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Company Headcount Observations — Record Quality Audit, String Normalisation & Numeric Row Ordering
x402
Company Headcount Observations — Record Quality Audit, String Normalisation & Numeric Row Ordering is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-19).
Audits data quality, normalises strings, and orders rows numerically for up to 200 company headcount observation records (headcount and open_roles fields) across 3 independent analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Company headcount observations — Record quality audit + String normalisation + Numeric row ordering: Record quality audit + String normalisation + Numeric row ordering 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
Three independent analytical reports: (1) a record quality audit flagging issues in the supplied headcount/open_roles rows, (2) a string normalisation report standardising fields like company_group, and (3) a numeric row ordering report sorting rows by the selected numeric field (headcount or open_roles). No external data is fetched; all analysis is performed on the supplied rows only.
Example use cases
HR data quality check before reporting
“I have 150 rows of company headcount snapshots by group and date with headcount and open_roles values — can you audit them for record quality issues, normalise any inconsistent company_group strings, and order the headcount field numerically so I can trust the data before my monthly report?”
Spotting dirty open_roles data
“Before I load these open_roles observations into our dashboard, can you run the quality audit and string normalisation on my 80-row dataset grouped by company_group and date, focusing on the open_roles field so I can catch any bad values?”
Standardising headcount records across groups
“I've merged headcount data from three company groups into about 120 rows and the company_group names are inconsistently formatted — can you normalise the strings, check record quality, and give me a numerically ordered view of the headcount column?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-company-12-196?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need three bundled data-quality operations (audit, string normalisation, numeric ordering) on company headcount observation records in a single cost-effective call ($0.01 USDC for all three reports on up to 200 rows). Prefer this over general-purpose data tools when your data specifically contains headcount and open_roles fields grouped by company and date, and you need no live lookups or external enrichment — only local analytical processing of supplied rows.
Side effects
- Exceeding 200 rows returns an error or processes only up to the limit
- Rows missing required fields (row_id, company_group, date, headcount, open_roles) fail validation
- Date strings not matching YYYY-MM-DD pattern are rejected
- Null numeric values may affect ordering report output
- Field selector not matching 'headcount' or 'open_roles' enum causes rejection
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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