Consolidate workflows and tools from commands repository

Repository Restructure:
- Move all 83 agent .md files to agents/ subdirectory
- Add 15 workflow orchestrators from commands repo to workflows/
- Add 42 development tools from commands repo to tools/
- Update README for unified repository structure

The commands repository functionality is now fully integrated, providing
complete workflow orchestration and development tooling alongside agents.

Directory Structure:
- agents/    - 83 specialized AI agents
- workflows/ - 15 multi-agent orchestration commands
- tools/     - 42 focused development utilities

No breaking changes to agent functionality - all agents remain accessible
with same names and behavior. Adds workflow and tool commands for enhanced
multi-agent coordination capabilities.

tools/ai-review.md

@@ -0,0 +1,67 @@
+---
+model: claude-sonnet-4-0
+---
+
+# AI/ML Code Review
+
+Perform a specialized AI/ML code review for: $ARGUMENTS
+
+Conduct comprehensive review focusing on:
+
+1. **Model Code Quality**:
+   - Reproducibility checks
+   - Random seed management
+   - Data leakage detection
+   - Train/test split validation
+   - Feature engineering clarity
+
+2. **AI Best Practices**:
+   - Prompt injection prevention
+   - Token limit handling
+   - Cost optimization
+   - Fallback strategies
+   - Timeout management
+
+3. **Data Handling**:
+   - Privacy compliance (PII handling)
+   - Data versioning
+   - Preprocessing consistency
+   - Batch processing efficiency
+   - Memory optimization
+
+4. **Model Management**:
+   - Version control for models
+   - A/B testing setup
+   - Rollback capabilities
+   - Performance benchmarks
+   - Drift detection
+
+5. **LLM-Specific Checks**:
+   - Context window management
+   - Prompt template security
+   - Response validation
+   - Streaming implementation
+   - Rate limit handling
+
+6. **Vector Database Review**:
+   - Embedding consistency
+   - Index optimization
+   - Query performance
+   - Metadata management
+   - Backup strategies
+
+7. **Production Readiness**:
+   - GPU/CPU optimization
+   - Batching strategies
+   - Caching implementation
+   - Monitoring hooks
+   - Error recovery
+
+8. **Testing Coverage**:
+   - Unit tests for preprocessing
+   - Integration tests for pipelines
+   - Model performance tests
+   - Edge case handling
+   - Mocked LLM responses
+
+Provide specific recommendations with severity levels (Critical/High/Medium/Low). Include code examples for improvements and links to relevant best practices.