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Tutoring Sessions — Category Frequencies + IQR Outlier Flags
x402
Tutoring Sessions — Category Frequencies + IQR Outlier Flags 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).
Analyzes tutoring session records to produce category frequency distributions and IQR-based outlier flags for up to 200 rows across two independent reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Tutoring sessions — Category frequencies + IQR outlier flags: Category frequencies + IQR outlier flags for supplied tutoring sessions records (session_minutes, session_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 two independent analytical reports: (1) category frequency counts for the course_group dimension showing how many records fall into each group, and (2) IQR-based outlier flags for the chosen numeric field (session_minutes or session_count), identifying rows that fall outside the interquartile range bounds. Results are computed locally from the supplied data with no external lookups.
Example use cases
Outlier detection in tutoring session durations
“I have 150 tutoring session records with course groups, dates, and session_minutes values — can you flag any sessions with unusually long or short durations using IQR outlier detection, and also tell me how frequently each course group appears?”
Course group frequency audit for tutoring platform
“Run a category frequency breakdown on my tutoring session dataset so I can see how many sessions each course group has logged — also flag any session_count values that are statistical outliers using the IQR method. I have about 80 rows to analyze.”
Quality check on exported tutoring session data
“I exported session data from our tutoring system — can you compute category frequencies for course_group and identify any IQR outliers in the session_count field across these 200 rows?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-education-16-107?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need fast, local statistical analysis on tutoring session data specifically — combining category frequency counts with IQR-based outlier detection in a single paid call. Ideal for education platforms auditing session quality, detecting anomalous session durations or counts, or summarizing group-level distributions without needing a full analytics pipeline. Best when dataset fits within 200 rows and you want two complementary statistical reports for $0.01 USDC.
Side effects
- Exceeding 200 rows results in rejection or truncation
- Missing required fields (row_id, course_group, date, session_minutes, session_count) cause validation errors
- Null numeric values may affect IQR calculation accuracy
- Invalid date format (non-YYYY-MM-DD) triggers schema validation failure
- Numeric values outside allowed range (-1T to 1T) are rejected
- Empty row array returns an error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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