learning-code_consistency

What problem does it solve?

This Skill helps ensure that code files (.py, .ipynb) and their corresponding documentation (.md) are consistent, preventing errors and improving the reliability of lab assignments and submissions.

Core Features & Use Cases

• Code Logic Verification: Compares Python scripts and Jupyter notebooks to ensure identical function definitions, logic, and output statements.
• Documentation Alignment: Validates that Markdown documentation accurately reflects code output, including statistical values and image references.
• Image Reference Check: Confirms that all images referenced in documentation exist and use correct relative paths.
• Use Case: Before submitting a lab assignment, use this Skill to automatically check if your Python script's calculations match the results presented in your report and if all necessary figures are correctly embedded.

Quick Start

Run the learning-code_consistency skill to check the alignment between main.py, report.md, and all images in the images folder.