# Prompt Compression

> Token-efficient prompt compression techniques for cost optimization

- Skill: `a5c-ai/prompt-compression` (Agent Skill, multi-file: 2 files)
- Install (CLI): `npx skillmds@latest add a5c-ai/prompt-compression`
- Raw SKILL.md: https://api.skillmd.com/api/skills/a5c-ai/prompt-compression/raw
- Safety review: pending (external: skill-scanner PASS, skillspector PASS)
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: AI & ML
- Author: a5c-ai (https://skillmd.com/u/a5c-ai)
- Updated: 2026-09-09
- Page: https://skillmd.com/skills/a5c-ai/prompt-compression

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# 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