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csv-analyzer

Analyze CSV files to generate summary statistics and data quality reports.

42|1|Updated Dec 14, 2025
Search Tags:#analysis#reporting#json#statistics#csv#data-quality
One-click install
npx skills add https://github.com/everruns/everruns --skill csv-analyzer-everruns
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: csv-analyzer
Source: https://github.com/everruns/everruns/tree/main/examples/skills/csv-analyzer
Command: npx skills add https://github.com/everruns/everruns --skill csv-analyzer-everruns

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

CSV data analysis to generate summary statistics and identify data-quality issues for better decision making.

Core Features & Use Cases

  • Generate per-column statistics (row_count, column_count, data types, null counts)
  • Detect quality issues (missing values, duplicates, constant columns)
  • Produce a structured JSON report for downstream tools
  • Use Case: profile a dataset of customer records to prepare a quality-assured dataset for analytics.

Quick Start

Run the analyze.py script on your CSV file to obtain a JSON report.

Frequently Asked Questions about csv-analyzer

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

FAQPage Schema
How do I generate summary statistics for a CSV file?▼

You can detect CSV data quality issues by running the analyze.py script, which identifies missing values, duplicates, and constant columns, outputting the results in a structured JSON report.

What is included in a CSV data quality report?▼

A CSV data quality report includes per-column statistics like row_count, column_count, data types, and null counts, alongside detected quality issues such as missing values, duplicates, and constant columns outputted as JSON.

Can I analyze CSV files with missing values and potential quality issues?▼

Yes, you can analyze CSV files with missing values and potential quality issues. The analyzer processes datasets with multiple columns to identify missing data, duplicates, and constant columns in the output JSON report.

How do I get a JSON report from my CSV data?▼

You get a JSON report from CSV data by running the analyze.py script, which processes your dataset and outputs a structured JSON file containing summary statistics and identified data quality issues.

What CSV quality issues can be automatically detected during profiling?▼

During CSV profiling, the analyzer automatically detects quality issues including missing values, duplicates, and constant columns, compiling them into a structured JSON report for downstream analytics tools.

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