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Question Bank Coverage — String Normalisation + Duplicate Key Report
x402
Question Bank Coverage — String Normalisation + Duplicate Key Report is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-30).
Normalises strings and detects duplicate keys in question bank coverage records (item_count, objective_count) for up to 200 rows, producing two independent analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Question bank coverage — String normalisation + Duplicate key report: String normalisation + Duplicate key report 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 independent reports: (1) a string normalisation report showing cleaned/standardised versions of string fields (e.g. course_group), and (2) a duplicate key report identifying rows sharing the same key values across the submitted question bank coverage records. Results are computed locally with no external lookups.
Example use cases
Cleaning messy course group labels
“I've exported 50 rows of question bank coverage records from our LMS and the course_group field has inconsistent capitalisation and whitespace. Can you normalise those strings and flag any duplicate row IDs? Here are the rows with their row_id, course_group, date, item_count, and objective_count values.”
Pre-import duplicate audit for curriculum data
“Before I import these 120 question bank coverage records into our new platform, can you run a duplicate key check and string normalisation pass on them? I want to make sure there are no repeated row IDs and that all course_group names are standardised.”
Weekly question bank data quality check
“Every Monday I get a fresh export of up to 200 question bank coverage rows with item counts and objective counts. Can you run the string normalisation and duplicate key reports on this week's batch and tell me which rows have problems?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-education-18-021?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need to clean and deduplicate question bank coverage data (item_count and objective_count records) in a single low-cost call. It is ideal for pre-import data quality checks, periodic audits of education dataset exports, or any workflow where you need both string normalisation and duplicate detection on up to 200 curriculum coverage rows without external API calls or live lookups.
Side effects
- Exceeding 200 rows returns a validation error
- Missing required fields (row_id, course_group, date, item_count, objective_count) causes row rejection
- Invalid date format (not YYYY-MM-DD) triggers a schema validation error
- Numeric values outside allowed range cause rejection
- Empty rows array returns an error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array |
Tags
x402
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