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Question Bank Coverage — String Normalisation + Numeric Interval Filter
x402
Question Bank Coverage — String Normalisation + Numeric Interval Filter is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-11-03).
Normalises course_group strings and filters question bank coverage rows by a numeric interval on item_count or objective_count, returning up to 2 reports for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Question bank coverage — String normalisation + Numeric interval filter: String normalisation + Numeric interval filter for supplied question bank coverage records (item_count, objective_count). 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 up to 2 analytical reports: one covering string-normalised course_group values and one covering rows filtered to the specified numeric interval on the chosen field (item_count or objective_count). Each report reflects local computation on the supplied rows with no external lookups.
Example use cases
Filter overloaded question bank items
“I've got a batch of question bank records with item_count and objective_count values — can you normalise the course_group names and filter down to only the rows where item_count is between 15 and 100? Here are the rows: row-1, 2026-10-01, group-a, item_count=10, objective_count=1 … up to row-50.”
Audit thin curriculum coverage
“Can you run a coverage check on my question bank data and flag only the records where objective_count falls between 2 and 5? I have about 80 rows across course groups like 'intro-math' and 'adv-science', and I also want the course group strings normalised.”
Compare coverage across date range
“I have 120 question bank rows dated from 2026-01-01 to 2026-06-30 across groups like 'biology-101' and 'chemistry-202'. Please normalise the course_group field and filter to rows where item_count is between 20 and 200, then give me both reports.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-education-18-026?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have question bank coverage data with course_group strings that need normalisation and numeric fields (item_count or objective_count) that need interval filtering, and you want both analyses in a single $0.01 call covering up to 200 rows — without needing live data lookup, prediction, or external action.
Side effects
- Rows array empty or missing — validation error returned
- More than 200 rows submitted — request rejected with maxItems error
- Date field does not match YYYY-MM-DD pattern — schema validation failure
- minimum greater than maximum — may return empty filtered result set
- field enum value not 'item_count' or 'objective_count' — schema rejection
- item_count or objective_count outside ±1,000,000,000,000 range — rejected
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| maximum | number | |
| minimum | number |
Tags
x402
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