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Review R analysis code for methodological issues

Community

Ensure statistical correctness in AI-generated R code reviews.

Data & Analytics#code review#error detection#methodology#bioinformatics#r#statistical analysis
Authordanmaclean
Version1.0.0
Installs0

System Documentation

What problem does it solve?

This Skill helps users identify and evaluate common methodological issues in R code produced or analyzed by AI, preventing errors and misinterpretations.

Core Features & Use Cases

  • Methodological Assessment: Detects fabricated functions, mistaken defaults, and domain-specific misunderstandings in R scripts.
  • Quality Verification: Checks for consistency with best practices outlined in the lab's reference documents.
  • Use Case: Assist bioinformatics analysts in reviewing AI-generated R code for correctness before deployment or publication, ensuring reliable results.

Quick Start

Verify the R code by providing it to the skill for an automated review of potential errors and inconsistencies.

Dependency Matrix

Required Modules

None required

Components

Standard package

💻 Claude Code Installation

Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.

Please help me install this Skill:
Name: Review R analysis code for methodological issues
Download link: https://github.com/danmaclean/ai_workshop/archive/main.zip#review-r-analysis-code-for-methodological-issues

Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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