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Texture Baking Data Quality Suite — Audit + String Normalisation + Missing-Value Fill
x402
Texture Baking Data Quality Suite — Audit + String Normalisation + Missing-Value Fill 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 three data quality reports on texture baking records: a record quality audit, string normalisation, and explicit missing-value fill for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Texture baking — Record quality audit + String normalisation + Explicit missing-value fill: Record quality audit + String normalisation + Explicit missing-value fill for supplied texture baking records (bake_seconds, texture_pixels). Up to 200 rows; 3 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 3 supplied-data reports for up to 200 rows.
Output
Three independent reports: (1) a record quality audit flagging issues across the submitted rows, (2) a string normalisation report showing cleaned asset_group and string fields, and (3) an explicit missing-value fill report showing imputed values for the chosen field (bake_seconds or texture_pixels) using the selected method (zero, mean, or median). All reports are based entirely on the supplied data with no external lookups.
Example use cases
Pre-pipeline texture data cleanup
“I have 120 texture baking records with messy asset_group names and some missing bake_seconds values — can you run the quality audit, normalise those strings, and fill missing bake_seconds using median imputation so the data is clean before I load it into the pipeline?”
QA check on baked texture pixel data
“Run a full data quality audit plus string normalisation and fill in any missing texture_pixels values with zeros for these 80 texture baking records — I want to see all three reports.”
Batch validation for animation asset group
“I've got a batch of 200 texture baking records across multiple asset groups and I need to check for data quality issues, clean up any inconsistent string formatting, and replace missing bake_seconds with the mean. Can you process all three reports for me?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-creative-10-208?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need three combined data quality operations — audit, string normalisation, and missing-value fill — on texture baking records (bake_seconds, texture_pixels) in a single low-cost call. It is ideal for 3D graphics or creative production pipelines needing lightweight, offline data cleaning without any external API calls, ML predictions, or live lookups.
Side effects
- Exceeding 200 rows causes rejection
- Invalid date format (not YYYY-MM-DD) triggers validation error
- Numeric values outside the allowed range cause schema rejection
- Missing required fields (row_id, date, asset_group) cause row-level errors
- Invalid enum values for method or field return a bad request error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| method | string |
Tags
x402
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