What problem does it solve?
It quickly bootstraps a new Claude Code project by generating the essential guidance and research artifacts, so you start from a clean, well-structured baseline instead of starting blank and guessing what to write.
Core Features & Use Cases
- Signal-driven project blueprinting: auto-detects language, package manager, repo/team/shared context, and project type (ML research vs web app) before asking questions.
- Dry-run first, then write: previews exactly which files will be created and lets you edit/skip/cancel per file to prevent unwanted changes.
- Minimal default artifacts for Claude Code: generates CLAUDE.md plus the right supporting files (research-notes.md and a project manifest like pyproject/package.json), with optional personal/team/public handling and safe gitignore additions.
- ML research / Web app profiles: loads tailored question sets and reference templates for deeper setup (e.g., red-line constraints, data/compute/targets for ML).
Quick Start
Run init-project to bootstrap a new project blueprint with dry-run previews first, then approve the generated files.