prompt-compression

# Prompt Compression Skill ## Capabilities - Implement token-efficient prompt compression - Design context pruning strategies - Configure selective context inclusion - Implement LLMLingua-style compression - Design summary-based compression - Create compression quality metrics ## Target Processes - cost-optimization-llm - agent-performance-optimization ## Implementation Details ### Compression Techniques 1. **LLMLingua**: Token-level compression 2. **Summary Compression**: LLM-based summarization 3. **Selective Context**: Relevant section extraction 4. **Token Pruning**: Remove low-importance tokens 5. **Document Filtering**: Pre-retrieval filtering ### Configuration Options - Compression ratio targets - Quality threshold settings - Token budget constraints - Compression model selection - Evaluation metrics ### Best Practices - Monitor quality vs compression tradeoff - Test with representative prompts - Set appropriate compression ratios - Validate compressed prompt quality - Track cost savings ### Dependencies - llmlingua (optional) - tiktoken - transformers