847/1000

Integration with GitHub Actions

# .github/workflows/pr-review.yml
name: AgentMesh PR Review
on: [pull_request]

jobs:
  review:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v2
      - run: pip install agentmesh-platform
      - run: python pr-agent.py --pr ${{ github.event.pull_request.number }}
        env:
          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}

Learn More

Note: This example uses simulated GitHub API calls. For production, integrate with actual GitHub API.

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