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Company Filing Inventories — Record Quality Audit + String Normalisation + Equal-Width Histogram
x402
Company Filing Inventories — 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 2026-10-20).
Runs three local analytical reports (record quality audit, string normalisation, and equal-width histogram) on supplied company filing inventory data covering available_filings and expected_filings fields, for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Company filing inventories — Record quality audit + String normalisation + Equal-width histogram: Record quality audit + String normalisation + Equal-width histogram for supplied company filing inventories records (available_filings, expected_filings). 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 flagging nulls, out-of-range values, and structural issues per row; (2) a string normalisation report identifying and correcting inconsistencies in company_group and date fields; and (3) an equal-width histogram breaking the selected numeric field (available_filings or expected_filings) into the specified number of bins with counts per bin. All processing is local with no external lookups.
Example use cases
Filing inventory data quality check
“I have a dataset of 50 company filing inventory rows with available_filings and expected_filings values — can you audit them for record quality issues, normalise the company_group strings, and give me a 10-bin histogram on available_filings?”
Detecting missing filings across groups
“We track expected vs available filings for two company groups across Q3 2024. Can you run the quality audit and string normalisation reports on these 30 rows to flag any nulls or inconsistent group names?”
Distribution analysis of expected filings
“I want to understand the distribution of expected_filings values across our 120 filing inventory records — can you run an equal-width histogram with 8 bins, plus the quality audit and string normalisation reports at the same time?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-company-17-202?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need to simultaneously profile, audit, and understand the distribution of company filing inventory data (available_filings / expected_filings) in a single low-cost call. It is ideal for batch data quality workflows on up to 200 rows where no live external data, predictions, or professional assessments are needed. It bundles three distinct analytical reports for $0.01 USDC, making it more efficient than calling separate quality, normalisation, and histogram endpoints independently.
Side effects
- Exceeding 200 rows returns a validation error
- Bins value outside 1–30 range causes a schema rejection
- Rows missing required fields (row_id, date, available_filings, expected_filings) fail validation
- Malformed date strings not matching YYYY-MM-DD pattern are rejected
- Numeric values outside ±1,000,000,000,000 fail schema validation
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| bins | integer | |
| rows | array | |
| field | string |
Tags
x402
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