data-pad

Load CSV, JSON, or NDJSON files and run SQL-like queries.

5|Updated Apr 8, 2026
One-click install
npx skills add https://github.com/JansenAnalytics/claudex --skill data-pad
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: data-pad
Source: https://github.com/JansenAnalytics/claudex/tree/main/skills/data-pad
Command: npx skills add https://github.com/JansenAnalytics/claudex --skill data-pad

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Data analysis often requires turning raw CSV, JSON, or API-derived data into actionable insights. This skill provides a streamlined workflow to load, query, and explore structured data so you can derive answers quickly without manual scripting.

Core Features & Use Cases

  • Load CSV, JSON, and NDJSON files into an in-memory or local database for analysis.
  • Run SQL-like queries to summarize, filter, and aggregate data.
  • Explore schemas and export results for reporting or further processing.
  • Use with data from APIs by fetching JSON and querying it locally.

Quick Start

Load a data file (CSV/JSON/NDJSON) and run a sample query to inspect the results.

Frequently Asked Questions about data-pad

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I run SQL queries on a JSON file from an API?

To query CSV data, load the file into the local database. You can then run SQL-like queries to filter, summarize, and aggregate records, turning raw file data into actionable insights.

Can I load and analyze NDJSON files for ad-hoc reporting?

Yes, you can load NDJSON files. The skill supports loading NDJSON formats alongside CSV and JSON, allowing you to explore schemas and export query results for reporting.

What is the best way to explore the schema of a structured data file?

The best way to explore a schema is to load your structured data file directly. Once loaded, you can inspect the schema and run SQL-like queries to understand the data structure and contents.

Does this approach work with both local files and remote URLs?

Yes, data querying works with both local files and remote URLs. You can load data from a local file or fetch it via a URL, then apply SQL-like queries to explore and aggregate the results.

How do I export aggregated query results to CSV or JSON?

You can export aggregated query results to CSV or JSON formats. After running SQL-like queries to summarize your structured data, use the export function to generate output files for reporting.