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Company Record Completeness — Record Quality Audit + String Normalisation + Date by Category Pivot
x402
Company Record Completeness — 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 2026-10-15).
Runs three local analytical reports (record quality audit, string normalisation, and date-by-category pivot) on up to 200 company record completeness rows containing populated_fields and required_fields data.
Price / call$0.01
Success—
StatusUnknown
How this service works
Company record completeness — Record quality audit + String normalisation + Date by category pivot: Record quality audit + String normalisation + Date by category pivot for supplied company record completeness records (populated_fields, required_fields). 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: (1) a record quality audit flagging completeness issues and anomalies in the supplied rows, (2) a string normalisation report cleaning and standardising text values such as company_group names, and (3) a date-by-category pivot summarising the chosen numeric field (populated_fields or required_fields) broken down by date and company group. All processing is local with no external lookups.
Example use cases
CRM data quality audit for sales team
“I've got a batch of 50 company CRM records with populated_fields and required_fields counts per group and date — can you run a record quality audit and string normalisation on them so I can see which company groups have the worst data completeness?”
Monthly completeness pivot by business unit
“Here are 120 rows of company record completeness data across several business units, each with a date and populated vs required field counts. Can you pivot them by date and category so I can see how completeness trends over the month?”
Pre-migration data normalisation check
“Before we migrate our company database, I need to normalise the string values and audit the record quality for around 80 rows of company completeness data — each row has a company_group, date, populated_fields, and required_fields. Can you run all three reports on the required_fields column?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-company-01-206?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need three bundled analytical passes — quality audit, string normalisation, and date pivot — on a batch of up to 200 company record completeness rows in a single $0.01 call. It is ideal for offline or pre-migration data hygiene workflows where no live lookup or external enrichment is needed and you want cost-efficient batch analysis of populated_fields vs required_fields ratios across company groups and dates.
Side effects
- More than 200 rows submitted — exceeds maximum batch size
- Missing required fields (row_id, company_group, date, populated_fields, required_fields) causes validation error
- Invalid date format (not YYYY-MM-DD) triggers schema rejection
- Numeric values outside allowed range (-1,000,000,000,000 to 1,000,000,000,000) rejected
- Invalid field enum value (must be 'populated_fields' or 'required_fields')
- Empty rows array rejected — minimum 1 row required
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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