Prompt Compression Skill
SkillAI & modelsToken-efficient prompt compression techniques for cost optimization
Instructions available. Your AI can read the instructions. Execution depends on the setup they require.
Account requirements not reviewed. Check the skill instructions before use; ahel provides instructions and does not run this skill.
Add ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.
Then ask your AI: use the Prompt Compression Skill skill
What this skill tells your AI
The instructions your AI receives, as published by a5c-ai/babysitter in library/specializations/ai-agents-conversational/skills/prompt-compression/SKILL.md and read by ahel’s review.
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
- LLMLingua: Token-level compression
- Summary Compression: LLM-based summarization
- Selective Context: Relevant section extraction
- Token Pruning: Remove low-importance tokens
- 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
Signals
- GitHub stars
- 2k
- Forks
- 112
- Last commit
- Sep 2026
Advanced
- Item type
- skill
- Key
prompt-compression- Source
- github.com/a5c-ai/babysitter
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