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⚡ Claw-Code-Go

The Go-Powered AI Agent Harness — Built for Real Execution, Not Just Demos.

⭐ The Go implementation of next-generation AI agent systems
⭐ Inspired by the architecture behind modern AI coding agents
⭐ Built for performance, extensibility, and real-world automation


🔥 Why This Project Exists

In 2026, the internal architecture of modern AI coding agents became publicly understood.

What emerged was not just a tool —
but a new paradigm:

👉 AI is no longer just generating text — it is executing systems.

Projects like claw-code demonstrated:

  • Tool orchestration
  • Multi-agent execution
  • Runtime context management
  • Plugin-based architectures

These systems represent the operating system of AI agents. :contentReference[oaicite:0]{index=0}


💡 What is Claw-Go?

Claw-Go is a clean-room Go implementation of an AI Agent Harness.

It is NOT:

  • ❌ a wrapper around an LLM
  • ❌ a prompt engineering demo
  • ❌ a toy chatbot

It IS:

✅ A runtime system for AI agents
✅ A tool execution engine
✅ A foundation for autonomous systems


🧠 Core Philosophy

LLM is NOT the system. LLM is just the brain.

The system = Runtime + Tools + Memory + Orchestration

🏗 Architecture Overview

             ┌──────────────────────┐
             │        CLI           │
             └─────────┬────────────┘
                       ↓
             ┌──────────────────────┐
             │      Commands        │
             └─────────┬────────────┘
                       ↓
             ┌──────────────────────┐
             │      Query Layer     │
             └─────────┬────────────┘
                       ↓
     ┌────────────────────────────────────┐
     │ Runtime | Plugins | Tools | MCP    │
     └────────────────────────────────────┘
                       ↓
             ┌──────────────────────┐
             │    LLM Providers     │
             └──────────────────────┘

⚙️ Project Structure

claw-go/
├── cmd/claw              # CLI entry
├── internal/
│   ├── app               # Command dispatcher
│   ├── models            # Shared data structures
│   ├── manifest          # System manifest
│   ├── query             # Query + output layer
│   ├── commands          # Command registry
│   ├── tools             # Tool system
│   ├── runtime           # Agent runtime core
│   ├── plugins           # Hook pipeline
│   ├── providers         # LLM abstraction
│   └── mcp               # MCP registry
└── go.mod

🚀 Quick Start

git clone https://github.com/shirdonl/claw-code-go.git
cd claw-code-go

go run ./cmd/claw summary
go run ./cmd/claw manifest
go run ./cmd/claw subsystems --limit 16
go run ./cmd/claw commands --limit 10
go run ./cmd/claw tools --limit 10
go run ./cmd/claw parity-audit

🧩 Core Modules

🧠 Runtime Session lifecycle Context management Execution loop

🔧 Tool System

Plugin-based architecture Dynamic tool invocation Extensible capabilities

🔌 Plugins

pipeline := plugins.New()
pipeline.Use(func(input string) string {
    return "[hook]" + input
})

Hook pipeline Middleware injection Event processing

🌐 Providers

type Provider interface {
    Generate(prompt string) string
}

Multi-LLM support OpenAI / DeepSeek / Local models Streaming-ready

🔗 MCP (Model Context Protocol)

External tool integration Registry-based architecture Future: distributed agent systems

⚡ Why Go?

Most agent frameworks are:

Python → slow, hard to scale TypeScript → complex runtime

Claw-Go is built for:

⚡ High performance 🧵 Concurrency (goroutines) 🔒 Memory safety 🚀 Production systems 🧪 Current Status

Feature Status

Feature Status
CLI ✅ Ready
Commands ✅ Ready
Tool System 🟡 Basic
Runtime 🟡 Skeleton
Plugins 🟡 Basic
Providers 🟡 Mock
MCP 🟡 Skeleton

🚧 Roadmap

Full Agent Runtime Loop Tool Auto Invocation Multi-Agent System DeepSeek / OpenAI Integration Streaming Execution Web UI

🔥 Example (Future)

claw run "Analyze this repository and generate documentation"

🌍 Vision

We believe:

The future of software is AI-native systems

Claw-Go aims to become:

The Go LangGraph The Go AutoGen The Agent OS for Developers

⚠️ Disclaimer

This project:

Does NOT contain proprietary code Is a clean-room implementation Is not affiliated with any original proprietary system ⭐ Star History

If this project helps you:

👉 Give it a ⭐ 👉 Share it 👉 Build something crazy with it

🤝 Contributing

PRs welcome.

We are building:

The next generation of AI systems.

🧠 Final Thought

LLMs are not the revolution. Systems built around them are.

About

Better Harness Tools that make real things done. Built in Go using oh-my-codex.

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