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Company Headcount Observations — Record Quality Audit + String Normalisation + Adjacent Row Changes
x402
Company Headcount Observations — Record Quality Audit + String Normalisation + Adjacent Row Changes 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).
Audits data quality, normalises strings, and detects adjacent row changes in company headcount observation records (headcount, open_roles) for up to 200 rows, returning 3 bundled analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Company headcount observations — Record quality audit + String normalisation + Adjacent row changes: Record quality audit + String normalisation + Adjacent row changes 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 missing, out-of-range, or malformed values; (2) a string normalisation report identifying inconsistent or non-standard company_group strings; (3) an adjacent row changes report showing where consecutive rows differ significantly in the selected numeric field (headcount or open_roles). All reports are computed locally with no external lookups.
Example use cases
HR data pipeline quality gate
“I'm loading monthly headcount snapshots from our HR system into our data warehouse and need to check this batch of 120 rows for data quality issues, inconsistent company group names, and any unusual jumps between consecutive rows — can you run the full audit on the headcount field?”
Open roles tracking anomaly detection
“We track open roles across company groups weekly and I want to spot any sudden changes between adjacent rows in this dataset of 80 records. Please run the adjacent row changes and record quality audit on the open_roles field.”
Pre-analytics headcount data cleaning
“Before I hand this headcount observation dataset off to our analytics team, I need a quality audit and string normalisation on the company_group values plus a check for row-to-row changes in headcount — the dataset has about 150 rows.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-company-12-200?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need a bundled, cost-effective (3 reports for $0.01 USDC) offline analysis of company headcount observation records covering quality auditing, string normalisation, and adjacent row change detection simultaneously — without requiring any live lookups or external data enrichment. Ideal for pre-pipeline data validation or exploratory data quality checks on workforce datasets up to 200 rows.
Side effects
- Rows array exceeds 200 items — request rejected
- Missing required fields (row_id, company_group, date, headcount, open_roles) in any row — validation error
- Date strings not matching YYYY-MM-DD pattern — schema validation failure
- Invalid field enum value (must be 'headcount' or 'open_roles') — rejected
- Empty rows array (minItems:1 violated) — rejected
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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