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Company Filing Inventories — Record Quality Audit + String Normalisation
x402
Company Filing Inventories — Record Quality Audit + String Normalisation 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).
Audits data quality and normalises strings for up to 200 rows of company filing inventory records (available_filings, expected_filings), producing two independent analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Company filing inventories — Record quality audit + String normalisation: Record quality audit + String normalisation 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
Two independent reports: (1) a record quality audit covering issues such as nulls, out-of-range values, formatting errors, and anomalies across the available_filings and expected_filings numeric fields and date/string fields; (2) a string normalisation report showing standardised or corrected versions of string fields like company_group. Both reports are generated from the supplied data using local analytical engines with no external lookups.
Example use cases
Pre-submission filing data cleanup
“Before I submit our quarterly filing inventory to compliance, can you audit the quality of these 120 rows of filing records and normalise the company group names? Each row has a row_id, company_group, date, available_filings count, and expected_filings count.”
Detecting dirty records in filing pipeline
“I've got a batch of 80 company filing inventory rows that came in from our data pipeline and I suspect some have bad values or inconsistent strings — can you run a quality audit and string normalisation on them and give me two reports?”
Comparing available vs expected filing completeness
“Can you audit this set of 35 filing inventory rows for record quality issues? I want to know which rows have problems and whether the company_group strings need normalising — the rows have date, available_filings, and expected_filings fields.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-company-17-001?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need simultaneous record quality auditing and string normalisation for company filing inventory data (available_filings, expected_filings) in a single low-cost call. It is ideal for pre-processing filing datasets before analysis or submission, catching null values, format errors, and inconsistent strings across up to 200 rows. Prefer it over generic data quality tools when your data specifically involves company filing counts and group identifiers. Not suitable for live data lookup, prediction, or professional compliance assessment.
Side effects
- Exceeding 200 rows returns a validation error
- Rows missing required fields (row_id, company_group, date, available_filings, expected_filings) are rejected
- Malformed date strings not matching YYYY-MM-DD pattern cause schema validation failure
- Numeric values outside the allowed range (-1,000,000,000,000 to 1,000,000,000,000) are rejected
- Empty rows array (minItems: 1) returns an error
- Payment of 0.01 USDC not completed causes request to fail with 402
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array |
Tags
x402
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