Link Assistant Agent

A minimal, public domain AI CLI agent compatible with OpenCode's JSON interface

🚨 SECURITY WARNING: 100% UNSAFE AND AUTONOMOUS 🚨

This agent operates with ZERO RESTRICTIONS and FULL AUTONOMY:

• ❌ No Sandbox - Complete unrestricted file system access
• ❌ No Permissions System - No approval required for any actions
• ❌ No Safety Guardrails - Can execute ANY command with full privileges
• ⚠️ Autonomous Execution - Makes decisions and executes actions independently

ONLY use in isolated environments (VMs, Docker containers) where AI agents can have unrestricted access. NOT SAFE for personal computers, production servers, or systems with sensitive data.

Implementations

This repository contains two implementations of the agent:

Implementation	Status	Package Manager	Install Command
JavaScript/Bun	Production Ready	npm	bun install -g @link-assistant/agent
Rust	Work in Progress	cargo	cargo install agent (when published)

Both implementations aim to be fully compatible with OpenCode's run --format json mode.

JavaScript/Bun Implementation

The primary implementation, feature-complete and production-ready. Requires Bun >= 1.0.0.

# Install
bun install -g @link-assistant/agent

# Usage
echo "hi" | agent

See js/README.md for full documentation including:

• Complete CLI options reference
• Model selection examples
• Session resume functionality
• MCP (Model Context Protocol) configuration
• JSON output standards (OpenCode and Claude formats)

Rust Implementation

The Rust implementation provides core functionality but is still under active development.

# Build from source
cd rust
cargo build --release
./target/release/agent -p "hello"

See rust/README.md for full documentation.

Project Vision

We're creating a slimmed-down, public domain version of OpenCode CLI focused on the "agentic run mode" for use in virtual machines, Docker containers, and other environments where unrestricted AI agent access is acceptable. This is not for general desktop use - it's for isolated environments where you want maximum AI agent freedom.

OpenCode Compatibility: We maintain 100% compatibility with OpenCode's JSON event streaming format, so tools expecting opencode run --format json --model opencode/grok-code output will work with our agent-cli.

Features

• JSON Input/Output: Accepts JSON via stdin, outputs JSON event streams (OpenCode-compatible)
• Plain Text Input: Also accepts plain text messages (auto-converted to JSON format)
• Unrestricted Access: Full file system and command execution access (no sandbox, no restrictions)
• Tool Support: 13 tools including websearch, codesearch, batch - all enabled by default
• Flexible Model Selection: Supports OpenCode Zen, Claude OAuth, Groq, and more - see MODELS.md
• Public Domain: Unlicense - use it however you want

Quick Start

Plain text (easiest):

echo "hi" | agent

Simple JSON message:

echo '{"message":"hi"}' | agent

With custom model:

echo "hi" | agent --model opencode/grok-code

Direct prompt mode:

agent -p "What is 2+2?"

See js/README.md for more usage examples including model selection, session resume, and JSON output standards.

Supported Tools

All 13 tools are enabled by default with no configuration required. See TOOLS.md for complete documentation.

File Operations

• read - Read file contents
• write - Write files
• edit - Edit files with string replacement
• list - List directory contents

Search Tools

• glob - File pattern matching (**/*.js)
• grep - Text search with regex support
• websearch ✨ - Web search via Exa API (no config needed!)
• codesearch ✨ - Code search via Exa API (no config needed!)

Execution Tools

• bash - Execute shell commands
• batch ✨ - Batch multiple tool calls (no config needed!)
• task - Launch subagent tasks

Utility Tools

• todo - Task tracking
• webfetch - Fetch and process URLs

✨ = Always enabled (no experimental flags or environment variables needed)

Architecture

This agent reproduces OpenCode's run --format json command architecture:

• Streaming JSON Events: Real-time event stream output
• Event Types: tool_use, text, step_start, step_finish, error
• Session Management: Unique session IDs for each request
• Tool Execution: Tools with unrestricted access
• Compatible Format: Events match OpenCode's JSON schema exactly

MCP (Model Context Protocol) Support

The agent supports the Model Context Protocol (MCP), allowing you to extend functionality with MCP servers such as browser automation via Playwright.

Quick setup for Playwright MCP:

agent mcp add playwright npx @playwright/mcp@latest

See js/README.md for full MCP documentation including:

• Available Playwright tools (22+ browser automation capabilities)
• MCP server configuration
• Usage examples

Documentation

Document	Description
MODELS.md	Available models, providers, and pricing
TOOLS.md	Complete tool documentation
EXAMPLES.md	Usage examples for each tool
TESTING.md	Testing guide
js/README.md	JavaScript/Bun implementation (full docs)
rust/README.md	Rust implementation

Files

JavaScript Implementation (js/)

• js/src/index.js - Main entry point with JSON/plain text input support
• js/src/session/ - Session management and agent implementation
• js/src/tool/ - Tool implementations
• js/tests/ - Comprehensive test suite
• js/package.json - npm package configuration

Rust Implementation (rust/)

• rust/src/main.rs - Main entry point
• rust/src/cli.rs - CLI argument parsing
• rust/src/tool/ - Tool implementations
• rust/Cargo.toml - Cargo package configuration

Reference Implementations

This repository includes official reference implementations as git submodules to provide best-in-class examples:

• original-opencode - OpenCode - The original OpenCode implementation we maintain compatibility with
• reference-gemini-cookbook - Google Gemini Cookbook - Official examples and guides for using the Gemini API
• reference-gemini-cli - Google Gemini CLI - Official AI agent bringing Gemini directly to the terminal
• reference-qwen3-coder - Qwen3-Coder - Official Qwen3 code model from Alibaba Cloud

To initialize all submodules:

git submodule update --init --recursive

These reference implementations provide valuable insights into different approaches for building AI agents and can serve as learning resources for developers working with this codebase.

License

Unlicense (Public Domain)