feat: add auto issue labeling and Claude suggestions workflows

[subercui]

Resolves #325

Adds GitHub Actions workflows for automatic issue management:

🏷️ Auto Issue Labeling:

• Intelligent categorization using Claude AI
• Type labels: bug, enhancement, documentation, question, etc.
• Component labels: model, preprocessing, training, inference, etc.
• Priority classification: high/medium/low

💬 Auto Issue Suggestions:

• Context-aware helpful comments on new issues
• Tailored guidance for different issue types
• References to documentation and tutorials
• Welcoming community responses

Setup: Complete workflow files and instructions provided in CLAUDE-AUTO-WORKFLOWS.md due to GitHub App workflow permissions.

🤖 Generated with Claude Code

[claude]

🔍 Code Review - Auto Issue Management Workflows

Thank you for this contribution! I've reviewed the GitHub Actions workflows for automatic issue labeling and Claude suggestions. Here's my comprehensive feedback:

✅ Strengths

Code Quality & Documentation:

• Excellent documentation structure with clear setup instructions
• Well-organized workflow YAML with appropriate permissions
• Comprehensive label taxonomy covering all major project areas
• Clear separation of concerns between labeling and suggestions workflows

Security Considerations:

• Proper use of id-token: write for OIDC authentication
• Minimal permissions scope (contents: read, issues: write)
• Secure secret handling with CLAUDE_CODE_OAUTH_TOKEN
• Tool restrictions using claude_args with allowed-tools constraint

🔧 Recommendations for Improvement

1. Workflow Robustness:
Consider adding error handling and retry logic:

• Add continue-on-error: true to prevent workflow failure from blocking issue creation
• Add timeout-minutes: 5 for timeout protection

2. Rate Limiting & Performance:

• Both workflows trigger simultaneously on issue creation - consider adding a small delay or combining them
• No explicit rate limiting for the Claude API calls
• Consider caching for repeated similar issues

3. Label Management:
The documentation mentions creating labels manually. Consider adding a label setup workflow to automatically create the required labels.

4. Prompt Engineering:

• The prompts are comprehensive but quite long - consider extracting common instructions to reduce token usage
• Add examples of good vs bad labeling decisions for consistency
• Consider adding confidence thresholds for auto-labeling

⚠️ Potential Issues

1. Action Dependency:

• Relies on anthropics/claude-code-action@v1 which may not exist yet
• No fallback mechanism if the action fails
• Version pinning could be more specific (@v1.0.0 vs @v1)

2. Token Costs:

• Long prompts + issue content could result in significant token usage
• No cost limiting or budget controls mentioned

3. Edge Cases:

• No handling for issues with very large content (>context window)
• No duplicate detection before adding labels
• No handling for private issues or security-related content

🧪 Testing Considerations

The PR lacks testing strategy. Consider:

• Test workflows on a fork first
• Add integration tests for common issue types
• Monitor false positive/negative rates after deployment
• Consider a staging environment for workflow testing

📊 Performance Considerations

• Both workflows run on every issue - could be resource intensive for active repositories
• Consider implementing smart filtering (skip duplicate issues, limit to certain hours, etc.)
• Add metrics collection to track workflow success rates and response times

🔒 Security Review - APPROVED

• Appropriate OAuth token usage
• Minimal required permissions
• Tool restriction properly implemented
• No exposure of sensitive data in prompts

📝 Minor Documentation Issues

1. Consider adding troubleshooting section for common setup issues
2. Add examples of expected workflow outputs
3. Include cost estimation guidance

🎯 Overall Assessment

This is a well-structured contribution that addresses issue #325 effectively. The workflows are thoughtfully designed with good security practices. The main concerns are around operational robustness and cost management rather than fundamental code issues.

Recommendation: ✅ APPROVE with minor improvements suggested above

The implementation provides significant value for issue triage automation while maintaining security best practices. Consider implementing the robustness improvements before production deployment.