{"uid":"cap_k2yyurC4YFqnP_yf4aDpH","slug":"label-review-analytics-date-by-category-pivot-keyed-dataset-comparison-f7180abb","name":"Label Review Analytics: Date-by-Category Pivot + Keyed Dataset Comparison","description":"Label review — Date by category pivot + Keyed dataset comparison: Date by category pivot + Keyed dataset comparison for supplied label review records (reviewed_records, changed_labels). Up to 200 rows; 2 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 2 supplied-data reports for up to 200 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two analytical reports on label review data: a date-by-category pivot table and a keyed dataset comparison, for up to 200 rows at $0.01 USDC.","exampleAgentPrompt":"Run a date-by-category pivot and keyed dataset comparison on my label review data — primary dataset has rows like {row_id: 'row-1', dataset_group: 'group-a', date: '2026-10-01', reviewed_records: 10, changed_labels: 1} (up to 200 rows), and I want to compare it against a second dataset with the same structure, analyzing the 'reviewed_records' field.","exampleUseCases":[{"title":"Daily label change audit across groups","prompt":"I have two weeks of label review logs with columns row_id, dataset_group, date, reviewed_records, and changed_labels — can you pivot them by date and category and also compare the first week against the second week to see where label changes spiked?"},{"title":"Annotation team productivity comparison","prompt":"Compare my two annotation team datasets for October — both have the same format with row_id, dataset_group, date, reviewed_records, and changed_labels — give me a date-by-category pivot for the reviewed_records field and show me which groups differ most between the two datasets."},{"title":"ML dataset quality review rollup","prompt":"I've got up to 150 rows of label review records across three dataset groups over the past month and a baseline dataset from last month — run a pivot by date and group plus a keyed comparison against the baseline, focusing on the changed_labels field."}],"resultDescription":"Returns two independent analytical reports: (1) a date-by-category pivot table cross-tabulating the chosen field (reviewed_records or changed_labels) across dates and dataset_group values, and (2) a keyed dataset comparison highlighting row-level or aggregate differences between the primary and secondary supplied datasets. All computation is local with no external lookups.","failureModes":["More than 200 rows submitted — request rejected or truncated","Missing required fields (row_id, dataset_group, date, reviewed_records, changed_labels) — validation error","Invalid date format (must match YYYY-MM-DD) — schema rejection","Numeric values outside allowed range (-1e12 to 1e12) — validation error","Empty rows array — minimum 1 item required","Field enum value not 'reviewed_records' or 'changed_labels' — rejected"],"whenToPreferThis":"Choose this endpoint when you have label review or annotation data organized by date and dataset group and need both a pivot summary and a side-by-side dataset comparison in a single cheap call ($0.01 USDC). It is ideal for ML data ops, annotation auditing, or quality assurance workflows where you want to compare two batches of up to 200 rows without any external lookups or live model inference.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-24T00:54:21.274Z","isFirstParty":false,"canonicalSlug":"label-review-analytics-date-by-category-pivot-keyed-dataset-comparison-f7180abb"}