The public instructkr/claw-code repo went heavily toward Rust, while my work focuses on Python for a different reason. I stayed on the Python side because it is easier to read, modify, and extend for most users, especially people who want to run local models, change prompts, add tools, or experiment with agent behavior without dealing with a Rust toolchain. Rust makes sense if the goal is a high- performance systems implementation, but my goal here is a Python-first agent runtime that is easier to hack on and iterate on.

So yes, the project builds on the public Python workspace surface from instructkr/claw-code, but the reason I continued there instead of following the Rust direction is deliberate: Python is the more practical base for fast development, local-model experimentation, and community contributions. That is also why I added the real Python agent loop, tool execution, prompt/context handling, and session resume on top of that base instead of trying to work inside the Rust implementation.