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Render Jobs — Record Quality Audit + String Normalisation + Keyed Dataset Comparison
x402
Render Jobs — Record Quality Audit + 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).
Runs three local analytical reports on render job records: a record quality audit, string normalisation, and a keyed comparison between two datasets, covering up to 200 rows of render_seconds and sample_count data.
Price / call$0.01
Success—
StatusUnknown
How this service works
Render jobs — Record quality audit + String normalisation + Keyed dataset comparison: Record quality audit + String normalisation + Keyed dataset comparison for supplied render jobs records (render_seconds, sample_count). 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 reports: (1) a record quality audit highlighting missing values, out-of-range figures, and data integrity issues across render_seconds and sample_count; (2) a string normalisation report for asset_group and other text fields; and (3) a keyed dataset comparison report showing row-level differences between the two supplied datasets — all computed locally with no external lookups.
Example use cases
Pre-pipeline render data validation
“Before we ingest this week's render job export into the pipeline, can you run a quality audit on these 150 rows — checking render_seconds and sample_count for issues — and also normalise the asset_group labels for me?”
Comparing current vs previous render export
“I have two versions of our render job records — this week's and last week's — each about 120 rows with render_seconds and sample_count. Can you do a keyed comparison to find what changed between them, plus flag any quality problems in the current set?”
Asset group string clean-up for reporting
“Our render job data has inconsistent asset_group naming across these 80 rows. Can you normalise those strings and give me a quality audit report on the render_seconds and sample_count values at the same time?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-creative-02-207?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need three bundled analytical passes — quality audit, string normalisation, and keyed cross-dataset comparison — on render job records in a single $0.01 call. Prefer it over single-report endpoints when your workflow requires all three analyses together, and when your dataset is within 200 rows. It is entirely offline and deterministic, so it is appropriate when no live data lookup, prediction, or external enrichment is needed.
Side effects
- Exceeding 200 rows in either dataset returns a validation error
- Missing required fields (row_id, date, render_seconds, sample_count, asset_group) causes row rejection
- Malformed date strings not matching YYYY-MM-DD pattern are rejected
- Numeric values outside the permitted range trigger schema validation failures
- Empty rows array returns an error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| other | array |
Tags
x402
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