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Company Record Completeness — Base-100 Series + IQR Outlier Flags
x402
Company Record Completeness — Base-100 Series + 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 2026-10-19).
Analyzes supplied company record completeness data (populated_fields, required_fields) to produce Base-100 indexed time series and IQR-based outlier flags across up to 200 rows, delivering two independent analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Company record completeness — Base-100 series + IQR outlier flags: Base-100 series + IQR outlier flags for supplied company record completeness records (populated_fields, required_fields). 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
Returns two analytical reports: (1) a Base-100 indexed time series for the selected field (populated_fields or required_fields) relative to the specified base row, and (2) IQR-based outlier flags identifying statistically anomalous rows across the supplied dataset of up to 200 company completeness records.
Example use cases
Data quality audit across company groups
“I have completeness records for three company groups over the past quarter — each row has a date, group name, how many fields are populated, and how many are required. Can you index the populated_fields values to a base of 100 starting from the first row and flag any IQR outliers?”
Spotting anomalous required fields counts
“Analyze my company record data for outliers in required_fields — I'll give you up to 150 rows with company_group, date, populated_fields, and required_fields, and I want to know which rows are statistically anomalous using IQR rules.”
Benchmarking completeness trends over time
“I want to benchmark my CRM completeness over time — take these 80 rows of company records with populated_fields and required_fields and give me a Base-100 series starting from row index 0 plus any IQR outlier flags for the populated_fields column.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-company-01-164?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need offline statistical analysis of company record completeness data using both time-series normalization (Base-100 indexing) and IQR-based outlier detection in a single low-cost call. It is ideal when you already have the data locally and need two analytical views simultaneously without any live lookup or external enrichment. Prefer it over general-purpose analytics tools when the data volume is ≤200 rows, the domain is specifically company record field population quality, and cost efficiency ($0.01 USDC for two reports) is a priority.
Side effects
- More than 200 rows submitted — request rejected due to maxItems constraint
- Missing required fields (row_id, company_group, date, populated_fields, required_fields) cause validation errors
- Invalid date format (not YYYY-MM-DD) triggers pattern validation failure
- base_index out of range (0–199) causes parameter rejection
- All-null numeric values may produce degenerate IQR results with no meaningful outlier detection
- Insufficient row variance may result in no outliers flagged
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| base_index | integer |
Tags
x402
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