What is the output format of the audit?

The skill generates a structured report including an executive summary, numerical scores for narrative and code quality, and specific line-by-line recommendations.

Can I use this for non-Anthropic notebooks?

While optimized for Anthropic Cookbook standards, the structural and technical checks are applicable to any high-quality technical tutorial or educational notebook.

What standards does this skill use for auditing?

It follows a specific rubric based on the Diataxis framework, focusing on action-oriented learning, proper setup patterns, and clear problem-focused introductions.

Does it scan for security vulnerabilities?

Yes, it automatically runs detect-secrets to identify hardcoded API keys and credentials within the notebook files before the manual review begins.

Cookbook Quality Auditor

Name: Cookbook Quality Auditor
Author: Activer007

byActiver007

학습 및 문서화

Audits technical notebooks against specific style guides and security standards to ensure high-quality educational content.

소개

The Cookbook Quality Auditor is a specialized skill designed to streamline the review process for technical notebooks, specifically optimized for the Anthropic Cookbook standards. It integrates automated security scanning for hardcoded secrets with a structured manual review framework based on the Diataxis documentation methodology. By evaluating notebooks across narrative quality, technical accuracy, and actionability, this skill helps maintainers and contributors produce professional-grade tutorials that focus on solving real-world problems rather than just demonstrating features.

주요 기능

Structure validation against problem-focused learning objectives (TLOs/ELOs)
Standardized scoring rubric for narrative, code, and technical accuracy
0 GitHub stars
Automated security scanning for hardcoded API keys and credentials
Actionable report generation with prioritized improvement recommendations
Markdown conversion for easier code review and context management

사용 사례

Reviewing community contributions to technical documentation and cookbooks
Performing pre-publication security and quality checks on AI tutorials
Ensuring consistent educational standards across a library of Jupyter notebooks

소개

주요 기능

Structure validation against problem-focused learning objectives (TLOs/ELOs)
Standardized scoring rubric for narrative, code, and technical accuracy
0 GitHub stars
Automated security scanning for hardcoded API keys and credentials
Actionable report generation with prioritized improvement recommendations
Markdown conversion for easier code review and context management

사용 사례

Reviewing community contributions to technical documentation and cookbooks
Performing pre-publication security and quality checks on AI tutorials
Ensuring consistent educational standards across a library of Jupyter notebooks