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Texture Baking Analytics — Category Frequencies + IQR Outlier Flags
x402
Texture Baking Analytics — Category Frequencies + IQR Outlier Flags is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-27).
Computes category frequency distributions and IQR-based outlier flags for texture baking records (bake_seconds or texture_pixels) across up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Texture baking — Category frequencies + IQR outlier flags: Category frequencies + IQR outlier flags 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: (1) category frequency counts broken down by asset_group, showing how many records fall in each category; and (2) IQR-based outlier flags identifying which rows have extreme values for the selected numeric field (bake_seconds or texture_pixels). Both reports are computed locally without external lookups.
Example use cases
Detect slow outlier bake jobs
“I've got a batch of 120 texture baking records with bake times — can you flag any bake_seconds values that are IQR outliers and also show me how many records fall into each asset group?”
Audit pixel count anomalies by group
“Run frequency and IQR outlier analysis on my texture baking dataset using the texture_pixels field — I want to see which asset groups dominate and which pixel values look statistically extreme.”
QA render pipeline by asset group
“I have 80 rows of texture bake job data across groups like 'characters', 'environments', and 'props' — give me the category frequency breakdown and flag any IQR outliers in bake_seconds so I can spot problem assets.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-creative-10-107?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have texture baking production data and need both categorical distribution analysis (how many records per asset group) and statistical outlier detection (IQR method) in a single low-cost call. Ideal for 3D pipeline QA, render farm audits, or asset management workflows where you want to identify anomalous bake times or texture sizes without setting up a full analytics stack.
Side effects
- Exceeding 200 rows returns an error or truncation
- Missing required fields (row_id, bake_seconds, texture_pixels) cause validation failure
- Invalid date format (non-YYYY-MM-DD) triggers schema rejection
- Null values in the selected numeric field may affect IQR calculation
- Invalid enum value for 'field' parameter causes rejection
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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