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data-explorer

Analyze CSV and Excel files to profile data and detect missing or anomalous values.

267|63|Updated Feb 15, 2026
Search Tags:#data quality#excel#csv#statistical analysis#data profiling#outlier detection
One-click install
npx skills add https://github.com/modu-ai/cowork-plugins --skill data-explorer-modu-ai
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: data-explorer
Source: https://github.com/modu-ai/cowork-plugins/tree/main/moai-data/skills/data-explorer
Command: npx skills add https://github.com/modu-ai/cowork-plugins --skill data-explorer-modu-ai

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pandas, numpy, scipy, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill streamlines the process of exploring and analyzing CSV and Excel datasets, enabling quick insights and data quality assessments without manual effort.

Core Features & Use Cases

  • Data Profiling: Summarizes data types, missing values, and statistical measures.
  • Quality Inspection: Detects anomalies, duplicates, and inconsistent data entries.
  • Use Case: For a dataset of sales transactions, quickly identify missing values, outliers, and correlations to support data-driven decision-making.

Quick Start

Provide a CSV or Excel file containing sales data to generate a detailed data profile and quality report automatically.

Frequently Asked Questions about data-explorer

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

FAQPage Schema
How do I automate data profiling for a CSV or Excel file?▼

You can automate data profiling by providing a CSV or Excel file to generate a detailed report summarizing data types, missing values, and statistical measures for your dataset.

What is the best way to detect outliers and missing values in a dataset?▼

Detecting outliers and missing values is best handled by running an automated quality inspection that identifies anomalies, duplicates, and inconsistent entries across your dataset.

Can I run statistical analysis and correlation checks on Excel data without manual formulas?▼

Yes, you can run statistical analysis on Excel data without manual formulas to automatically assess correlations and support data-driven decision-making for datasets like sales transactions.

Do I need Python and pandas installed to perform CSV data quality inspections?▼

You need a Python environment with pandas, numpy, and scipy dependencies installed to execute the scripts that automate comprehensive dataset evaluations and quality inspections.

Does this data profiling approach work for large CSV files with inconsistent entries?▼

This data profiling approach works for CSV files by detecting inconsistencies and anomalous values, though performance depends on your environment's capacity to handle large datasets.

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