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Company Headcount Observations — Record Quality Audit, String Normalisation & Equal-Width Histogram
x402
Company Headcount Observations — Record Quality Audit, String Normalisation & Equal-Width Histogram 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 analytical reports (record quality audit, string normalisation, and equal-width histogram) on company headcount observation data including headcount and open_roles fields.
Price / call$0.01
Success—
StatusUnknown
How this service works
Company headcount observations — Record quality audit + String normalisation + Equal-width histogram: Record quality audit + String normalisation + Equal-width histogram for supplied company headcount observations records (headcount, open_roles). 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 identifying missing values, out-of-range entries, and data issues across the supplied rows; (2) a string normalisation report cleaning and standardising the company_group field; and (3) an equal-width histogram report bucketing the selected numeric field (headcount or open_roles) into the specified number of bins. All reports are generated locally without external lookups.
Example use cases
HR data quality check before reporting
“I've got 150 rows of company headcount observations with headcount and open_roles columns — can you audit the record quality and flag any issues, normalise the company_group strings, and give me a 10-bin histogram of headcount values?”
Hiring pipeline distribution analysis
“Run an equal-width histogram with 8 bins on our open_roles data across these company groups — I also want the record quality audit and string normalisation reports so we can clean this up before our board presentation.”
Workforce data normalisation for data warehouse
“Before we load this headcount observation data into our warehouse, can you check record quality, normalise the company group name strings, and show me a histogram of headcount with 5 bins so we know what we're working with?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-company-12-202?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need to simultaneously audit data quality, normalise string fields, and analyse the numeric distribution of company headcount or open_roles data in a single API call. It is ideal for pre-processing or profiling HR/workforce datasets before downstream analytics, reporting, or data warehouse ingestion. Best when you have up to 200 rows and want three bundled analytical reports at low cost without any external data lookups or live integrations.
Side effects
- More than 200 rows submitted — exceeds maximum row limit
- Missing required fields (row_id, company_group, date, headcount, open_roles) in any row
- Date field does not match YYYY-MM-DD pattern
- Bin count outside 1–30 range
- Invalid field enum value (must be 'headcount' or 'open_roles')
- Numeric values outside allowed range (-1,000,000,000,000 to 1,000,000,000,000)
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| bins | integer | |
| rows | array | |
| field | string |
Tags
x402
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