Better harness tools, focused on execution not merely storing the archive of leaked Claude Code
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Claw Codes is actively being rewritten into a high-performance agent framework
Building better harness tools — focused on execution, not just structure or storage.
Important
A Rust-based core is currently in development and will serve as the foundation of the next phase of Claw Codes.
This core is designed to:
- improve execution speed
- ensure memory safety
- enable low-level system control
- support scalable agent workflows
Alongside this, a Python layer is being developed to handle orchestration, rapid iteration, and higher-level abstractions.
The system is actively evolving and will undergo continuous architectural improvements.
Claw Codes is not a finished product.
It is a system under active development, with a focus on:
- 🦀 Rust-based core engine (in progress)
- 🐍 Python orchestration layer
- ⚙️ Improved execution pipeline
- 🧩 Modular system architecture
- 🔍 Continuous reverse engineering and refinement
- 🧠 Exploration of agent-based system design
Each part of the system is being designed with performance, clarity, and scalability in mind.
The goal of Claw Codes is to evolve into a foundation for:
- intelligent execution systems
- autonomous workflows
- agent-driven applications
- modular AI tooling infrastructure
Rather than focusing solely on generation, the system prioritizes:
Execution, control, and structured automation
- Multi-agent task execution
- Tool-based architecture
- CLI-first interface
- Modular and extensible system design
- Local and remote execution support
- Structured workflow orchestration
- Plugin-ready architecture
Claw Codes is being designed with:
- Clear separation between components
- Defined boundaries between tools and agents
- Extensibility at every layer
- High-performance core (Rust)
- Flexible orchestration layer (Python)
- Core architecture stabilization
- Rust execution engine
- Python orchestration layer
- Tool system expansion
- Multi-agent coordination layer
- Plugin ecosystem
- Performance optimization
- CLI improvements
- Documentation expansion
This project involves deep exploration into:
- agent execution systems
- orchestration patterns
- CLI-based AI workflows
- tool integration design
- system-level architecture
The implementation is being rebuilt independently with a focus on clean design and long-term scalability.
This repository started gaining traction shortly after I backed up the code within a few hours of discovery.
Contributions are welcome.
Ways to contribute:
- Improve system architecture
- Add new features
- Optimize performance
- Fix issues
- Suggest improvements
- Share ideas and feedback
Claw Codes is currently:
- under active development
- not yet stable
- continuously evolving
Expect frequent updates, restructuring, and improvements as the system matures.
Claw Codes is an independent, clean-room implementation and is not affiliated with, endorsed by, or maintained by any organization or company referenced in this project.
This repository is intended strictly for:
- Educational purposes
- Software architecture exploration
- Defensive and research-driven development
- Experimental AI system design
No proprietary claims are made over any external systems or codebases.
0xKarl: https://x.com/0xKarl
For questions, discussions, or collaboration:
👉 Telegram: https://t.me/Carl_Crypt
Feel free to reach out if you’re interested in:
- the architecture
- contributions
- ideas and improvements
- general discussions about AI systems