# Message Queue Consumer Tool - Compliance Checklist

**Status**: ✅ **MOSTLY COMPLIANT**  
**Priority**: LOW - Minor verification needed

## ✅ Already Compliant

- [x] Has all required files: `main.py`, `agents.yaml`, `workflows.yaml`, `readme.md`, `template.md`
- [x] Class name follows convention: `MessageQueueConsumerMCPTool`
- [x] Has `_bypass_pydantic = True`
- [x] Documentation files are lowercase
- [x] Modern workflow patterns
- [x] Good documentation structure

## ⚠️ Items to Verify

### 1. Model Configuration Review
- [ ] Verify all agents use optimal models (`gpt-4o` preferred)
- [ ] Check for any `gpt-4` that could be upgraded
- [ ] Ensure message processing agents have appropriate models

### 2. Workflow Format Verification
- [ ] Verify all workflows use modern `output: to:` format
- [ ] Check for any deprecated `output_key` patterns
- [ ] Validate step reference accuracy

### 3. Message Queue Integration
- [ ] Verify queue connection patterns are secure
- [ ] Check error handling for queue failures
- [ ] Validate message processing reliability

## 🔍 Message Queue Specific Checks

### Queue Operations
- [ ] Connection management
- [ ] Message acknowledgment patterns
- [ ] Error handling for failed messages
- [ ] Dead letter queue handling
- [ ] Queue monitoring capabilities

### Performance Considerations
- [ ] Message processing efficiency
- [ ] Batch processing capabilities
- [ ] Resource usage optimization
- [ ] Scaling considerations

## 🧪 Testing Recommendations

- [ ] Test queue connection and disconnection
- [ ] Verify message processing accuracy
- [ ] Test error handling scenarios
- [ ] Validate queue monitoring
- [ ] Test performance under load

## 📅 Implementation Priority

1. **MEDIUM**: Verify model configurations
2. **LOW**: Check workflow format compliance
3. **LOW**: Validate queue integration patterns
4. **OPTIONAL**: Optimize performance

## 🎯 Success Criteria

- [ ] All agents use optimal model configurations
- [ ] All workflows use modern format
- [ ] Queue operations are reliable
- [ ] Error handling is robust
- [ ] Performance is acceptable for production use

## 💡 Enhancement Opportunities

- [ ] Add queue health monitoring
- [ ] Implement advanced message filtering
- [ ] Add message transformation capabilities
- [ ] Enhance error recovery mechanisms
- [ ] Add queue analytics and metrics

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**Estimated Work**: 1 hour (verification and minor updates)  
**Risk Level**: Low (likely already compliant)  
**Dependencies**: Message queue infrastructure  
**Status**: Verification needed, likely minimal fixes required
