headroom
CommunityShrink LLM context without losing signal.
Authorbobvarkey
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This Skill reduces oversized LLM context by compressing redundant tool output, JSON, code, and text while preserving the information needed to keep working accurately.
Core Features & Use Cases
- Content Routing: Detects the input type and selects an appropriate compression strategy automatically.
- Structured Compression: Compresses JSON, code, and long text with specialized methods such as SmartCrusher, CodeCompressor, and LLMLingua-2.
- Proxy Workflow: Runs as a proxy so existing OpenClaw and OpenAI-compatible setups can benefit from compression without changing application logic.
Quick Start
Use the headroom skill to compress the latest tool output before sending it back into the LLM context.
Dependency Matrix
Required Modules
python3
Components
Standard package💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: headroom Download link: https://github.com/bobvarkey/openclaw-workspace/archive/main.zip#headroom Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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