What types of data validation does it perform?

It conducts sanity checks for unexpected nulls, row count magnitude, trend continuity in time series, and ensures subtotals sum correctly to totals.

Does this skill require a direct database connection?

While it performs best with a connected MCP data warehouse server, it can also analyze data provided via CSV, Excel files, or manually pasted query results.

Can it help with data visualization?

Yes, the skill can leverage Python or HTML to generate charts and dashboards that make complex data trends easier to understand.

How does the skill handle SQL errors?

The workflow includes an automated debugging step where Claude checks syntax, column names, and table references to retry failed queries.

Data Analysis Assistant

Name: Data Analysis Assistant
Author: anthropics

byanthropics

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11,566

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数据科学与机器学习

Performs end-to-end data analysis from quick metric lookups to comprehensive stakeholder reports using SQL and visualization tools.

This skill transforms Claude into a full-cycle data analyst capable of navigating complex datasets to provide actionable insights. It handles the entire analytical workflow: exploring database schemas via MCP servers, writing and debugging SQL, validating results for accuracy, and interpreting trends. Whether you need a simple count of active users or a deep-dive investigation into conversion rate drops, the skill can process data from live warehouses or uploaded files like CSVs and Excel to produce everything from quick answers to formal, stakeholder-ready reports with integrated visualizations.

主要功能

01Flexible data input including MCP connections, CSV/Excel uploads, or manual pasting.

02Integrated data validation checks to ensure row count sanity and aggregation accuracy.

03Visual storytelling through integrated chart generation and dashboard building.

04Support for multi-level analysis ranging from quick lookups to complex trend investigations.

0511,566 GitHub stars

06Automated schema exploration and SQL query generation for data warehouses.

使用场景

01Preparing formal quarterly business reviews and executive summary reports.

02Running data quality assessments to identify inconsistencies or missing information in tables.

03Investigating the primary drivers behind changes in business KPIs or user behavior.

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add anthropics/knowledge-work-plugins analyze

For use in Claude.ai and ChatGPT

主要功能

01Flexible data input including MCP connections, CSV/Excel uploads, or manual pasting.

02Integrated data validation checks to ensure row count sanity and aggregation accuracy.

03Visual storytelling through integrated chart generation and dashboard building.

04Support for multi-level analysis ranging from quick lookups to complex trend investigations.

0511,566 GitHub stars

06Automated schema exploration and SQL query generation for data warehouses.

使用场景

01Preparing formal quarterly business reviews and executive summary reports.

02Running data quality assessments to identify inconsistencies or missing information in tables.

03Investigating the primary drivers behind changes in business KPIs or user behavior.