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Tutoring Sessions — Record Quality Audit + String Normalisation + Numeric Distribution
x402
Tutoring Sessions — Record Quality Audit + String Normalisation + Numeric Distribution is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-26).
Performs three local analytical reports on tutoring session records: record quality audit, string normalisation, and numeric distribution summary for session_minutes or session_count fields.
Price / call$0.01
Success—
StatusUnknown
How this service works
Tutoring sessions — Record quality audit + String normalisation + Numeric distribution: Record quality audit + String normalisation + Numeric distribution for supplied tutoring sessions records (session_minutes, session_count). Up to 200 rows; 3 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 3 supplied-data reports for up to 200 rows.
Output
Three independent analytical reports: (1) a record quality audit flagging missing, malformed, or out-of-range values; (2) string normalisation results for text fields like course_group; and (3) a numeric distribution summary (e.g. quantiles, min, max, mean) for the selected numeric field (session_minutes or session_count). All analysis is performed locally on the supplied rows with no external lookups.
Example use cases
Pre-load data quality check
“Before I import this batch of tutoring session logs into our database, can you run a record quality audit plus string normalisation on the course_group names and give me a numeric distribution of session_minutes? Here are 150 rows with row_id, course_group, date, session_minutes, and session_count.”
Identify inconsistent course labels
“I suspect our tutoring data has inconsistent course group labels — can you normalise the strings in my course_group column and also audit the overall record quality across these 80 tutoring session rows? I also want a distribution of session_count.”
Education analytics pipeline validation
“We're building a tutoring analytics dashboard and need to validate incoming data. Can you run the three-report bundle — quality audit, string normalisation, and numeric distribution for session_minutes — on this set of 200 tutoring session records before we pass them downstream?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-education-16-193?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have up to 200 tutoring session records and need all three data-hygiene operations — quality auditing, string normalisation, and numeric distribution — bundled into a single low-cost call. It is ideal for pre-processing education data before downstream analytics or storage, and when no external lookups, predictions, or live data enrichment are needed.
Side effects
- Submitting more than 200 rows returns an error — batch must be split
- Missing required fields (row_id, date, session_minutes, session_count) causes validation failure
- Malformed date strings not matching YYYY-MM-DD pattern are rejected
- Numeric values outside the allowed range (±1 trillion) may be flagged or rejected
- Empty rows array returns an error — at least 1 row is required
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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