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Glossary Coverage Record Quality Audit and String Normalisation
x402
Glossary Coverage Record Quality Audit and 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 2026-11-01).
Audits glossary coverage records (covered_terms, required_terms) for data quality issues and normalises strings, returning two independent analytical reports for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Glossary coverage — Record quality audit + String normalisation: Record quality audit + String normalisation for supplied glossary coverage records (covered_terms, required_terms). 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 analytical reports: (1) a record quality audit identifying issues such as missing values, out-of-range numbers, and malformed fields across up to 200 glossary coverage rows; (2) a string normalisation report with cleaned and standardised string values for fields like document_group and row_id. No external lookups or predictions are made; all analysis is performed locally on the supplied data.
Example use cases
Glossary coverage data cleanup before reporting
“I have 50 rows of glossary coverage records with document groups, dates, covered_terms counts, and required_terms counts — can you run both a record quality audit and string normalisation on them so I can clean the dataset before building my monthly report?”
Detecting bad values in term coverage records
“Some of my glossary coverage rows look suspicious — covered_terms or required_terms might be null or out of range. Can you audit these records for quality issues and also normalise any string fields? I've got about 80 rows spanning several document groups dated across Q3 2026.”
Validating imported glossary data from third party
“We just imported glossary coverage data from a vendor — about 120 rows with row IDs, document groups, dates, covered_terms, and required_terms. Can you run a quality audit and string normalisation pass on it so I can flag any problems before loading it into our system?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-writing-20-001?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need both a data quality audit and string normalisation specifically for glossary coverage records containing covered_terms and required_terms fields, and your dataset is up to 200 rows. It is ideal for a one-shot, low-cost ($0.01 USDC) dual-report pass with no external dependencies or live lookups. Prefer alternatives if you need live glossary lookups, predictive analytics, or need to process more than 200 rows at once.
Side effects
- More than 200 rows submitted — request rejected with validation error
- Missing required fields (row_id, document_group, date, covered_terms, required_terms) — row-level error in audit report
- Malformed date format (not YYYY-MM-DD) — validation failure for affected rows
- covered_terms or required_terms outside numeric bounds — flagged or rejected
- Empty rows array — request rejected
- Payment not included or insufficient — x402 payment required error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array |
Tags
x402
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