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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.
1.4 KiB
1.4 KiB
model
| model |
|---|
| claude-sonnet-4-0 |
AI Prompt Optimization
Optimize the following prompt for better AI model performance: $ARGUMENTS
Analyze and improve the prompt by:
-
Prompt Engineering:
- Apply chain-of-thought reasoning
- Add few-shot examples
- Implement role-based instructions
- Use clear delimiters and formatting
- Add output format specifications
-
Context Optimization:
- Minimize token usage
- Structure information hierarchically
- Remove redundant information
- Add relevant context
- Use compression techniques
-
Performance Testing:
- Create prompt variants
- Design evaluation criteria
- Test edge cases
- Measure consistency
- Compare model outputs
-
Model-Specific Optimization:
- GPT-4 best practices
- Claude optimization techniques
- Prompt chaining strategies
- Temperature/parameter tuning
- Token budget management
-
RAG Integration:
- Context window management
- Retrieval query optimization
- Chunk size recommendations
- Embedding strategies
- Reranking approaches
-
Production Considerations:
- Prompt versioning
- A/B testing framework
- Monitoring metrics
- Fallback strategies
- Cost optimization
Provide optimized prompts with explanations for each change. Include evaluation metrics and testing strategies. Consider both quality and cost efficiency.