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Training Assessments — Trailing Mean Series + Adjacent Row Changes
x402
Training Assessments — Trailing Mean Series + Adjacent Row Changes 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).
Computes a trailing mean series and adjacent row changes for pre_score or post_score fields across up to 200 training assessment records, returning two analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Training assessments — Trailing mean series + Adjacent row changes: Trailing mean series + Adjacent row changes for supplied training assessments records (pre_score, post_score). 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) a trailing mean series showing the rolling average of the selected score field (pre_score or post_score) over the specified window size for each row, and (2) an adjacent row changes report showing the difference between consecutive rows' score values — both computed locally on the supplied dataset of up to 200 records.
Example use cases
Track score trends across training cohorts
“I have 50 training assessment records with pre and post scores across several course groups. Can you compute a trailing mean series with a window of 4 on the post_score field and also show me the adjacent row changes so I can see how scores shifted session by session?”
Detect improvement dips in e-learning sessions
“Here are 120 rows of our e-learning assessment data with dates, course groups, and pre/post scores. Run a rolling average with window 5 on pre_score and include the adjacent row changes — I want to spot any dips or spikes between consecutive sessions.”
Compare score momentum across a training program
“I've got 80 rows of assessment records from our onboarding training program. Use window size 3 on post_score to generate a trailing mean series and adjacent row changes report — I want to understand the momentum of score changes over the course duration.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-education-11-146?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need both a rolling/trailing mean time series and adjacent row-to-row change analysis on training assessment score data (pre_score or post_score) in a single low-cost call. Ideal when you have up to 200 pre-aggregated assessment records and want lightweight local statistical computation without sending data to an external prediction or ML service. Best suited for education analytics, L&D reporting, or training program evaluation workflows.
Side effects
- Fewer than 1 row supplied — minimum 1 row required
- More than 200 rows submitted — exceeds maxItems limit
- Invalid date format (must match YYYY-MM-DD pattern)
- Window size less than 2 or greater than 200
- Missing required fields: row_id, course_group, date, pre_score, or post_score
- Invalid field enum value — must be 'pre_score' or 'post_score'
- Payment not included or insufficient — requires 0.01 USDC via x402 protocol
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| window | integer |
Tags
x402
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