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Onboarding Progress Trailing Mean Series & Secondary-Measure Weighted Mean
x402
Onboarding Progress Trailing Mean Series & 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 2026-10-25).
Computes a trailing mean time series and a secondary-measure weighted mean for onboarding progress data (completed_steps, required_steps) across up to 200 rows, returning two analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Onboarding progress — Trailing mean series + Secondary-measure weighted mean: Trailing mean series + Secondary-measure weighted mean for supplied onboarding progress records (completed_steps, required_steps). 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 for the supplied onboarding progress rows: (1) a trailing mean time series computed over the specified window for the selected field (completed_steps or required_steps), and (2) a secondary-measure weighted mean aggregation. Results are computed locally with no external lookups or predictions.
Example use cases
Smoothing team onboarding completion trends
“I have weekly onboarding data for two teams over the last 3 months — each row has a date, team group, completed steps, and required steps. Can you run a trailing mean series with a window of 4 on completed_steps so I can see the smoothed trend for each group?”
Weighted mean for required steps by group
“Can you compute the secondary-measure weighted mean for our onboarding required_steps data? I've got about 50 rows across 5 team groups with dates and step counts — I want to understand how the weighting shakes out across the dataset.”
Dual analytics report for onboarding audit
“I need both a trailing mean series and a weighted mean report on our onboarding progress records for last quarter — roughly 120 rows covering multiple teams, with completed_steps and required_steps per row. Use a trailing window of 7 and focus on completed_steps.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-operations-08-151?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need to compute both a rolling/trailing mean time series AND a weighted mean on the same onboarding progress dataset in a single call at minimal cost ($0.01 USDC). It is ideal for HR analytics pipelines, onboarding dashboards, and team performance monitoring where completed_steps and required_steps are the primary metrics. Prefer this over general-purpose analytics tools when you want a lightweight, deterministic, no-external-lookup computation on up to 200 rows.
Side effects
- Fewer than 1 row supplied — minimum row count not met
- More than 200 rows supplied — exceeds maximum row limit
- Window size larger than number of rows — trailing mean cannot be computed
- Missing required fields (row_id, date, completed_steps, required_steps) — validation error
- Invalid date format (not YYYY-MM-DD) — pattern mismatch error
- Field enum value not one of completed_steps or required_steps — invalid input
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| window | integer |
Tags
x402
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