Air

AIR is a toolkit for optimizing tool outputs for AI consumption. The name is inspired by "accessibility retrofitting" - just as we retrofit infrastructure for accessibility, we need to retrofit developer tools for AI ergonomics.

The Problem

AI context windows are the scarcest resource. A 200K token window sounds large, but:

• A single npm install output can consume 2000+ tokens
• A test report can eat 5000+ tokens
• 50-96% of this is noise: progress bars, blank lines, redundant info

The real cost isn't tokens - it's attention dilution. Even with unlimited tokens, noise in context degrades AI reasoning quality.

The Solution

AIR intercepts tool outputs at the source, filtering noise before it enters the context window. Prevention, not cleanup.

Packages

Package	Description	npm
@10iii/air-core	Core compression library	npm
@10iii/air	CLI tool (air command)	npm
@10iii/air-oc-plugin	OpenCode plugin	npm
@10iii/air-openclaw-plugin	OpenClaw plugin	npm

Quick Start

CLI

# Install globally
npm install -g @10iii/air

# Read a file with compression
air read src/index.ts --skeleton

# Run a command with output compression  
air bash "npm install"

# Search with de-duplication
air grep "TODO" --include "*.ts"

# Test output compression
air test "npm test"

As a Library

import { ReadCompressor, BashCompressor, GrepCompressor } from '@10iii/air-core';

// Compress file content
const read = new ReadCompressor();
const result = read.compress(fileContent, { mode: 'skeleton' });

// Compress command output
const bash = new BashCompressor();
const result = bash.compress(output, { command: 'npm install' });

OpenCode Plugin

Add to your opencode.json:

{
  "plugin": ["@10iii/air-oc-plugin"]
}

Compressors

air-read

File content compression with intelligent truncation and structure awareness.

• skeleton: Extract function/class signatures only
• focused: Line range extraction with context
• truncate: Smart truncation with size limits

air-bash

Command output compression with pattern recognition.

• npm/pnpm/yarn install → progress removal, error extraction
• git operations → diff summarization
• Generic → intelligent truncation

air-grep

Search result compression with path de-duplication and context optimization.

air-test

Test output parsing for pytest, jest, go test, and more.

air-web

Web page content extraction with readability and markdown conversion.

air-ls

Directory listing with tree structure and smart filtering.

air-diff

Diff output compression with hunk summarization.

air-api

API response compression (JSON field filtering).

air-search

Web search with multiple engine support (DuckDuckGo, Bing, Baidu, Sogou).

Token Savings Rate (TSR)

Compressor	Typical TSR
air-test	90%+
air-bash	60-90%
air-read	50-80%
air-grep	40-60%
air-web	70-90%

Design Principles

1. Prevention > Cleanup - Filter at the source, not after
2. Rule-based > LLM-based - Deterministic compression, no API calls
3. Progressive Disclosure - Skeleton first, details on demand
4. Cross-platform - Works with any AI tool
5. Zero API Key - No external API dependencies

Requirements

• Node.js >= 18

License

MIT

Privacy

AIR collects anonymous usage statistics to improve the product. This includes compressed content hashes (not the content itself), compression ratios, and basic metadata. No personal data is collected. You can modify this via air config.

Contributing

Contributions welcome! Please read CONTRIBUTING.md and the Architecture docs first.