# Schema Conformity Analytics — Record Quality Audit, String Normalisation & Keyed Dataset Comparison > Schema Conformity Analytics — Record Quality Audit, String Normalisation & 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 2026-10-14). Runs three local analytical reports on schema conformity data (valid_records, checked_records): a record quality audit, string normalisation, and keyed dataset comparison across up to 200 rows. ## Facts - Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-02-207?utm_source=zero.xyz - Price: $0.01/call - Payment: x402 - Status: unknown - Last checked: 2026-10-14 - Activations on Zero: 0 - Tags: x402 - Canonical page: https://www.zero.xyz/c/schema-conformity-analytics-record-quality-audit-string-normalisation-4de52696 - Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_d0CoR7y_aU6M_gLMTfKmq 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 schema-conformity-analytics-record-quality-audit-string-normalisation-4de52696 -d '' ``` Example prompt: Can you run a record quality audit, string normalisation, and keyed comparison on my two schema conformity datasets? The primary dataset has rows like row-1 in group-a on 2026-10-01 with valid_records=10 and checked_records=1, and the secondary dataset has the same keys but valid_records=10 and checked_records=2 — up to 4 rows each. ## When to prefer this Choose this endpoint when you need three simultaneous analytical reports — quality audit, string normalisation, and keyed comparison — on schema conformity record data (valid_records, checked_records) in a single low-cost call. It is ideal for batch offline analysis of up to 200 rows where no live data lookup, external enrichment, or prediction is needed. Prefer it over separate single-report endpoints when all three report types are relevant to your conformity dataset workflow. ## Known failure modes - Exceeding 200 rows in either dataset array returns a validation error - Missing required fields (row_id, dataset_group, date, valid_records, checked_records) causes row rejection - Malformed date strings not matching YYYY-MM-DD pattern cause schema validation failure - Submitting an empty rows array (minItems:1 violated) returns an error - Numeric values outside ±1,000,000,000,000 bounds cause schema rejection - Payment of 0.01 USDC must be included; missing payment results in 402 response ## How this service works Schema conformity — Record quality audit + String normalisation + Keyed dataset comparison: Record quality audit + String normalisation + Keyed dataset comparison for supplied schema conformity records (valid_records, checked_records). Up to 200 rows; 3 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 3 supplied-data reports for up to 200 rows. ## Output Returns three independent analytical reports computed locally against the supplied data: (1) a record quality audit assessing the validity and completeness of valid_records and checked_records fields, (2) a string normalisation report cleaning and standardising string fields such as dataset_group, and (3) a keyed dataset comparison diffing the primary (rows) and secondary (other) datasets by row_id to surface value-level discrepancies. No external lookups or predictions are made. ## Request schema (JSON Schema) ```json { "type": "object", "properties": { "rows": { "type": "array", "items": { "type": "object", "required": [ "row_id", "dataset_group", "date", "valid_records", "checked_records" ], "properties": { "date": { "type": "string", "default": "", "pattern": "^\\d{4}-\\d{2}-\\d{2}$", "maxLength": 10 }, "row_id": { "type": "string", "default": "", "maxLength": 80, "minLength": 1 }, "dataset_group": { "type": "string", "default": "", "maxLength": 80 }, "valid_records": { "type": [ "number", "null" ], "maximum": 1000000000000, "minimum": -1000000000000 }, "checked_records": { "type": [ "number", "null" ], "maximum": 1000000000000, "minimum": -1000000000000 } }, "additionalProperties": false }, "default": [ { "date": "2026-10-01", "row_id": "row-1", "dataset_group": "group-a", "valid_records": 10, "checked_records": 1 }, { "date": "2026-10-02", "row_id": "row-2", "dataset_group": "group-b", "valid_records": 20, "checked_records": 2 }, { "date": "2026-10-03", "row_id": "row-3", "dataset_group": "group-a", "valid_records": 15, "checked_records": 3 }, { "date": "2026-10-04", "row_id": "row-4", "dataset_group": "group-b", "valid_records": 30, "checked_records": 4 } ], "maxItems": 200, "minItems": 1 }, "other": { "type": "array", "items": { "type": "object", "required": [ "row_id", "dataset_group", "date", "valid_records", "checked_records" ], "properties": { "date": { "type": "string", "default": "", "pattern": "^\\d{4}-\\d{2}-\\d{2}$", "maxLength": 10 }, "row_id": { "type": "string", "default": "", "maxLength": 80, "minLength": 1 }, "dataset_group": { "type": "string", "default": "", "maxLength": 80 }, "valid_records": { "type": [ "number", "null" ], "maximum": 1000000000000, "minimum": -1000000000000 }, "checked_records": { "type": [ "number", "null" ], "maximum": 1000000000000, "minimum": -1000000000000 } }, "additionalProperties": fa … (truncated) ``` ## More - Live health (JSON, refreshed every minute): https://www.zero.xyz/c/schema-conformity-analytics-record-quality-audit-string-normalisation-4de52696/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)