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Schema Conformity String Normalisation & Adjacent Row Changes Analytics
x402
Schema Conformity String Normalisation & Adjacent Row Changes Analytics 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 two analytical reports — string normalisation and adjacent row changes — over up to 200 schema conformity records containing valid_records and checked_records fields.
Price / call$0.01
Success—
StatusUnknown
How this service works
Schema conformity — String normalisation + Adjacent row changes: String normalisation + Adjacent row changes for supplied schema conformity records (valid_records, checked_records). 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 independent analytical reports for the submitted rows: (1) a string normalisation report covering the selected field across all supplied schema conformity records, and (2) an adjacent row changes report showing value deltas between consecutive rows for the selected field. Both reports are computed locally with no external lookups. Up to 200 rows supported per call.
Example use cases
Audit schema conformity drift over time
“I have a week's worth of daily schema conformity records for two dataset groups — can you run the adjacent row changes report on the valid_records field so I can see where conformity jumped or dropped between days? Here are my rows: row-1 2026-10-01 group-a valid=100 checked=110, row-2 2026-10-02 group-a valid=90 checked=108, row-3 2026-10-03 group-b valid=200 checked=205, row-4 2026-10-04 group-b valid=195 checked=202.”
Normalize string fields in conformity dataset
“Run the string normalisation report for my schema conformity batch — I've got 3 rows: row-1 on 2025-01-10 in group-finance with valid_records=500 and checked_records=510, row-2 on 2025-01-11 in group-finance with valid_records=480 checked_records=505, row-3 on 2025-01-12 in group-ops with valid_records=300 checked_records=310. Target the checked_records field.”
Data quality monitoring for pipeline validation
“My data pipeline produces daily conformity counts — can you give me both the string normalisation and adjacent row changes analyses for these 5 rows targeting valid_records? row-1 2026-03-01 group-ingestion valid=1000 checked=1020, row-2 2026-03-02 group-ingestion valid=998 checked=1018, row-3 2026-03-03 group-ingestion valid=1050 checked=1055, row-4 2026-03-04 group-transform valid=850 checked=860, row-5 2026-03-05 group-transform valid=870 checked=875.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-02-029?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need dual analytical reports — string normalisation and adjacent row changes — specifically on schema conformity datasets with valid_records and checked_records metrics, in batches of up to 200 rows per call. It is purpose-built for data quality and conformity tracking workflows rather than general-purpose statistics or live data lookup.
Side effects
- Fewer than 1 row supplied — minItems validation failure
- More than 200 rows supplied — maxItems validation failure
- Invalid date format (not YYYY-MM-DD) — pattern validation failure
- Missing required fields (row_id, dataset_group, date, valid_records, checked_records) — schema validation error
- Field selector not in enum ['valid_records','checked_records'] — enum validation failure
- Numeric values outside allowed range (-1e12 to 1e12) — range validation failure
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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