# Data Ingestion Batches — Category Frequencies + Keyed Dataset Comparison > Data Ingestion Batches — Category Frequencies + Keyed Dataset Comparison is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-19). Analyzes up to 200 data ingestion batch records to produce two reports: category frequency distribution by dataset group, and a keyed row-by-row comparison between two supplied datasets. ## Facts - Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-01-111?utm_source=zero.xyz - Price: $0.01/call - Payment: x402 - Status: unknown - Last checked: 2026-10-19 - Activations on Zero: 0 - Tags: x402 - Canonical page: https://www.zero.xyz/c/data-ingestion-batches-category-frequencies-keyed-dataset-comparison-4abcacd6 - Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_5ObzvqlnLKDJ3CA2bibi0 Status and success rate cover calls made through Zero and Zero's own probes. Third-party monitors may report differently. ## How to call it through Zero Zero handles the 402 payment challenge and records the run. With the Zero CLI installed (`npm i -g @zeroxyz/cli`): ```sh zero fetch --capability data-ingestion-batches-category-frequencies-keyed-dataset-comparison-4abcacd6 -d '' ``` Example prompt: I have two sets of ingestion batch records — each with row IDs, dataset groups, dates, received rows, and accepted rows — can you run a category frequency breakdown and a keyed comparison between the two datasets? Here's my primary set: [{"row_id":"r1","dataset_group":"customers","date":"2025-01-10","received_rows":500,"accepted_rows":490}] and comparison set: [{"row_id":"r1","dataset_group":"customers","date":"2025-01-10","received_rows":500,"accepted_rows":475}]. ## When to prefer this Choose this endpoint when you need both a frequency/distribution report across dataset groups AND a keyed row-level diff between two ingestion batch snapshots in a single call for under $0.01. It is best suited for ETL monitoring, pipeline QA, and acceptance rate audits where you already have the batch data in hand and want local analytical computation — not for live pipeline introspection, external data fetching, or single-metric calculations. ## Known failure modes - Input array exceeds 200 rows — request rejected with validation error - Missing required fields (row_id, dataset_group, date, received_rows, accepted_rows) — row rejected or error returned - Date field does not match YYYY-MM-DD pattern — validation failure - Numeric values out of allowed range (±1,000,000,000,000) — schema rejection - Empty rows array — minimum 1 item required, returns error - Non-overlapping row_ids between primary and secondary datasets — comparison report may return empty or unmatched rows ## How this service works Data ingestion batches — Category frequencies + Keyed dataset comparison: Category frequencies + Keyed dataset comparison for supplied data ingestion batches records (received_rows, accepted_rows). Up to 200 rows; 2 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 2 supplied-data reports for up to 200 rows. ## Output Returns two analytical reports: (1) a category frequency table showing how often each dataset_group appears and aggregated received/accepted row counts per group in the primary dataset; (2) a keyed row-by-row comparison between the primary ('rows') and secondary ('other') datasets, highlighting differences in received_rows and accepted_rows for matching row_ids. All analysis is performed locally with no external lookups. ## Request schema (JSON Schema) ```json { "type": "object", "properties": { "rows": { "type": "array", "items": { "type": "object", "required": [ "row_id", "dataset_group", "date", "received_rows", "accepted_rows" ], "properties": { "date": { "type": "string", "default": "", "pattern": "^\\d{4}-\\d{2}-\\d{2}$", "maxLength": 10 }, "row_id": { "type": "string", "default": "", "maxLength": 80, "minLength": 1 }, "accepted_rows": { "type": [ "number", "null" ], "maximum": 1000000000000, "minimum": -1000000000000 }, "dataset_group": { "type": "string", "default": "", "maxLength": 80 }, "received_rows": { "type": [ "number", "null" ], "maximum": 1000000000000, "minimum": -1000000000000 } }, "additionalProperties": false }, "default": [ { "date": "2026-10-01", "row_id": "row-1", "accepted_rows": 1, "dataset_group": "group-a", "received_rows": 10 }, { "date": "2026-10-02", "row_id": "row-2", "accepted_rows": 2, "dataset_group": "group-b", "received_rows": 20 }, { "date": "2026-10-03", "row_id": "row-3", "accepted_rows": 3, "dataset_group": "group-a", "received_rows": 15 }, { "date": "2026-10-04", "row_id": "row-4", "accepted_rows": 4, "dataset_group": "group-b", "received_rows": 30 } ], "maxItems": 200, "minItems": 1 }, "other": { "type": "array", "items": { "type": "object", "required": [ "row_id", "dataset_group", "date", "received_rows", "accepted_rows" ], "properties": { "date": { "type": "string", "default": "", "pattern": "^\\d{4}-\\d{2}-\\d{2}$", "maxLength": 10 }, "row_id": { "type": "string", "default": "", "maxLength": 80, "minLength": 1 }, "accepted_rows": { "type": [ "number", "null" ], "maximum": 1000000000000, "minimum": -1000000000000 }, "dataset_group": { "type": "string", "default": "", "maxLength": 80 }, "received_rows": { "type": [ "number", "null" ], "maximum": 1000000000000, "minimum": -1000000000000 } }, "additionalProperties": false }, "de … (truncated) ``` ## More - Live health (JSON, refreshed every minute): https://www.zero.xyz/c/data-ingestion-batches-category-frequencies-keyed-dataset-comparison-4abcacd6/health.json - [Zero catalog index](https://www.zero.xyz/llms.txt) - [Other services from market.datapackvibe.com](https://www.zero.xyz/host/market.datapackvibe.com/llms.txt)