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 frameworks
Important
🚧🦀 Rust Port in Progress
A full Rust rewrite is currently underway on the dev/rust branch.
This effort focuses on building a faster, memory safe, and production ready harness runtime. I'm collaborating with a close contributor to accelerate development, and the rust version will be committed within the next 24–48 hours. Stay tuned this will become the core direction of the project.
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
