feat: #46: Add GitHub Actions workflow for automated code review

[wassertim]

Summary

• ✅ Complete GitHub Actions workflow for automated AI code review
• ✅ Support for multiple AI providers (OpenAI, Anthropic, Google)
• ✅ Robust timeout and error handling with debug logging
• ✅ Node.js and MCP tools setup for StreetRace functionality
• ✅ Local testing scripts and comprehensive documentation

Key Features

• AI Code Review Integration: Automated code review using StreetRace with configurable AI models
• Multi-Provider Support: Works with OpenAI, Anthropic Claude, and Google AI APIs
• Error Handling: Proper timeout detection, verbose logging, and graceful failure handling
• MCP Support: Full Node.js and Model Context Protocol setup for file operations
• Testing Suite: Local testing scripts to validate workflow before deployment

Technical Implementation

• Timeout Handling: 300-second HTTP timeouts with proper error detection by parsing output
• Debug Logging: Verbose mode enabled with comprehensive logging for troubleshooting
• Dependencies: Node.js 20 setup with @modelcontextprotocol/server-filesystem installation
• Report Generation: Automated review report creation with timestamp-based naming
• PR Integration: Automatic comment posting with review results

Files Added

• .github/workflows/code-review.yml - Main GitHub Actions workflow
• .github/workflows/scripts/ - Workflow execution scripts (code-review, post-comment, extract-diff)
• templates/github-code-review.md - Structured review instructions template
• scripts/test-*.sh - Local testing and validation utilities
• docs/GITHUB_ACTIONS_SETUP.md - Complete setup and configuration guide

Test Plan

• Local workflow testing with scripts/test-github-workflow.sh
• Timeout handling validation with verbose logging
• MCP tools installation and Node.js setup verification
• Multi-provider API key configuration testing
• Report generation and PR comment posting validation

Resolution

This resolves the timeout issues encountered during GitHub Actions execution by:

1. Adding missing Node.js setup - Required for MCP server functionality
2. Installing MCP filesystem server - Essential dependency for file operations
3. Implementing proper timeout detection - Parses output for timeout errors
4. Adding comprehensive debug logging - Verbose mode for better troubleshooting
5. Increasing timeout limits - 300-second HTTP timeouts for CI environment

🤖 Generated with Claude Code

[github-actions]

🤖 AI Code Review

Pull Request Context:

Review Results:

Summary

This pull request introduces a comprehensive implementation of an AI-powered code review workflow using GitHub Actions. It allows the StreetRace🚗💨 application to facilitate automated code reviews on pull requests, analyzing changes, and posting structured feedback.

Critical Issues 🚨

• Security: Ensure that API keys are stored securely in GitHub Secrets. All references to potential API keys in the code should be validated against being hardcoded.
• Error Handling: There should be strict checks on conditions like missing environment variables to ensure the workflow does not fail silently.

High Priority Issues ⚠️

• Performance: The extract-diff.sh and post-review-comment.sh scripts should be reviewed for any performance bottlenecks especially with large diffs, as there's a potential for high resource consumption if the diff size exceeds the limit.
• Logging: Improve logging throughout the scripts to capture more context, especially around failed API calls and errors in post-review processes.

Medium Priority Issues ℹ️

• Code Clarity: The integration scripts could use more comments explaining the workflow especially in complex sections. This will aid in maintainability.
• Modularity: Consider breaking larger functions into smaller reusable components within the scripts, enhancing readability and testing capabilities.

Low Priority Issues 💡

• Documentation: The Shepherding of README.md and related documentation files (like CLAUDE.md, GITHUB_ACTIONS_SETUP.md) could be updated with examples of how to utilize the new workflow effectively. They seem solid but might want more real-world application context.

Positive Feedback ✅

• Structured Approach: The implementation follows a well-structured approach for integration with GitHub Actions, which is a good practice in CI/CD pipelines. The usage of environment variables for configuration is sensible and enhances security. Good usage of colored output for terminal feedback in bash scripts.
• Comprehensive Testing: The introduction of local test scripts to simulate the GitHub workflow is a great addition that allows developers to validate changes without pushing directly to GitHub.

Recommendations

• =Testing= : Ensure there are enough unit tests covering the new functionality and edge cases. Introduce integration tests where appropriate to validate the interaction between various components in the workflow.
• Follow-up Work: Regularly update the documentation and provide training for team members on utilizing the new automation features for more effective use in their workflow.

Overall, this is a strong pull request that represents significant forward progress in integrating AI-assisted code reviews within the CI/CD flow, with room for refining error handling and documentation.

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This review was generated automatically using StreetRace AI. Please use your judgment when addressing the feedback.