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Texture Baking Quality Audit + Trailing Mean Series
x402
Texture Baking Quality Audit + 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 a record quality audit and trailing mean series analysis on texture baking data (bake_seconds, texture_pixels) for up to 200 rows, returning two analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Texture baking — Record quality audit + Trailing mean series: Record quality audit + Trailing mean series 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
Returns two analytical reports for the supplied texture baking records: (1) a record quality audit identifying missing values, nulls, and data completeness issues per row, and (2) a trailing mean series computing rolling averages of the selected field (bake_seconds or texture_pixels) over the specified window size, using only the supplied data with no external lookups.
Example use cases
Quality check on baking pipeline records
“I have 120 rows of texture baking job data with bake_seconds and texture_pixels — can you run a record quality audit on them so I can see which rows have missing or suspicious values?”
Rolling average for bake duration analysis
“Can you compute a trailing mean series for bake_seconds across my 80 texture baking records using a window of 10, so I can see how average bake time is trending over dates?”
Dual report for asset group performance review
“I need both a quality audit and a trailing mean series on texture_pixels for my 60 texture baking records grouped by asset_group — use a window of 4 and flag any data issues.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-creative-10-010?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need offline, local analytical computation on texture baking time series data — specifically for data quality auditing combined with trailing mean trend analysis — without requiring any external data sources, predictions, or live lookups. Ideal for 3D rendering pipeline QA workflows processing up to 200 records at a time.
Side effects
- Fewer than 1 row supplied — minimum row count not met
- More than 200 rows supplied — exceeds maximum row limit
- Invalid date format (not YYYY-MM-DD) in row data
- Missing required row fields (row_id, bake_seconds, or texture_pixels)
- Window size smaller than 2 or larger than 200 — out of valid range
- Field value not in allowed enum (must be bake_seconds or texture_pixels)
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| window | integer |
Tags
x402
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