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Shot Schedules String Normalisation and Trailing Mean Series
x402
Shot Schedules String Normalisation and Trailing Mean Series is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-21).
Runs string normalisation and trailing mean series analysis on shot schedule records (planned_hours, actual_hours) for up to 200 rows, returning two analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Shot schedules — String normalisation + Trailing mean series: String normalisation + Trailing mean series for supplied shot schedules records (planned_hours, actual_hours). 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: (1) a string normalisation report over the specified field in the shot schedule rows, and (2) a trailing mean series (rolling average) over the same field using the specified window size, both computed locally without external lookups.
Example use cases
Film production hours trend analysis
“I have 120 rows of daily shot schedule data with planned and actual hours across two asset groups. Can you run string normalisation and a trailing mean series on actual_hours with a window of 5 so I can see the rolling trend?”
Planned hours deviation smoothing
“Here are 80 shot schedule records for our TV episode shoot. Run the string normalisation and trailing mean analysis on planned_hours with a window of 10 — I want to see both reports to understand how our schedule drifted.”
Asset group hours pattern review
“I've got 200 shot schedule rows tagged with asset groups and dates. Please apply string normalisation and trailing mean series to actual_hours using a window of 3 and return both analytical reports.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-creative-13-028?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have shot schedule tabular data with planned and actual hours and need both string normalisation and rolling mean analysis in a single call at low cost ($0.01 USDC for two reports). Ideal for production scheduling analytics on batches up to 200 rows where no live data lookup or external predictions are needed.
Side effects
- More than 200 rows submitted — endpoint enforces maxItems:200
- Missing required fields (row_id, date, planned_hours, actual_hours) cause validation errors
- Date values not matching YYYY-MM-DD pattern are rejected
- Window size outside range 2–200 causes schema validation failure
- Null values in the target numeric field may affect trailing mean computation
- Invalid field selector (not 'planned_hours' or 'actual_hours') causes rejection
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| window | integer |
Tags
x402
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