skills.rest
PaulKinlan
PaulKinlanCOMMUNITY
Explore all skills by this author →
Website𝕏@paul_kinlanGitHub

data-analysis

Inspect, validate, and summarize CSV, JSON, and JSONL data files.

2|Updated Feb 4, 2026
Search Tags:#data quality#reporting#json#data analysis#statistics#csv
One-click install
npx skills add https://github.com/PaulKinlan/docker-agent-test --skill data-analysis-paulkinlan
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: data-analysis
Source: https://github.com/PaulKinlan/docker-agent-test/tree/main/config/skills/analyst/data-analysis
Command: npx skills add https://github.com/PaulKinlan/docker-agent-test --skill data-analysis-paulkinlan

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

This Skill automates the process of inspecting, validating, and analyzing data files, providing quick insights and summary statistics without manual intervention.

Core Features & Use Cases

  • Data Inspection: Quickly view file information, headers, and sample rows for various formats (CSV, JSON, JSONL).
  • Data Quality Checks: Identify empty fields, duplicate rows, and null values to ensure data integrity.
  • Statistical Analysis: Compute summary statistics (mean, median, min, max) for numeric fields and value counts for categorical fields.
  • Complex Analysis: Leverage Python for more advanced data manipulation and analysis.
  • Reporting: Generate a structured Markdown report of the analysis and register it as an artifact.
  • Use Case: You receive a CSV file containing customer transaction data. Use this Skill to understand the data structure, check for missing values, calculate the average transaction amount, and see the distribution of customer statuses, then generate a report.

Quick Start

Analyze the data in the file named 'transactions.csv' located in the shared directory.

Frequently Asked Questions about data-analysis

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

FAQPage Schema
How do I inspect a CSV file and check data quality automatically?▼

You can inspect CSV files and check data quality by using this Skill to view headers and sample rows while identifying empty fields, duplicate rows, and null values. It validates data integrity across CSV, JSON, and JSONL formats.

What's the best way to compute summary statistics for a JSON dataset?▼

Computing summary statistics for a JSON dataset is done by this Skill, which calculates mean, median, min, and max for numeric fields, plus value counts for categorical fields. It handles JSON and JSONL formats natively to provide quick insights.

Can I generate a Markdown report of my data analysis results?▼

Yes, generating a Markdown report of your data analysis results is supported. This Skill computes summary statistics, performs quality checks, and registers the structured Markdown report as an artifact automatically after processing your data files.

Does this data analysis tool support running custom Python scripts for complex analysis?▼

Yes, this data analysis tool supports running custom Python scripts for complex analysis. You can leverage Python within the Skill to perform advanced data manipulation beyond standard inspection and summary statistics on your CSV and JSON files.

How do I find missing values and duplicate rows in a JSONL file?▼

Finding missing values and duplicate rows in a JSONL file is handled by this Skill's data quality checks feature. It scans your data to identify empty fields, null values, and duplicate rows, ensuring data integrity without manual intervention.

Related Skills

Explore More Data & Analytics Skills→
UKGovernmentBEISUKGovernmentBEIS
617

investigate-dataset

Inspect HuggingFace, CSV, and JSON datasets for schema and quality.

Official
Intermediate
oaustegardoaustegard
137

exploring-data

Generate interactive HTML exploratory data analysis reports from datasets.

Community
Intermediate
mk-knight23mk-knight23
1

data-pipeline

Build and run Python ETL pipelines for CSV, JSON, Parquet, and database sources.

Community
Intermediate
CompSci-SquadCompSci-Squad

data-scientist

Perform advanced analytics, predictive modeling, and statistical modeling for data science tasks.

Official
Advanced