csv-processor

A deterministic, network-free skill — the easiest case. Useful as a control when debugging the agent ↔ skill plumbing: if this fails, the failure is in the runner, not the skill.

Contract

Input (single CLI argument):

python src/main.py /path/to/data.csv

The script reads argv[1] as a filesystem path. CSV must have a header row.

Output (stdout, JSON):

{
  "rowCount": 1234,
  "columns": {
    "price": { "min": 1.23, "mean": 42.0, "max": 999.99, "count": 1234 },
    "quantity": { "min": 0, "mean": 7.5, "max": 100, "count": 1230 }
  }
}

Only numeric columns appear under columns. count is the number of cells that parsed successfully (numeric); non-numeric / blank cells are skipped.

Errors — written to stderr as {"error": "..."} and exit code 1.

Run locally

cd examples/csv-processor
python src/main.py sample.csv

A sample.csv is bundled so the example runs out of the box.

Adapt this

• Different aggregations — add median, p95, stddev; same shape, more keys per column.
• Streaming — for huge files, replace the in-memory accumulation with a running-mean update; one extra variable per column, same output shape.
• Source other than disk — accept a URL or stdin instead of argv[1]. The aggregation core doesn't care.