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Proposal Preparation IQR Outlier Flags and Date by Category Pivot
x402
Proposal Preparation IQR Outlier Flags and 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 2026-10-26).
Runs IQR-based outlier detection and a date-by-category pivot analysis on up to 200 proposal preparation records (completed_sections, planned_sections) and returns two independent analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Proposal preparation — IQR outlier flags + Date by category pivot: IQR outlier flags + Date by category pivot for supplied proposal preparation records (completed_sections, planned_sections). 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 independent reports: (1) an IQR outlier flag report identifying which rows have anomalous values in the selected field (completed_sections or planned_sections) based on interquartile range analysis, and (2) a date-by-category pivot table aggregating section counts by date and document_group.
Example use cases
Flagging anomalous proposal section counts
“I have a batch of proposal records with completed_sections and planned_sections — can you run IQR outlier detection on completed_sections and also pivot the data by date and document_group? Here are up to 150 rows with row_id, date, document_group, and both section counts.”
Monitoring proposal progress by team over time
“I want to see how proposal sections are trending across our document groups over the past quarter. Can you take these proposal records and give me a date-by-category breakdown of planned_sections, plus flag any outlier rows?”
Pre-submission audit of proposal data quality
“Before we submit our proposals, I need a statistical audit — run IQR outlier flags on the completed_sections field for these 80 proposal records, and also generate a pivot of section counts by date and document group so I can spot any gaps.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-writing-08-178?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have structured proposal preparation records with section count metrics and need both statistical outlier detection (IQR-based) and a temporal category pivot in a single call. It is ideal for batch audits of up to 200 rows where you want two complementary analytical views without building custom analytics code. Not suitable for real-time lookups, predictions, or proposals needing external data enrichment.
Side effects
- Fewer than 1 row submitted returns a validation error
- More than 200 rows submitted exceeds the maximum and is rejected
- Invalid date format (not YYYY-MM-DD) causes schema validation failure
- Null values in both numeric fields may reduce outlier detection accuracy
- Invalid enum value for 'field' parameter causes rejection
- Insufficient data variance may produce trivial or empty outlier flags
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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