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Business Directory Coverage — Record Quality Audit + String Normalisation + Keyed Dataset Comparison
x402
Business Directory Coverage — 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 2026-10-16).
Runs three analytical reports (record quality audit, string normalisation, and keyed dataset comparison) on up to 200 rows of business directory coverage data containing listed_entities and verified_entities fields.
Price / call$0.01
Success—
StatusUnknown
How this service works
Business directory coverage — Record quality audit + String normalisation + Keyed dataset comparison: Record quality audit + String normalisation + Keyed dataset comparison 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
Three independent analytical reports returned for the supplied rows: (1) a record quality audit highlighting missing, null, or out-of-range values; (2) a string normalisation report standardising company_group and other string fields; and (3) a keyed dataset comparison report showing row-level differences between the primary and comparison datasets based on shared keys. All processing is local with no external lookups.
Example use cases
Pre-ingestion data quality check
“Before we load this month's business directory coverage export into our pipeline, can you run a quality audit on these 150 rows — each has a row_id, company_group, date, listed_entities count, and verified_entities count — and flag any malformed or missing values?”
Normalising company group name strings
“I have a business directory dataset with inconsistent company_group name formatting across 120 rows — can you run the string normalisation report on it so we get clean, standardised group names before we join it to another table?”
Spotting coverage drift between two snapshots
“I've got two versions of our business directory coverage data — last quarter and this quarter, both around 180 rows — can you run the keyed dataset comparison to show me which rows have changed in listed_entities or verified_entities between the two snapshots?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-company-14-207?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need offline, deterministic data quality analysis on business directory coverage records without any live lookup or external API call. It is ideal for pre-ingestion validation, string standardisation pipelines, and diff-style comparison between two snapshots of the same dataset. At $0.01 USDC for three reports on up to 200 rows it is cost-effective for batch auditing workflows.
Side effects
- Rows array exceeds 200 items — request rejected
- Missing required fields (row_id, company_group, date, listed_entities, verified_entities) on any row — validation error
- Date field not matching YYYY-MM-DD pattern — schema validation failure
- listed_entities or verified_entities values outside allowed numeric range — schema rejection
- Empty rows array (minItems: 1 not met) — request rejected
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| other | array |
Tags
x402
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