Squeez tool compresses bash output 90%+ to extend Claude Code context window

Squeez is a background hook that automatically compresses raw bash output before it reaches Claude Code, addressing context window overflow during longer tasks.
Problem and solution
When using Claude Code for extended tasks, raw bash output from commands like ps aux, docker logs, and git log can fill the context window with thousands of tokens of unnecessary noise. This causes the model to lose track of ongoing work mid-session. Squeez compresses this output automatically without changing your workflow.
Performance and installation
The tool achieves an average reduction of 92.8% across 19 common commands. This compression helps sessions last longer and maintains response coherence further into tasks.
Installation options:
- One-line install:
curl -fsSL https://raw.githubusercontent.com/claudioemmanuel/squeez/main/install.sh | sh - Available on npm and crates.io
How it works
Squeez runs as a background hook that intercepts bash output before it reaches Claude Code. It identifies verbose command output and applies compression algorithms to reduce token usage while preserving essential information. The tool specifically targets common development commands known to generate excessive output.
📖 Read the full source: r/ClaudeAI
👀 See Also

Memora v0.2.25 MCP Server: 5× Faster Writes on D1 Database
Memora v0.2.25, an MCP server for Claude persistent memory, achieves 5× faster writes on Cloudflare D1 with memory_create dropping from 10s+ to ~1.8s and memory_update from 10s+ to ~1.1s per call.

ANE Optimization Through Phone-Steered AI Experiments Shows Kernel Fusion Benefits
A developer ran 55 experiments on Apple Neural Engine optimization, steering the process from their phone using Claude for brainstorming. Key improvements included fusing 3 ANE kernels into 1 mega-kernel, reducing validation loss from 3.75 to 2.49 and step time from 176ms to 96ms.

Open-Source SDK for AI Knowledge Work
ClioAI's kw-sdk offers a structured framework for AI agents performing knowledge work, implementing a self-verifying loop with task briefing, rubric creation, and verification.

Publicly Hosted MCP Servers for Health, Academic, and Government Data
A developer has built and publicly hosts 14 MCP servers providing access to CDC datasets, clinical trials, FDA data, academic publications, congressional information, weather data, and other utilities. These servers require no setup, API keys, or local installation.