Review data science blog posts and generate structured referee reports.
npx skills add https://github.com/cmg777/starter-academic-v501 --skill referee-post
Please help me install this Agent Skill. Skill: referee-post Source: https://github.com/cmg777/starter-academic-v501/tree/main/.claude/skills/referee-post Command: npx skills add https://github.com/cmg777/starter-academic-v501 --skill referee-post
This Skill provides a rigorous, expert review of data science blog posts, ensuring they meet high standards for correctness, clarity, and pedagogical value.
Use the referee-post skill to review the post with slug 'python_doubleml'.
High-intent search queries and answers about installing and using this skill.
You can review a data science blog post by evaluating code correctness, mathematical rigor, writing clarity, and pedagogical value, which produces a structured referee report with specific suggestions and severity ratings.
Academic rigor in data science tutorials ensures mathematical equations and code interpretations are correct, maintaining high pedagogical value and preventing readers from learning inaccurate methodologies.
Yes, automated review tools can assess data science tutorials for beginner accessibility, narrative flow, and writing clarity, generating a structured report with actionable pedagogical feedback and improvement suggestions.
Evaluating code quality in a data science blog post involves analyzing code correctness, verifying data interpretations, and ensuring explanations are accessible for beginners to yield a comprehensive quality assessment.
Automated review tools for data science posts may lack deep contextual understanding of niche datasets, potentially missing subtle domain-specific interpretation errors that require human expert evaluation.
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