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Render Jobs — Record Quality Audit + String Normalisation + Numeric Distribution
x402
Render Jobs — Record Quality Audit + String Normalisation + Numeric Distribution 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 bundled analytical reports on render job records: a record quality audit, string normalisation, and numeric distribution analysis for render_seconds or sample_count fields.
Price / call$0.01
Success—
StatusUnknown
How this service works
Render jobs — Record quality audit + String normalisation + Numeric distribution: Record quality audit + String normalisation + Numeric distribution 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 flagging completeness, validity, and consistency issues per row; (2) a string normalisation report for text fields like asset_group; and (3) a numeric distribution analysis (e.g. percentiles, range, frequency buckets) for the selected numeric field (render_seconds or sample_count). All reports are computed locally with no external lookups.
Example use cases
Render pipeline data quality check
“I have a batch of render job logs from last month — about 150 rows each with a row_id, asset_group, date, render_seconds, and sample_count. Can you audit them for record quality issues, normalise the string fields, and show me the numeric distribution for render_seconds?”
Sample count spread analysis for asset groups
“Here are 60 render job records across two asset groups with sample_count and render_seconds values. Run the full three-part report — quality audit, string normalisation, and numeric distribution — focused on sample_count so I can see how spread out the values are.”
Pre-delivery data validation for render studio
“Before I hand off this rendering dataset to the client, I want to make sure the data is clean. Can you do a record quality audit, normalise any inconsistent strings in the asset_group column, and give me a distribution breakdown of render_seconds for these 200 render job rows?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-creative-02-193?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need a bundled, cost-efficient three-in-one analysis of render job records — quality audit, string normalisation, and numeric distribution — all in a single call for up to 200 rows. Ideal for creative/media pipeline QA workflows where render_seconds and sample_count are the primary metrics, and no external data sources or live predictions are needed.
Side effects
- Exceeding 200 row limit returns a validation error
- Missing required fields (row_id, date, render_seconds, sample_count) causes schema rejection
- Invalid date format (not YYYY-MM-DD) triggers pattern validation failure
- Numeric values outside ±1,000,000,000,000 bounds are rejected
- Empty rows array returns a minItems validation error
- Unrecognised field enum value (not render_seconds or sample_count) causes rejection
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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