What are the prerequisites for using this skill?

You must have AWS credentials configured for Secrets Manager access and the 'boto3' and 'redshift-connector' Python packages installed.

Where does the skill save the exploration data?

All exploration results are saved to a markdown file at your repository root named after the schema and table (e.g., public_users_exploration.md).

Does this skill require specific database permissions?

Yes, the AWS IAM role or credentials used must have permissions to access AWS Secrets Manager (for credentials) and the underlying Redshift cluster.

Can I run custom queries with this skill?

Yes, Phase 2 of the workflow includes a 'Custom query' option that allows you to run specific SQL fragments against the selected table.

How do I trigger the Redshift exploration?

Use natural language phrases like 'explore redshift table', 'show me table structure', or 'redshift table schema' followed by the table name in schema.table format.

Redshift Table Explorer

Name: Redshift Table Explorer
Author: AI-Builder-Team

byAI-Builder-Team

•

데이터베이스 관리

Explores Amazon Redshift table schemas, metadata, and data distributions interactively to accelerate database discovery.

This skill enables developers and data analysts to quickly navigate Amazon Redshift databases by retrieving table structures, data types, and sample records directly within Claude Code. It automates the process of querying metadata, calculating column statistics like null counts and value distributions, and identifying unique values. By providing a structured workflow for data exploration—including the generation of markdown reports—it eliminates the need to switch between the terminal and external SQL clients when investigating database schemas or debugging data quality issues.

주요 기능

01Interactive schema discovery and metadata retrieval

022 GitHub stars

03Sample row extraction and custom SQL fragment execution

04Automated column statistics including counts, nulls, and distributions

05Automatic markdown report generation for exploration results

06Identification of DISTINCT values for specific database columns

사용 사례

01Onboarding to new database environments by exploring unknown table structures

02Validating table schemas and data types before writing complex ETL pipelines

03Investigating data quality issues like unexpected null percentages or value ranges

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add ai-builder-team/ai-builder-plugin-marketplace exploring-redshift-tables

For use in Claude.ai and ChatGPT

Download Skill

주요 기능

01Interactive schema discovery and metadata retrieval

022 GitHub stars

03Sample row extraction and custom SQL fragment execution

04Automated column statistics including counts, nulls, and distributions

05Automatic markdown report generation for exploration results

06Identification of DISTINCT values for specific database columns

사용 사례

01Onboarding to new database environments by exploring unknown table structures

02Validating table schemas and data types before writing complex ETL pipelines

03Investigating data quality issues like unexpected null percentages or value ranges

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add ai-builder-team/ai-builder-plugin-marketplace exploring-redshift-tables

For use in Claude.ai and ChatGPT

Download Skill