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Business Directory Coverage — Record Quality Audit + String Normalisation + Date by Category Pivot
x402
Business Directory Coverage — Record Quality Audit + String Normalisation + Date by Category Pivot is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-16).
Runs three local analytical reports (record quality audit, string normalisation, and date-by-category pivot) on up to 200 rows of business directory coverage data containing listed and verified entity counts.
Price / call$0.01
Success—
StatusUnknown
How this service works
Business directory coverage — Record quality audit + String normalisation + Date by category pivot: Record quality audit + String normalisation + Date by category pivot for supplied business directory coverage records (listed_entities, verified_entities). 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: (1) a record quality audit flagging issues such as nulls, out-of-range values, and structural anomalies; (2) a string normalisation report identifying and correcting inconsistencies in text fields like company_group; and (3) a date-by-category pivot summarising the chosen metric (listed_entities or verified_entities) aggregated by date and company group. All computed locally without any external lookups or live data.
Example use cases
Auditing directory data before a merge
“I'm about to merge two business directory datasets and I need to audit the record quality, normalise any string inconsistencies, and pivot coverage by date and company group first — can you run all three reports on these rows? I have group-a with 15 listed and 3 verified on 2026-11-01, and group-b with 30 listed and 4 verified on 2026-11-02, using listed_entities as the pivot field.”
Monthly directory coverage review
“It's end of month and I need a full analytical check on our business directory coverage records — run the quality audit, string normalisation, and date pivot on these 4 rows: row-1 group-alpha 50 listed 5 verified on 2026-10-01, row-2 group-beta 80 listed 10 verified on 2026-10-08, row-3 group-alpha 60 listed 7 verified on 2026-10-15, row-4 group-beta 90 listed 12 verified on 2026-10-22, pivoting on verified_entities.”
Spotting anomalies in verified entity counts
“Some of our verified_entities counts look off across different company groups — can you run a record quality audit and string normalisation plus a date-by-category pivot focused on verified_entities for these records: row-1 group-x 100 listed 0 verified 2026-09-01, row-2 group-y 200 listed null verified 2026-09-02, row-3 group-x 150 listed 5 verified 2026-09-03?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-company-14-206?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have up to 200 rows of business directory coverage data with listed and verified entity counts and need three complementary analytical reports (quality audit, string normalisation, and date-by-category pivot) in a single low-cost call. It is ideal for offline, batch-style data validation and summarisation tasks where no live lookups, external predictions, or real-time data are needed. It is not suitable if you need more than 200 rows processed, real-time directory lookups, or only one of the three reports independently.
Side effects
- More than 200 rows submitted — request rejected with a row limit error
- Missing required fields (row_id, company_group, date, listed_entities, verified_entities) — validation error returned
- Date field not matching YYYY-MM-DD pattern — schema validation failure
- Invalid field enum value (not 'listed_entities' or 'verified_entities') — rejected with enum error
- Empty rows array — minimum items violation
- Numeric values outside allowed range (±1,000,000,000,000) — schema rejection
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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