Squeezes tool output, logs, files and long chats before they reach the model, so Claude Code, Codex and other agents spend fewer tokens with the same answers.
In short: Squeezes tool output, logs, files and long chats before they reach the model, so Claude Code, Codex and other agents spend fewer tokens with the same answers. It is a free skill for people who use Claude Code, Codex or Cursor and want help with coding agent skills.
Checked on · Added
| Agent / tool | Access / cost | Link |
|---|---|---|
| Claude Code | Paid Claude plan or API | claude.com/claude-code |
| Codex | ChatGPT plan or API | openai.com/codex |
| Cursor | Free tier + paid | cursor.com |
| GitHub repo | Open source · ★ 76.9k | headroomlabs-ai/headroom |
Image: from the GitHub README, shown with credit.
Images from the project README on GitHub.
pip install "headroom-ai[all]" headroom wrap claude
Install command copied from the project README. Check the README for the latest version.
Squeezes tool output, logs, files and long chats before they reach the model, so Claude Code, Codex and other agents spend fewer tokens with the same answers.
Headroom compresses everything your AI agent reads (tool outputs, logs, RAG chunks, files and chat history) before it reaches the model. Compression runs on your machine; no prompt or file content is sent anywhere to be…
Short excerpt from the README of headroomlabs-ai/headroom. Read the full README on GitHub.
Your agent's traffic goes through a local proxy on your machine. An anonymous usage beacon is on by default (no prompts or code, per the README); turn it off with HEADROOM_TELEMETRY=off. First run downloads a compression model from Hugging Face. Different from Context Mode, which keeps tool output out of the chat; Headroom compresses what does go in.
Squeezes tool output, logs, files and long chats before they reach the model, so Claude Code, Codex and other agents spend fewer tokens with the same answers.
It works with Claude Code, Codex and Cursor. The code is on GitHub at headroomlabs-ai/headroom.
Free & open source (Apache 2.0); compression runs on your own computer. A paid Enterprise plan for teams exists, but you don't need it. License: Apache-2.0.
Run the install command from the README: “pip install "headroom-ai[all]"”. Check the README on GitHub for the latest version, then follow the steps on this page.
We read 905 instruction and code files in the repo and found no red flags. That is not a guarantee, so review anything that runs commands on your machine.
All credit to the original authors. We rewrite in our own words and link back. Something wrong? Report it.
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