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Lighting Setups — Record Quality Audit + String Normalisation + Date by Category Pivot
x402
Lighting Setups — Record Quality Audit + String Normalisation + Date by Category Pivot 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 lighting setup records: a record quality audit, string normalisation, and a date-by-category pivot, for up to 200 rows of light_count and render_seconds data.
Price / call$0.01
Success—
StatusUnknown
How this service works
Lighting setups — Record quality audit + String normalisation + Date by category pivot: Record quality audit + String normalisation + Date by category pivot for supplied lighting setups records (light_count, render_seconds). 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: (1) a record quality audit flagging completeness and validity issues per row, (2) a string normalisation report cleaning and standardising text fields like asset_group, and (3) a date-by-category pivot summarising the selected numeric field (light_count or render_seconds) broken down by date and asset group — all computed locally from the supplied data, no external lookups.
Example use cases
Quality check on lighting batch
“I've got about 80 rows of lighting setup records with asset_group, date, light_count, and render_seconds — can you audit the record quality, normalise the string fields, and pivot them by date and category so I can spot issues?”
Pivot render seconds by asset group
“Run a date-by-category pivot on my lighting data using render_seconds as the field — I have 120 rows across a few asset groups and want to see how render times break down over the dates.”
Pre-delivery data validation for lighting assets
“Before I hand off these lighting setup records to the team, can you do a full quality audit and string normalisation on the 60 rows I have? The fields are row_id, asset_group, date, light_count, and render_seconds.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-creative-11-206?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need three bundled analytical operations — quality audit, string normalisation, and date pivot — on lighting setup records in a single cost-efficient call ($0.01 USDC for all three reports). Ideal for pre-processing or QA steps in 3D rendering pipelines where you want to validate, clean, and summarise up to 200 rows of lighting data without any external lookups or live data dependencies.
Side effects
- More than 200 rows submitted — exceeds maxItems limit
- Missing required fields (row_id, asset_group, date, light_count, or render_seconds) causes validation error
- Malformed date string not matching YYYY-MM-DD pattern rejected
- Invalid field enum value (must be light_count or render_seconds)
- Empty rows array (minItems: 1) returns error
- Numeric values outside allowed range cause schema rejection
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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