code-review

Review R and Python research scripts against an 11-category scorecard.

127|22|Updated Feb 20, 2026

Search Tags:#quality assurance #code review #Python #reproducibility #R #research scripts #academic code

Ready to run

npx skills add https://github.com/flonat/claude-code-flonat --skill code-review-flonat

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: code-review
Source: https://github.com/flonat/claude-code-flonat/tree/main/skills/code-review
Command: npx skills add https://github.com/flonat/claude-code-flonat --skill code-review-flonat

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill automates the rigorous quality assurance of research scripts, ensuring reproducibility, clarity, and correctness, thereby reducing errors and improving the reliability of research findings.

Core Features & Use Cases

Comprehensive Scorecard: Evaluates code across 11 critical categories including reproducibility, script structure, output hygiene, function quality, domain correctness, figure quality, data persistence, dependencies, and language-specific checks (R/Python).
Report-Only: Never modifies source files, providing objective feedback.
Use Case: Before submitting a paper, use /code-review on your R and Python analysis scripts to generate a CODE-REVIEW-REPORT.md that identifies potential issues in reproducibility, estimator correctness, and figure presentation.

Quick Start

Run a quality review on the script located at 'analysis/main.R'.

Frequently Asked Questions about code-review

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I perform a code review for research scripts in R and Python?▼

Perform a research script code review by evaluating R and Python files against an 11-category scorecard covering reproducibility, structure, correctness, and presentation. This process generates a detailed report file without modifying the original source code.

What is the best way to check reproducibility and quality in academic code before publication?▼

Check academic code reproducibility and quality by running an automated review that assesses script structure, output hygiene, and figure presentation. It produces a markdown report identifying potential issues in estimator correctness and reproducibility before paper submission.

Can I use this code review tool to automatically fix issues in my Python analysis scripts?▼

No, this code review tool cannot automatically fix issues in your Python analysis scripts. It operates in a report-only mode, providing objective feedback by generating a markdown review file while leaving your original source files completely unmodified.

Does the research script quality assurance scorecard evaluate function quality and dependencies?▼

Yes, the research script quality assurance scorecard evaluates function quality and dependencies. It also assesses data persistence, domain correctness, figure quality, output hygiene, and language-specific checks for R and Python.

How do I generate a reproducibility report for my analysis scripts without altering the source files?▼

Generate a reproducibility report by running a report-only quality review on your analysis scripts. The process automatically creates a markdown file containing objective feedback on script structure and correctness without altering your source files.