plan-thesis-check

What problem does it solve?

This skill helps researchers verify that a given data plan — specifically the research method and the associated data fields — satisfies data requirements for modeling, analysis, and reproducibility. It ensures that the required fields exist or can be derived and that data usage aligns with methodological constraints, preventing missing data and incompatible transformations.

Core Features & Use Cases

• Data-method alignment: checks whether the research method fields are present in the data fields or can be computed from them.
• Auxiliary field awareness: identifies needed time, identifier, or grouping fields and flags any gaps for data preparation and coding.
• Feasibility & tooling: evaluates whether a Python-based implementation is practical and outlines the minimal data checklist for execution.
• Use Case: Given a method that requires time, id, and group indicators with up to five data fields, return a feasibility assessment and a data preparation plan.

Quick Start

Provide the research method and data field definitions to receive a feasibility assessment and a recommended data checklist.