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Document Section Coverage Analyzer — Record Quality Audit, String Normalisation & Two-Measure Correlation
x402
Document Section Coverage Analyzer — Record Quality Audit, String Normalisation & Two-Measure Correlation is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-23).
Runs three local analytical reports (record quality audit, string normalisation, and two-measure correlation) on up to 200 document section coverage records containing present_sections and required_sections fields.
Price / call$0.01
Success—
StatusUnknown
How this service works
Document section coverage — Record quality audit + String normalisation + Two-measure correlation: Record quality audit + String normalisation + Two-measure correlation for supplied document section coverage records (present_sections, required_sections). 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 identifying missing, malformed, or out-of-range values across the supplied rows; (2) a string normalisation report cleaning and standardising document_group and other text fields; and (3) a two-measure correlation report quantifying the statistical relationship between present_sections and required_sections across all rows. All processing is performed locally with no external lookups.
Example use cases
Compliance team document coverage audit
“I have 150 rows of document section tracking data for our compliance review — each row has a document group, a date, how many sections are present, and how many are required. Can you run a quality audit on the records, normalise the group name strings, and show me the correlation between present and required sections?”
Editorial team section completeness check
“We track section completeness across our editorial teams by date. I've got 80 rows with document_group, date, present_sections, and required_sections fields. Please audit the data quality, normalise the group labels, and correlate the two section measures so we can see how well teams are meeting their targets.”
Automated pipeline data validation for coverage reports
“Before we publish our monthly coverage report, can you validate the 200 rows of document section data we collected this month — run the record quality audit to flag bad rows, normalise the document_group strings, and compute the correlation between present_sections and required_sections?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-writing-01-204?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need a combined, cost-efficient batch report covering data quality auditing, text normalisation, and correlation analysis for document section coverage records in a single call. It is best suited for offline or pipeline use cases where you already have the data (no live lookup needed) and want three analytical perspectives in one request for $0.01 USDC. Prefer alternatives if you need real-time document fetching, predictive models, or more than 200 rows per batch.
Side effects
- Fewer than 1 row supplied returns a validation error
- More than 200 rows submitted exceeds the batch limit and is rejected
- Rows missing required fields (row_id, document_group, date, present_sections, required_sections) cause schema validation failures
- Dates not matching YYYY-MM-DD pattern are flagged or rejected
- Non-numeric values in present_sections or required_sections fields cause type errors
- Insufficient numeric variance in the two measures may result in undefined or degenerate correlation output
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array |
Tags
x402
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