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Question Bank Coverage — String Normalisation + Exact Row Deduplication
x402
Question Bank Coverage — String Normalisation + Exact Row Deduplication is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-29).
Normalises strings and deduplicates rows in question bank coverage records (item_count, objective_count), producing 2 analytical reports for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Question bank coverage — String normalisation + Exact row deduplication: String normalisation + Exact row deduplication 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
Two analytical reports covering: (1) string-normalised versions of the input question bank coverage records with course group and string fields standardised, and (2) a deduplicated row set identifying and removing exact duplicate records, along with summary statistics on item_count and objective_count across up to 200 input rows.
Example use cases
Deduplicating curriculum coverage exports
“I've exported question bank coverage data from our LMS with possible duplicate rows — can you normalise the course group names and remove any exact duplicates? Here are the rows: row-1, 2026-09-01, group-a, 25 items, 5 objectives; row-2, 2026-09-01, group-a, 25 items, 5 objectives; row-3, 2026-09-02, group-b, 40 items, 8 objectives.”
Standardising question bank audit records
“Our question bank audit has inconsistent string formatting across course groups — can you normalise those strings and flag any exact duplicate rows? I have 5 records: row-1 through row-5, dated 2026-11-01 to 2026-11-05, groups like 'Group A', 'group-a', 'GROUP A', with item counts 10, 10, 20, 30, 20 and objective counts 2, 2, 4, 6, 4.”
Pre-analysis cleanup of objective coverage data
“Before I run my coverage analysis I need to clean my question bank data — normalise the strings and deduplicate exact rows. I've got 6 entries: row-1 to row-6, dates from 2026-08-01 to 2026-08-06, course groups alpha, beta, alpha, gamma, beta, alpha, with item counts 5, 15, 5, 25, 15, 10 and objective counts 1, 3, 1, 5, 3, 2.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-education-18-020?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need lightweight, local string normalisation and exact row deduplication for question bank coverage records without any external data lookups or predictions. Ideal for pre-processing education dataset exports (up to 200 rows) before downstream analysis, especially when you need two packaged reports in a single low-cost call ($0.01 USDC). Not suitable for fuzzy deduplication, semantic matching, or datasets exceeding 200 rows.
Side effects
- More than 200 rows submitted — request rejected with validation error
- Missing required fields (row_id, course_group, date, item_count, objective_count) — row-level validation failure
- Date field not matching YYYY-MM-DD pattern — schema validation error
- row_id exceeds 80 characters — validation rejection
- Numeric fields outside allowed range — schema rejection
- Empty rows array — minItems validation failure
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array |
Tags
x402
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