data-analyst

Analyzes CSV, Excel, and JSON datasets to generate summaries and insights.

Updated Mar 19, 2026
One-click install
npx skills add https://github.com/gaos6e/MyOpenclaw --skill data-analyst-gaos6e
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: data-analyst
Source: https://github.com/gaos6e/MyOpenclaw/tree/main/workspace/skills/data-analyst-pro
Command: npx skills add https://github.com/gaos6e/MyOpenclaw --skill data-analyst-gaos6e

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill automates data analysis tasks by interpreting user instructions and applying analytics to datasets, reducing manual workload.

Core Features & Use Cases

  • Data cleaning and preprocessing to handle missing values and inconsistencies.
  • Exploratory data analysis and summary statistics to reveal key insights.
  • Reproducible analysis workflows for CSV, Excel, or JSON data across ad-hoc analytics, dashboards, and reports.

Quick Start

Analyze the provided dataset to produce a summary of key metrics.

Frequently Asked Questions about data-analyst

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

FAQPage Schema
How do I analyze a CSV file to generate summary statistics and key insights?

Yes, you can analyze Excel data alongside CSV and JSON files. The skill processes these formats to perform data cleaning, aggregation, and reporting, generating reproducible workflows and actionable summaries across all supported file types.

What is the best way to automate exploratory data analysis for ad-hoc reporting?

Data cleaning handles missing values and inconsistencies by applying robust input validation and error handling. This ensures your datasets are safely transformed and preprocessed before generating reproducible summaries and reports.

Does this data analysis approach work with JSON data for dashboard generation?

Data provenance and reproducible workflows ensure repeatable analyses by tracking data origins and applying consistent transformation rules. This guarantees that every reporting and aggregation task produces identical, verifiable results.

Why does my data analysis workflow lack reproducibility when handling missing values?

Before analyzing datasets, you must provide valid CSV, Excel, or JSON files containing the raw metrics. This prerequisite input data serves as the foundation for the skill to execute cleaning, aggregation, and exploratory analysis tasks.