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Texture Baking Analytics — Record Quality Audit, String Normalisation & Two-Measure Correlation
x402
Texture Baking Analytics — Record Quality Audit, String Normalisation & Two-Measure Correlation 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 local analytical reports on texture baking records: data quality audit, string normalisation, and Pearson/Spearman correlation between bake_seconds and texture_pixels.
Price / call$0.01
Success—
StatusUnknown
How this service works
Texture baking — Record quality audit + String normalisation + Two-measure correlation: Record quality audit + String normalisation + Two-measure correlation 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
Returns three structured analytical reports: (1) a record quality audit flagging nulls, out-of-range values, and malformed dates; (2) a string normalisation report showing standardised asset_group values; and (3) a two-measure correlation report (e.g. Pearson/Spearman) between bake_seconds and texture_pixels across the supplied rows.
Example use cases
Pipeline data quality check
“I've exported 120 rows from our texture baking pipeline — each row has a row_id, asset_group, date, bake_seconds, and texture_pixels. Can you run a quality audit on them to flag missing or bad values, normalise the asset_group strings, and tell me if bake_seconds and texture_pixels are correlated?”
Render farm bake time analysis
“We ran a render farm job and collected bake logs for 80 assets across two groups. Can you check the data quality, clean up the group labels, and calculate the correlation between bake time in seconds and the texture pixel count?”
QA report for 3D asset batch
“I need a QA report on this batch of 3D texture baking records — about 30 rows with bake_seconds and texture_pixels columns. Please audit for data issues, normalise the string fields, and show me whether bake duration and pixel resolution move together.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-creative-10-204?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have up to 200 texture baking records and need all three analyses — data quality audit, string normalisation, and correlation — in a single cheap call ($0.01 USDC). It is self-contained with no external lookups, making it fast, deterministic, and safe for sensitive internal pipeline data. Prefer alternatives if you need predictions, external enrichment, or more than 200 rows.
Side effects
- Exceeding 200 rows returns a validation error
- Missing required fields (row_id, bake_seconds, texture_pixels) causes row-level rejection
- Malformed date strings not matching YYYY-MM-DD pattern are flagged or rejected
- Null numeric values may reduce correlation sample size and affect result accuracy
- Empty rows array returns an error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array |
Tags
x402
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