init-ralph-research

To set up iterative research projects, this Skill initializes a dedicated directory and populates it with template files for specification, progress tracking, and assumption logging. This provides a consistent structure for documenting findings and planning steps immediately.

Starting AI-driven research loops requires structured documentation. This Skill creates predefined templates like spec.md and assumptions-and-questions.md, allowing you to immediately begin logging assumptions and configuring your iterative development process.

Yes, you can use topic-based naming for research project directories. When initializing a project for a topic like quantum computing advancements, the Skill creates a dedicated directory matching that name for your new research files.

No dependencies are required to initialize a research project with template files. The Skill operates independently to create your directory structure and populate files like progress.md, ensuring immediate documentation setup without external dependencies.

Automating research project setup generates three core template files: spec.md for specifications, progress.md for tracking, and assumptions-and-questions.md for logging assumptions. These files ensure consistent structure for iterative development.

Using a template structure for iterative development ensures consistent documentation and progress tracking across all projects. Unlike manual folders, it automatically provides predefined formats for specification and assumption logging, preventing missing files.