csv-processor_skill

Overview

This skill provides a compact CSV processor for reading, writing, converting, and analyzing CSV files. It supports filtering, sorting, aggregation, and format conversion to help you manipulate tabular data quickly. Designed for command-style use, it works well with scripts and automation workflows.

How this skill works

The tool inspects CSV files and performs row-level operations like filtering and sorting, column-level transformations, and group aggregations. It can convert CSV to other formats (for example JSON) and write results to disk or stdout. Commands accept column names, filter values, sort directions, and aggregation specs to produce deterministic outputs.

When to use it

• Clean and prepare CSVs before importing into databases or analytics tools.
• Quickly filter large CSVs to extract relevant rows or columns.
• Sort datasets by date, numeric or textual fields for reporting.
• Aggregate transactions by category, sum amounts, or compute counts and averages.
• Convert CSVs to JSON for APIs or downstream processing.

Best practices

• Specify exact column names to avoid ambiguous matches and unexpected results.
• Preview changes on a subset of rows before running full-file operations to avoid costly mistakes.
• Use explicit sort directions (asc/desc) when ordering results to ensure reproducible output.
• When aggregating, validate numeric columns and handle missing values explicitly.
• Write converted or transformed outputs to a new file rather than overwriting originals until results are verified.

Example use cases

• Filter a user export to only include active accounts and write the subset to a new CSV.
• Sort transaction logs by timestamp and convert the top N rows to JSON for an API payload.
• Aggregate sales by product category to produce summary reports and totals.
• Convert legacy CSV reports into JSON for ingestion by a modern data pipeline.
• Chain filter → sort → aggregate to prepare a reporting dataset for visualization.