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Business Directory Coverage — String Normalisation + IQR Outlier Flags
x402
Business Directory Coverage — String Normalisation + IQR Outlier Flags 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).
Normalises strings and flags IQR-based outliers in business directory coverage data (listed_entities, verified_entities) for up to 200 rows, producing 2 independent analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Business directory coverage — String normalisation + IQR outlier flags: String normalisation + IQR outlier flags for supplied business directory coverage records (listed_entities, verified_entities). 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 2 independent analytical reports: (1) a string normalisation report covering the supplied row data, and (2) an IQR outlier flag report identifying statistically anomalous values in the selected field (listed_entities or verified_entities), all computed locally without external lookups or predictions. No external data is fetched.
Example use cases
Outlier audit for directory listing counts
“I have 50 rows of business directory data by company group and date, and I suspect some listed_entities values are statistical outliers. Can you run IQR outlier flagging on the listed_entities field and also normalise the string fields for me?”
Verified entity anomaly detection
“Please analyse my business directory coverage records — about 120 rows with company_group, date, listed_entities and verified_entities — and flag any IQR outliers in the verified_entities field, plus normalise the strings across all rows.”
Data quality check before reporting
“Before I publish my directory coverage report, can you clean and normalise the string fields in my 80-row dataset of listed and verified entity counts by group, and flag any rows where the numbers look like statistical outliers using IQR?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-company-14-032?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need lightweight, local statistical analysis of business directory coverage metrics — specifically string normalisation and IQR-based outlier detection — without any live lookups, predictions, or external API calls. Ideal for data quality audits on batches of up to 200 directory records where cost efficiency matters ($0.01 USDC for 2 reports). Prefer alternatives if you need predictive analytics, external data enrichment, or analysis of fields beyond listed_entities and verified_entities.
Side effects
- More than 200 rows submitted — request rejected due to maxItems constraint
- Missing required fields (row_id, company_group, date, listed_entities, verified_entities) — validation error
- Date field does not match YYYY-MM-DD pattern — schema validation failure
- Field value outside allowed numeric range (±1,000,000,000,000) — rejected
- Invalid enum value for 'field' parameter (must be listed_entities or verified_entities) — error response
- Empty rows array (minItems: 1 not satisfied) — validation failure
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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