star-code-architect

Bootstrapping a research codebase involves searching, scoring, and cloning reference implementations from GitHub to establish a target architecture. This skill automates that process to create consistent directory layouts for AI research projects.

Conservative rebranding safely renames packages and metadata while preserving runtime-critical strings and provenance. This ensures the research codebase remains functional and its origins are tracked after migration.

Generating architectural documentation involves creating an authoritative codearc.md spec and migration plan. This ensures consistent code placement and organization across the entire research codebase.

Bootstrapping does not strictly require an existing GitHub URL. You can run the skill with just a plan name to survey existing code and establish a target architecture for your AI research project.

Provenance tracking is needed to maintain the origin and history of reference implementations during automated bootstrapping and conservative rebranding. It ensures your AI research project retains authoritative links to its source code.

Automated codebase scaffolding is limited to establishing directory layouts and architectural specs for AI research projects. It focuses on structural organization and does not execute or debug the research code itself.