{"uid":"cap_8TSy2j-i88sSekWlyKQKM","slug":"business-directory-coverage-date-by-category-pivot-keyed-dataset-65cafba6","name":"Business Directory Coverage — Date-by-Category Pivot & Keyed Dataset Comparison","description":"Business directory coverage — Date by category pivot + Keyed dataset comparison: Date by category pivot + Keyed dataset comparison for supplied business directory coverage records (listed_entities, verified_entities). 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 business directory coverage data: a date-by-category pivot table and a keyed dataset comparison, across up to 200 supplied rows.","exampleAgentPrompt":"I have two sets of business directory coverage records — each with up to 50 rows including row_id, company_group, date, listed_entities, and verified_entities — can you run a date-by-category pivot and a keyed comparison between the two datasets using the listed_entities field?","exampleUseCases":[{"title":"Tracking directory coverage growth over time","prompt":"I have 4 months of weekly business directory snapshots across groups A and B, each row has a date, company_group, listed_entities, and verified_entities — can you pivot this by date and category and also compare it against last quarter's dataset to see what changed in listed_entities?"},{"title":"Auditing verified vs listed entity discrepancies","prompt":"Can you take my two directory coverage datasets — a current one and a reference one — and run both a date-by-category pivot and a keyed comparison on verified_entities so I can spot which company groups have diverged?"},{"title":"Benchmarking regional directory completeness","prompt":"I have directory coverage data for three regional company groups across 30 days, with listed_entities and verified_entities per row — please pivot it by date and group, and compare it against our target benchmark dataset using listed_entities."}],"resultDescription":"Returns two analytical reports: (1) a date-by-category pivot table showing the selected metric (listed_entities or verified_entities) broken down by date and company_group, and (2) a keyed dataset comparison highlighting differences between the primary rows dataset and the supplied comparison (other) dataset, all computed locally without any external lookups.","failureModes":["Rows array exceeds 200 items — request rejected","Missing required fields (row_id, company_group, date, listed_entities, verified_entities) in any row — validation error","Invalid date format (must be YYYY-MM-DD) — schema validation failure","Field enum value not recognized (must be listed_entities or verified_entities) — rejected","Empty rows array — minimum 1 item required"],"whenToPreferThis":"Choose this endpoint when you have pre-collected business directory coverage data (listed and verified entity counts by company group and date) and need both a pivot table view and a side-by-side keyed comparison against a second dataset in a single low-cost call. It is purely local analytical computation with no live data fetching, making it suitable for offline batch analysis of up to 200 rows at $0.01 per call.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-20T18:57:01.448Z","isFirstParty":false,"canonicalSlug":"business-directory-coverage-date-by-category-pivot-keyed-dataset-65cafba6"}