Snip

snip - Reduce LLM Token Usage by 60-90%

CLI proxy that filters shell output before it reaches your AI coding assistant's context window. Works with Claude Code, Cursor, Copilot, Gemini CLI, Windsurf, Cline, Codex, Pi, Grok Build, Kilo Code, Antigravity, OpenCode, OpenClaw, Aider, and any tool that runs shell commands.

AI coding agents burn tokens on verbose shell output that adds zero signal. A passing go test produces hundreds of lines the LLM will never use. git log dumps full commit metadata when a one-liner per commit suffices.

snip sits between your AI tool and the shell, filtering output through declarative YAML pipelines. Write a YAML file, drop it in a folder, done. The extensible LLM token optimizer: filters are YAML data files, not compiled code.
Measured on a real Claude Code session — 128 commands, 2.3M tokens saved.

Quick Start

How It Works

Before — Claude Code sees this (275 tokens):

After — snip returns this (8 tokens):

That's 97% fewer tokens, measured on this very repository. The filter injects -json and counts individual test results, so the LLM gets more signal — 1125 tests passed, not just 18 packages — in a fraction of the space.

No filter match? The command passes through unchanged — zero overhead.

Token Savings by Command

Stop wasting tokens on noise. snip gives the LLM the same signal in a fraction of the context window.

Installation

Homebrew (recommended)

From GitHub Releases

Download the latest binary for your platform from Releases.

From source

Or build locally:

make install and make install-lite use the first available destination:
an explicit GOBIN, go env GOBIN, or the first go env GOPATH entry plus
/bin. Use make upgrade or make upgrade-lite to replace the resolved
snip on PATH instead. An explicit GOBIN overrides the…