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Compositing Graphs — Category Frequencies + IQR Outlier Flags
x402
Compositing Graphs — Category Frequencies + IQR Outlier Flags 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).
Analyzes compositing graph records to produce category frequency distributions and IQR-based outlier flags for node_count or render_seconds fields, across up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Compositing graphs — Category frequencies + IQR outlier flags: Category frequencies + IQR outlier flags for supplied compositing graphs records (node_count, render_seconds). 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 statistical reports: (1) a category frequency distribution showing how often each asset_group value appears in the supplied rows, and (2) IQR-based outlier flags for the selected numeric field (node_count or render_seconds), identifying which rows fall outside the interquartile range threshold. Results are computed locally on the supplied data with no external lookups.
Example use cases
Detecting render time anomalies in pipeline
“I have 80 compositing graph records from our rendering pipeline — can you run IQR outlier detection on the render_seconds field and also tell me how often each asset_group appears? I want to know which jobs are statistical outliers.”
Auditing node count spikes by asset group
“Here are 150 rows of compositing graph data with node counts and asset groups. Can you compute the category frequencies for asset_group and flag any IQR outliers in node_count so I can see which scenes are abnormally complex?”
QA check on weekly compositing batch
“We just ran a weekly compositing batch and I have the results as a table of rows with row_id, asset_group, date, node_count, and render_seconds. Please give me the category frequency breakdown and IQR outlier flags for render_seconds so we can QA the output.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-creative-09-107?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have compositing graph records (with asset_group, node_count, and render_seconds fields) and need both a categorical frequency summary and IQR-based outlier detection in a single low-cost call. Ideal for pipeline QA, batch job auditing, or anomaly detection on rendering data without requiring an external analytics platform.
Side effects
- Empty or missing rows array returns an error
- More than 200 rows causes rejection due to maxItems limit
- Invalid date format (not YYYY-MM-DD) triggers schema validation failure
- Missing required fields (row_id, asset_group, date, node_count, render_seconds) causes row rejection
- Invalid field enum value (not node_count or render_seconds) returns error
- Numeric values outside ±1 trillion range are rejected
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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