What scoring criteria are used in the audit?

Notebooks are scored on a 20-point scale across four dimensions: Narrative Quality, Code Quality, Technical Accuracy, and Actionability & Understanding.

What is a Cookbook Audit?

A Cookbook Audit is a structured evaluation process that checks Jupyter Notebooks against a specific style guide and technical rubric to ensure they are educational, secure, and functional.

Does it check for specific AI model names?

Yes, the auditor ensures notebooks use current and valid model names like claude-sonnet-4-5 and follows the pattern of defining them as constants at the top of the file.

How does this skill handle security?

The skill automatically runs a validation script that uses detect-secrets to scan for hardcoded API keys and credentials within the notebook before you begin the manual review.

Why does the skill convert notebooks to markdown?

Converting .ipynb files to markdown in a temporary folder allows for a cleaner review process by focusing on the code and narrative while excluding heavy outputs that can clutter the context.

Cookbook Auditor

Name: Cookbook Auditor
Author: Microck

byMicrock

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学習とドキュメンテーション

Audits Jupyter Notebooks against professional style guides and technical rubrics to ensure high-quality educational content.

概要

The Cookbook Auditor skill automates and standardizes the review process for technical tutorials and educational notebooks. It integrates automated technical checks, including secret detection and dependency validation, with a comprehensive manual review framework based on the Diataxis documentation methodology. By evaluating narrative flow, code quality, and learning objectives, this skill helps developers create actionable, professional-grade technical content that prioritizes both practical execution and conceptual understanding while ensuring adherence to modern AI model naming conventions and security standards.

主な機能

Markdown conversion for streamlined review of code and narrative context
81 GitHub stars
Consistency checks for environment setup and model constant definitions
Structured audit reports with executive summaries and prioritized fixes
Objective scoring rubric covering narrative, code, accuracy, and actionability
Automated technical validation and credential scanning for .ipynb files

ユースケース

Reviewing technical tutorials for documentation quality and consistency
Ensuring notebooks follow best practices before public repository release
Auditing AI-focused cookbooks for security vulnerabilities and API accuracy

概要

主な機能

Markdown conversion for streamlined review of code and narrative context
81 GitHub stars
Consistency checks for environment setup and model constant definitions
Structured audit reports with executive summaries and prioritized fixes
Objective scoring rubric covering narrative, code, accuracy, and actionability
Automated technical validation and credential scanning for .ipynb files

ユースケース

Reviewing technical tutorials for documentation quality and consistency
Ensuring notebooks follow best practices before public repository release
Auditing AI-focused cookbooks for security vulnerabilities and API accuracy