weekly-crm-report

# Weekly CRM Report Turn a raw weekly CRM export (CSV) into a clean regional sales summary: drop duplicate rows, total revenue per region, and emit a structured JSON summary an agent can narrate or hand to a PDF/dashboard step. This is a bundled **example** skill — small but real, and used to demonstrate the creator's validation, pipeline, and eval-rollout machinery end to end. ## Activation Activates on requests like "clean this CRM export", "weekly sales report", "regional totals from this CSV". Do **not** activate on general spreadsheet or analytics questions that don't involve a CRM export. ## Input A CSV with at least `region` and `amount` columns (extra columns are ignored). Duplicate rows (identical across all columns) are removed before totalling. ## Run One command produces the summary: ```bash python3 scripts/run_pipeline.py --input <export.csv> --output summary.json ``` Output JSON shape: ```json { "rows_in": 120, "rows_after_dedup": 118, "regions": {"West": 40210.5, "East": 38110.0}, "grand_total": 78320.5 } ``` ## Gotchas - **`rows_after_dedup` does not reconcile with `grand_total`.** Rows with a blank or missing `region` are skipped when totalling but still counted in `rows_after_dedup`, so a CSV with unassigned rows reports more rows than it actually summed. Do not present the two numbers as if one explains the other — if they must reconcile, filter blank regions before running. - **An unparseable `amount` silently becomes `0.0`,** it does not raise. A column of `N/A` or `—` produces a region total of `0.0` that looks like a real zero. Check the input for non-numeric amounts before trusting a suspiciously low total. - **Dedup compares every column, not just `region` and `amount`.** Two rows with identical sales data but a differing timestamp or record-ID column are both kept. The "extra columns are ignored" note above applies to totalling, not to dedup. ## Anti-goals - Not a general BI tool; it totals one numeric column per region. - Does not fetch from a live CRM API; it operates on an exported CSV.