Research Project Bootstrapper
File naming, versioning, and documentation that prevents chaos
Set up a research project the right way from day one: consistent folder structure, explicit naming conventions, versioning rules, and minimal documentation so "future you" (or collaborators) can understand the project without a tour.
PROMPT
Create a skill called "Research Project Bootstrapper". Ask for: - Project type (if unknown: unspecified) - Collaboration setting (solo/team; if unknown: unspecified) - Data sensitivity (human subjects? proprietary?) to influence naming/sharing advice - Preferred naming convention components (date-first vs descriptor-first) Output: 1) Folder structure proposal. 2) Naming convention rules + examples. 3) Versioning rules (semantic vs v01 vs date-based). 4) Minimal docs: README + data dictionary + changelog templates. Rules: - If a detail is unknown, mark it as unspecified rather than guessing.
How It Works
Unclear file naming and versioning creates a backlog of unorganized content.
This recipe sets up the scaffolding before the mess starts — or cleans up
an existing mess into something navigable.
What You Get
- Folder scaffold: data/raw, data/processed, analysis, figures, manuscripts, admin
- Naming convention template: YYYYMMDD_project_descriptor_v01.ext
- A CHANGELOG and README outline
- A data dictionary template (columns, units, provenance)
- Sensitivity-aware advice (human subjects, proprietary data)
Setup Steps
- Tell the Claw your project type (wet lab, computational, qualitative, mixed)
- Tell the Claw your collaboration mode (solo/team) and storage location
- The Claw generates a complete organization blueprint you can implement locally
Tips
- Great for new projects, but also useful for cleaning up existing ones
- Especially valuable when a student is graduating or handing off a project
- The data dictionary pays for itself the first time someone asks "what is this column?"