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Texture Baking Analytics — String Normalisation & Keyed Dataset Comparison
x402
Texture Baking Analytics — String Normalisation & Keyed Dataset Comparison 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).
Normalises strings and performs keyed comparison across two supplied texture baking datasets (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 — String normalisation + Keyed dataset comparison: String normalisation + Keyed dataset comparison 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
Two analytical reports: (1) a string normalisation report detailing how string fields (row_id, asset_group, date) were cleaned and standardised across both datasets, and (2) a keyed dataset comparison report showing row-by-row differences in bake_seconds and texture_pixels between the 'rows' and 'other' inputs, keyed by row_id. No external lookups or predictions are included.
Example use cases
Spot-check two render pipeline exports
“I have two exports from our texture baking pipeline for the same asset groups on 2026-10-01 through 2026-10-04 — can you normalise the strings and run a keyed comparison to show me which rows have different bake_seconds or texture_pixels values between the two runs?”
Audit asset group bake time consistency
“We ran our texture baker twice this week across group-a and group-b assets and I need to know if the bake_seconds match row-by-row — can you normalise all the string fields and compare the two datasets keyed by row_id?”
QA check before merging texture datasets
“Before I merge these two texture baking record sets, can you do a string normalisation pass and a keyed comparison for up to 50 rows, flagging any discrepancies in bake_seconds or texture_pixels by asset group and date?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-creative-10-036?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have two batches of texture baking records (up to 200 rows each) and need both string normalisation and a keyed row-by-row comparison in a single low-cost call ($0.01 USDC). It operates entirely on supplied data with no external API calls, making it deterministic and offline-safe. Prefer it over general data-diff tools when your data specifically contains bake_seconds and texture_pixels fields organised by asset_group and date.
Side effects
- Exceeding 200 rows in either dataset returns a validation error
- Missing required fields (row_id, asset_group, date, bake_seconds, texture_pixels) causes row rejection
- Date strings not matching YYYY-MM-DD pattern fail schema validation
- Numeric values outside ±1,000,000,000,000 range are rejected
- Empty rows array (minItems: 1 violated) returns an error
- Mismatched row_ids between datasets result in unmatched-row entries in comparison report
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| other | array |
Tags
x402
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