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Texture Baking Data Quality Suite — Record Audit + String Normalisation + IQR Outlier Flags
x402
Texture Baking Data Quality Suite — Record Audit + String Normalisation + 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 2026-10-17).
Runs three local analytical reports on texture baking records: a record quality audit, string normalisation, and IQR-based outlier flagging for bake_seconds and texture_pixels fields.
Price / call$0.01
Success—
StatusUnknown
How this service works
Texture baking — Record quality audit + String normalisation + IQR outlier flags: Record quality audit + String normalisation + IQR outlier flags 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 independent analytical reports for the submitted texture baking rows: (1) a record quality audit identifying missing, malformed, or invalid fields; (2) normalised string representations of text fields such as asset_group; (3) IQR-based outlier flags indicating which rows have anomalous values in the selected numeric field (bake_seconds or texture_pixels). All analysis is performed locally with no external lookups.
Example use cases
Pre-pipeline texture bake data validation
“I have a batch of texture baking logs with up to 150 rows — each has a row_id, asset_group, date, bake_seconds, and texture_pixels. Can you audit them for record quality issues, normalise the asset_group strings, and flag any IQR outliers in bake_seconds?”
QA audit for texture rendering anomalies
“My rendering team exported 80 texture baking records and I suspect there are outlier bake times messing up our estimates. Run the three-report quality suite on these rows and flag anything outside the IQR range for texture_pixels.”
Data cleaning before asset group reporting
“Before I roll these texture baking records into our weekly report, can you normalise the string fields and do a record quality audit on all 200 rows? Also flag any IQR outliers in bake_seconds so I know which rows to investigate.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-creative-10-203?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have texture baking tabular data (up to 200 rows) and need all three of: record quality auditing, string normalisation, and IQR outlier detection in a single low-cost call. It is purpose-built for the 3D graphics / texture baking domain and combines three reports for $0.01 USDC, making it efficient versus calling separate data-quality services. Prefer it when no live lookup or ML prediction is needed — purely local analytical processing of supplied records.
Side effects
- Submitting more than 200 rows returns an error (maxItems constraint)
- Missing required fields (row_id, asset_group, date, bake_seconds, texture_pixels) causes validation failure
- Invalid date format (non-YYYY-MM-DD) triggers schema rejection
- Null values in both numeric fields may reduce usefulness of IQR outlier report
- Selecting an invalid field enum value causes request rejection
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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