headroom: Reduce Tokens
Headroom reduces the number of tokens required to get the same answers from a large language model by compressing tool outputs, logs, files, and RAG chunks
- •When you need to minimize token usage for cost savings or optimization
- •When your LLM workflows involve large amounts of data or logs
- •When you want to improve the efficiency of your language model-powered applications
curl -X POST -H 'Content-Type: application/json' -d '["echo", "Hello World"]' http://localhost:8080/compress
Skip the builder — one click puts this in Claude, Cursor, Antigravity and more.
A prompt/skill package — nothing to install beyond adding it to your AI tool.
mkdir -p ~/.claude/skills/headroomlabs-ai-headroom && curl -fsSL https://workflowstacks.com/api/skills/headroomlabs-ai-headroom/claude-skill -o ~/.claude/skills/headroomlabs-ai-headroom/SKILL.mdOpens the app with this repo with the prompt ready to go — no copy-paste needed.
Headroom: Reduce Tokens is a very large Python project (~274k lines across 850 code files, plus 912 test files). You install it into your AI tool with one command; there is nothing to run yourself. Last commit this month, Apache-2.0 license, has a test suite.
- 1README.mdStart here — what it does and how to install it
- 2headroom/cli.pyWhere the program starts running
- 3.env.exampleThe API keys and settings you must provide
- 4headroom/__init__.pyInside headroom/ — the main logic begins here
- 5examples/07-context-compression.ipynbA worked example — copy this to get going
Skip the builder — one click puts this in Claude, Cursor, Antigravity and more.
A prompt/skill package — nothing to install beyond adding it to your AI tool.
mkdir -p ~/.claude/skills/headroomlabs-ai-headroom && curl -fsSL https://workflowstacks.com/api/skills/headroomlabs-ai-headroom/claude-skill -o ~/.claude/skills/headroomlabs-ai-headroom/SKILL.mdOpens the app with this repo with the prompt ready to go — no copy-paste needed.
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