Prompt Compression Skill

SkillAI & models

Token-efficient prompt compression techniques for cost optimization

Use Prompt Compression Skill in Claude, ChatGPT or Ahel Desktop

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Also: Claude Code · Cursor · Codex

Then ask your AI: use the Prompt Compression Skill

Details

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.

No other account needed.

Add Ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.

Prompt Compression SkillStart free

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: 113
Last commit: Sep 2026

Advanced

Item type: skill
Key: prompt-compression
Source: github.com/a5c-ai/babysitter

github.com/a5c-ai/babysitter