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Learning Resource Usage — String Normalisation + Secondary-Measure Weighted Mean
x402
Learning Resource Usage — String Normalisation + Secondary-Measure Weighted Mean is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-11-02).
Normalises string fields and computes a secondary-measure weighted mean across up to 200 learning resource usage records (access_count, resource_minutes), returning two analytical reports per call.
Price / call$0.01
Success—
StatusUnknown
How this service works
Learning resource usage — String normalisation + Secondary-measure weighted mean: String normalisation + Secondary-measure weighted mean for supplied learning resource usage records (access_count, resource_minutes). 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 per call: (1) string-normalised course_group labels applied across all rows, and (2) a secondary-measure weighted mean computed over the specified field (access_count or resource_minutes) for the supplied dataset of up to 200 rows. No external lookups or predictions are included.
Example use cases
Weekly course engagement analysis
“I have a week's worth of learning resource usage — 12 rows with course group names, dates, access counts and resource minutes. Can you normalise the group name strings and give me a weighted mean report using access_count as the field?”
Compare two course groups' resource usage
“I've got 50 rows of usage data split between 'Group Alpha' and 'Group Beta' with daily access_count and resource_minutes. Run string normalisation on the group names and compute the secondary-measure weighted mean on resource_minutes for me.”
Monthly e-learning audit batch report
“Here are 200 rows of monthly learning resource usage records with course_group, date, access_count, and resource_minutes fields. Please normalise the strings and produce the two weighted-mean analytical reports using access_count as the primary field.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-education-12-034?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need both string normalisation of course group labels AND a weighted mean computation on learning resource usage data (access_count or resource_minutes) in a single low-cost call. It is ideal for education analytics pipelines handling up to 200 rows of usage records where two bundled local analytical reports are sufficient and no live data lookup, prediction, or external service is required.
Side effects
- More than 200 rows submitted — request rejected, max 200 rows enforced
- Missing required fields (row_id, course_group, date, access_count, resource_minutes) — validation error
- Invalid date format (must match YYYY-MM-DD pattern) — schema validation failure
- Numeric values outside allowed range (±1,000,000,000,000) — validation error
- Empty rows array (minItems: 1 not satisfied) — schema rejection
- Invalid field enum value (must be access_count or resource_minutes) — rejected
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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