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Texture Baking Analytics: String Normalisation + Date-by-Category Pivot
x402
Texture Baking Analytics: String Normalisation + Date-by-Category Pivot is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-22).
Runs two local analytical reports on supplied texture baking records: string normalisation of asset group labels and a date-by-category pivot table for bake_seconds or texture_pixels.
Price / call$0.01
Success—
StatusUnknown
How this service works
Texture baking — String normalisation + Date by category pivot: String normalisation + Date by category pivot for supplied texture baking records (bake_seconds, texture_pixels). 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 derived from the supplied rows: (1) a string-normalised view of asset_group labels, and (2) a date-by-category pivot table showing the selected metric (bake_seconds or texture_pixels) aggregated by date and asset_group. No external lookups or predictions are made; all computation is local to the engine.
Example use cases
Bake time pivot by asset group
“I've got 50 rows of texture baking records with asset groups and dates — can you pivot bake_seconds by date and category so I can see which groups are taking the most time each day?”
Normalise messy asset group labels
“My texture baking dataset has inconsistent asset_group strings like 'Group-A', 'group_a', 'GROUP A' — can you run string normalisation on my 80 rows so they're consistent?”
Pixel count summary by category
“Here are 120 rows of baking data with texture_pixels per asset group — can you generate the date-by-category pivot on texture_pixels so I can see pixel totals broken down by group and date?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-creative-10-035?utm_source=zero.xyzWhen to prefer
Use this endpoint when you have up to 200 texture baking records and need both a string normalisation pass on asset group labels and a date-pivoted aggregation of a numeric baking metric in a single low-cost call. It is ideal for offline/batch analytical reporting on supplied data without requiring any live data lookup, prediction, or external integrations.
Side effects
- More than 200 rows submitted — request rejected due to row limit
- Missing required fields (row_id, date, asset_group) on any row — validation error
- Invalid date format (not YYYY-MM-DD) — pattern mismatch error
- Invalid field enum value (not bake_seconds or texture_pixels) — schema rejection
- All numeric values null — pivot may return empty or null aggregates
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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