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Company Filing Inventories — Record Quality Audit + IQR Outlier Flags
x402
Company Filing Inventories — 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 2026-10-20).
Runs a record quality audit and IQR-based outlier detection on up to 200 rows of company filing inventory data (available_filings, expected_filings), returning two independent analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Company filing inventories — Record quality audit + IQR outlier flags: Record quality audit + IQR outlier flags for supplied company filing inventories records (available_filings, expected_filings). 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 reports: (1) a record quality audit identifying data issues such as nulls, format errors, or invalid values across the supplied rows, and (2) IQR outlier flags identifying which rows contain statistically anomalous values for the selected field (available_filings or expected_filings). No live lookup or external data is used — all analysis is performed locally on the supplied data.
Example use cases
Compliance filing data quality check
“I have a dataset of 120 company filing inventory rows with dates, company groups, and available_filings counts — can you run a record quality audit and flag any IQR outliers in the available_filings field so I can clean up the bad records before submitting?”
Expected filings anomaly detection
“We track expected_filings across several company groups by date and want to know which rows look statistically unusual — please audit our 80-row dataset and flag outliers in expected_filings using IQR analysis.”
Pre-reporting data validation for filing inventory
“Before we finalize our quarterly filing report, can you check this batch of 150 company filing records for quality issues and IQR-based outliers in available_filings? I'll give you the rows with row_id, company_group, date, available_filings, and expected_filings.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-company-17-014?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have a batch of company filing inventory records (up to 200 rows) and need both a general record quality audit and IQR-based statistical outlier detection in a single call. It is ideal for pre-processing or data cleaning pipelines where you want to identify dirty or anomalous filing records without any external lookups or live data. Prefer this over generic data validation tools when your data specifically involves available_filings and expected_filings fields organized by company group and date.
Side effects
- Fewer than 1 row or more than 200 rows submitted — request rejected
- Missing required fields (row_id, company_group, date, available_filings, expected_filings) on any row — validation error
- Invalid date format (non YYYY-MM-DD) — schema validation failure
- Field selector not one of 'available_filings' or 'expected_filings' — enum validation error
- All values null for selected field — IQR computation may be undefined or return no flags
- Payment not received or insufficient — 402 payment required error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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