Can it analyze Jupyter Notebooks?

Yes, it prioritizes Jupyter Notebooks (.ipynb) as they often contain the primary analysis workflow, but it also scans .py, .R, and .mat files.

What documents does this skill generate?

It produces two main files: 'notes/code-analysis.md', containing the detailed technical findings, and 'drafts/methods.md', which is the formatted Methods section.

What prerequisites are needed to run Code Analyzer?

Code Analyzer requires a 'scope.md' file for context and a cloned repository in the 'code/' directory. It also benefits from having ethics documentation for cross-referencing.

How does it handle ambiguous logic in my code?

It follows a 'No Silent Assumptions' principle. If the purpose of a script or a hardcoded parameter is unclear, the skill will pause and ask you for clarification before documenting it.

Does it provide statistical verification?

Yes, it includes a statistical review step that validates the appropriateness of identified tests and checks for common issues like multiple comparison handling.

Code Analyzer

Name: Code Analyzer
Author: sxg

bysxg

0•

Data Science & ML

Analyzes GitHub repositories to extract computational methodologies and automatically draft scientific Methods sections.

Code Analyzer is a specialized skill within the writer plugin designed to bridge the gap between source code and technical documentation. It systematically scans repository structures to identify key analysis scripts, notebooks, and data pipelines, extracting essential details regarding preprocessing, statistical tests, and machine learning models. By enforcing a 'no silent assumptions' policy, the skill ensures that all documented methods are verified by the user, resulting in a high-fidelity Methods section that is cross-referenced with project ethics and validated by a statistical review process.

Key Features

01Automated repository scanning and key file identification (Notebooks, Python, R, MATLAB)

020 GitHub stars

03Extraction of data processing, statistical analysis, and ML pipelines

04Integrated statistical reviewer checkpoint for methodological validation

05Interactive clarification system to resolve ambiguous parameters or logic

06Ethics cross-referencing to ensure code aligns with approved procedures

Use Cases

01Drafting the Methods section of an academic paper directly from a research repository

02Auditing codebases to ensure implemented procedures match ethical protocol descriptions

03Generating technical documentation for complex data science workflows

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add sxg/science code-analyzer

For use in Claude.ai and ChatGPT

Download Skill