Data Analysis

Generate queries and execute code to analyze structured datasets.

30|5|Updated Jan 14, 2026
One-click install
npx skills add https://github.com/allenai/asta-plugins --skill data-analysis-allenai
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: Data Analysis
Source: https://github.com/allenai/asta-plugins/tree/main/plugins/asta-preview/skills/analyze-data
Command: npx skills add https://github.com/allenai/asta-plugins --skill data-analysis-allenai

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill provides a structured approach for analyzing datasets and extracting meaningful insights, helping researchers and data scientists quickly explore and interpret data.

Core Features & Use Cases

  • Automated Data Exploration: Generate targeted analytical queries based on user requests to uncover patterns and relationships in datasets.
  • Research Question Answering: Assist in refining research questions and validating hypotheses using code-based analysis.
  • Use Case: A researcher uploads a CSV of experimental results and asks for a statistical summary or correlation analysis, which the Skill then executes and reports.

Quick Start

Ask the AI to analyze a CSV file by providing a question like "What are the most correlated variables in this dataset?" and specify the file path when prompted.

Frequently Asked Questions about Data Analysis

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

FAQPage Schema
How do I perform automated data exploration on a CSV dataset?▼

You can perform statistical analysis on experimental results by providing a CSV file and asking a question, which triggers the AI to generate tailored queries and execute code to calculate correlations and summaries.

What is the best way to find correlated variables in structured data?▼

The best way to find correlated variables is to prompt the AI with a specific question about your dataset, which generates and executes code-driven queries to reveal relationships.

Can I use this to validate research hypotheses with code-based analysis?▼

Yes, you can validate research hypotheses by refining your research questions and executing code-based analysis on structured data to test your assumptions and report findings.

Does this data analysis approach require specific data processing libraries?▼

Yes, this approach depends on underlying data processing libraries to perform code-driven insights and execute analytical queries on structured datasets like CSV files.

What types of datasets are supported for statistical summaries and data exploration?▼

Statistical summaries and data exploration are supported for structured datasets, such as CSV files of experimental results, where code can be executed to uncover patterns and relationships.