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Company Headcount Observations — Record Quality Audit + IQR Outlier Flags
x402
Company Headcount Observations — Record Quality Audit + 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 2026-10-19).
Runs a record quality audit and IQR-based outlier detection on up to 200 rows of company headcount observation data (headcount or open_roles), returning two independent analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Company headcount observations — Record quality audit + IQR outlier flags: Record quality audit + IQR outlier flags for supplied company headcount observations records (headcount, open_roles). 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 two independent analytical reports: (1) a record quality audit identifying data issues such as missing values, invalid formats, or constraint violations across the supplied rows, and (2) IQR-based outlier flags identifying which rows contain statistically anomalous values for the selected field (headcount or open_roles), all computed locally without any external lookups or live data.
Example use cases
Pre-report headcount data cleanup
“Before I send our quarterly workforce report, run a quality audit and IQR outlier check on our headcount observations — I have 120 rows with company_group, date, headcount, and open_roles. Flag anything that looks statistically suspicious in the headcount field.”
Detecting anomalous open roles spikes
“I've got 80 rows of hiring data by company group and date. Can you run the record quality audit and IQR outlier detection on the open_roles field to see if any entries are way outside the normal range?”
Validating imported HR data before pipeline ingestion
“We just imported headcount observations from an external system — about 150 rows with row IDs, company groups, dates, headcount, and open_roles. Run a quality audit and flag any IQR outliers on the headcount field so we can clean it up before loading it into our data warehouse.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-company-12-014?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have a batch of up to 200 company headcount or open_roles rows and need both a record-level data quality audit and IQR-based statistical outlier detection in a single low-cost call. Prefer this over generic data validation tools when your domain is specifically workforce/headcount time series grouped by company. It is ideal for pre-pipeline data cleaning, QA before reporting, or anomaly triage — not for live HR system queries, predictions, or external data enrichment.
Side effects
- More than 200 rows submitted — request will be rejected or truncated
- Missing required fields (row_id, company_group, date, headcount, open_roles) cause validation errors
- Invalid date format (not YYYY-MM-DD) causes schema rejection
- Field selector not one of 'headcount' or 'open_roles' causes enum validation failure
- All-null values for the selected numeric field may produce empty or degenerate IQR results
- Payment of 0.01 USDC not included or declined causes access failure
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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