No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by claudioemmanuel · MCP Server · ★ 200
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is squeez safe to install? View the security audit →
squeez End-to-end token optimizer for Claude Code, GitHub Copilot CLI, OpenCode, Gemini CLI, and OpenAI Codex CLI. Compresses bash output up to 95%, collapses redundant calls, and injects a terse prompt persona — automatically, with zero new runtime dependencies. Install Three methods — all produce the same result (binary at , hooks registered). curl (recommended) Windows: requires Git Bash. Run the command above inside Git Bash — PowerShell/CMD are not supported. npm / npx bash Install globally npm install -g squeez Or run once
| Stars | 200 |
| Forks | 23 |
| Language | Rust |
| Category | MCP Server |
| License | Apache-2.0 |
| Quality Score | 68.6204009013026/100 |
| Last Updated | 2026-09-11 |
| Created | 2026-03-23 |
| Platforms | claude-code, cli, codex, gemini, mcp, rust |
| Est. Tokens | ~30k |
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squeez is Hook-based token compressor for 5 AI CLI hosts (Claude Code, Copilot CLI, OpenCode, Gemini CLI, Codex CLI). Up to 95% bash compression, signature-mode for code reads, cross-call dedup, MCP server, sel. It is categorized as a MCP Server with 200 GitHub stars.
squeez is primarily written in Rust. It covers topics such as ai-cli, bash-hook, claude-code.
You can find installation instructions and usage details in the squeez GitHub repository at github.com/claudioemmanuel/squeez. The project has 200 stars and 23 forks, indicating an active community.
squeez is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to squeez on Agent Skills Hub include lissom-skills, agent-sessions, memorix. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: