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Lighting Setups Data Quality Pipeline: Record Audit + String Normalisation + Exact Row Deduplication
x402
Lighting Setups Data Quality Pipeline: Record Audit + String Normalisation + Exact Row Deduplication 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 up to 200 lighting setup records — a record quality audit, string normalisation, and exact row deduplication — using light_count and render_seconds as the core measures.
Price / call$0.01
Success—
StatusUnknown
How this service works
Lighting setups — Record quality audit + String normalisation + Exact row deduplication: Record quality audit + String normalisation + Exact row deduplication 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
Three independent analytical reports covering: (1) a record quality audit flagging completeness and validity issues in the lighting setup rows, (2) a string normalisation report showing standardised versions of text fields like asset_group, and (3) an exact row deduplication report identifying and removing fully duplicate records — all computed locally without external lookups.
Example use cases
Quality audit before render pipeline ingestion
“Before I import these lighting setup records into our render pipeline, can you run a quality audit on them? I have about 150 rows with light_count and render_seconds values across multiple asset groups and I need to know which records have issues.”
Deduplicating lighting configuration exports
“I exported our lighting configurations and I think there are exact duplicate rows in there. Can you deduplicate this dataset of around 80 lighting setup records that each have a row_id, asset_group, date, light_count, and render_seconds?”
Normalising asset group strings across studio projects
“Our asset_group names are inconsistently formatted across different studio projects in our lighting data. Can you normalise the strings across these 120 lighting setup rows so everything is standardised?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-creative-11-191?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have lighting setup records (with light_count and render_seconds measures) that need simultaneous quality auditing, string normalisation, and exact deduplication in a single call for a flat fee. It is ideal for pre-pipeline data cleaning of small-to-medium creative/render datasets (up to 200 rows) where you want three reports for the price of one without any external data lookups or ML-based predictions.
Side effects
- Input array exceeds 200 rows — request will be rejected
- Missing required fields (row_id, asset_group, date, light_count, render_seconds) on any row
- Date field not matching YYYY-MM-DD pattern — validation error
- row_id empty or blank — minLength constraint failure
- Numeric fields outside allowed range (±1,000,000,000,000) — schema rejection
- Payment of 0.01 USDC not fulfilled — 402 response before processing
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array |
Tags
x402
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