I wrote an MCP based on that technique - https://github.com/whs/mcp-chinesewall

Basically to avoid the ambiguity of training LLM from unlicensed code, I use it to generate description of the code to another LLM trained from permissively licensed code. (There aren't any usable public domain models I've found)

I use it in real world and it seems that the codegen model work 10-20% of the time (the description is not detailed enough - which is good for "clean room" but a base model couldn't follow that). All models can review the code, retry and write its own implementation based on the codegen result though.

Nice. Any chance you could put in some attributions and credits in your paper? https://orcid.org/0009-0007-3955-9994