How does this help with data quality?

The skill assesses naming conventions, identifies missing tests, and checks for primary key definitions, providing actionable recommendations to improve model robustness.

Can it generate documentation automatically?

Yes, it triggers 'dbt docs generate' and compiles the resulting metadata into a structured Markdown analysis report within your repository.

What specific metadata does the skill analyze?

It primarily reads dbt manifest and catalog JSON files to extract model definitions, relationships, primary keys, and dependency counts.

Does this skill only work with DBT projects?

While specifically optimized for DBT workflows using manifest and catalog files, its logic is designed to be the foundation for general database structure analysis and metadata reporting.

Data Structure & DBT Analyzer

Name: Data Structure & DBT Analyzer
Author: nerver111

bynerver111

0•

数据库管理

Conducts comprehensive database reverse engineering and metadata analysis to generate actionable data lineage reports.

The Data Structure Analyzer is a specialized Claude Code skill designed for data engineers and developers to automatically audit, document, and optimize database schemas. It excels in DBT (Data Build Tool) environments by automating project health diagnostics, metadata extraction from manifest files, and the generation of detailed lineage reports. By programmatically inspecting model relationships and dependency structures, it provides a holistic overview of data layers—from staging to marts—helping teams identify data quality gaps and maintain clean, scalable data models.

主要功能

01Structured analysis report generation with optimization recommendations

02Comprehensive data lineage and dependency mapping across model layers

03Automated DBT project health diagnostics and documentation generation

04Data quality assessment and naming convention auditing

05Deep metadata analysis via manifest and catalog file inspection

060 GitHub stars

使用场景

01Onboarding to legacy data projects with complex or undocumented schemas

02Auditing DBT project structures for best practices and dependency optimization

03Generating automated data lineage reports for stakeholder documentation and compliance

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add nerver111/git-skill-test analyze-data-structure

For use in Claude.ai and ChatGPT

主要功能

01Structured analysis report generation with optimization recommendations

02Comprehensive data lineage and dependency mapping across model layers

03Automated DBT project health diagnostics and documentation generation

04Data quality assessment and naming convention auditing

05Deep metadata analysis via manifest and catalog file inspection

060 GitHub stars

使用场景

01Onboarding to legacy data projects with complex or undocumented schemas

02Auditing DBT project structures for best practices and dependency optimization

03Generating automated data lineage reports for stakeholder documentation and compliance

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add nerver111/git-skill-test analyze-data-structure

For use in Claude.ai and ChatGPT