---
name: openai-csv-workbench
description: "Analyze CSV files in /mnt/data and return concise numeric summaries."
license: "MIT"
metadata:
  decimalai-skill-id: "d00a7247-ae1d-4fae-a5a0-f2207a6a8b31"
  decimalai-version-id: "390108c6-3560-4339-a3c9-c64400c594cf"
  decimalai-version: "1"
  decimalai-body-sha256: "f90ed936478991b4e16b35e1c9e799302661bdd469b175d58293d22968e86eb9"
  decimalai-name: "openai/csv-workbench"
  decimalai-format: "1"
  decimalai-invocation: "model"
  decimalai-category: "data"
  decimalai-source: "https://app.decimal.ai/s/openai-csv-workbench@1/SKILL.md"
---
# CSV Workbench

Use this skill when the user asks for quick analysis of tabular data.

## Workflow

1. Inspect the CSV schema first (`head`, `python csv.DictReader`, or both).
2. Compute requested aggregates with a short Python script.
3. Return concise results with concrete numbers and units when available.

## Constraints

- Prefer Python stdlib for portability.
- If data is missing or malformed, state assumptions clearly.
- Keep the final answer short and actionable.