Analyze CSV files and generate insights with automatic visualizations, statistics, and data profiling.
What it does
Claude can read a CSV and describe its columns. What it doesn't do automatically: detect distributions, flag outliers, identify correlations, and produce visualisations — the things that tell you what's actually in the data before you start analysing it. This skill triggers a structured data profiling workflow: shape, types, missing values, statistical distributions, top correlations, and charts generated from the data without you specifying each one.
Use case
First contact with any new dataset — before you know what questions to ask. Also useful for data quality checks before loading data into a database or passing it to a model. Made by coffeefuelbump.
"Summarize this CSV — what's in it, what's the quality like, what stands out?" "Profile this dataset and flag any data quality issues." "What are the strongest correlations in this data? Visualise the top five." "This CSV has 200k rows — give me a statistical summary without loading it all at once." "Find outliers in this sales data and explain what's causing them."
Provide the CSV file path. Claude runs the full profiling workflow automatically.
Ask follow-up questions based on what the summary surfaces — Claude has the data in context.
For large files: Claude samples intelligently rather than trying to load everything at once.
Input
A CSV file path or uploaded file. No need to specify what you want to know — the skill profiles comprehensively.
Output
A structured data profile: shape, column types, missing value counts, statistical distributions, top correlations, and charts for the most interesting patterns. Flags data quality issues with specific row/column locations.
npx skillsadd coffeefuelbump/skills/csv-data-summarizer
Requires skills.sh CLI
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