csv-processorlisted

# 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): ```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 ```bash 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.