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Account Research Coverage — Record Quality Audit + Exact Row Deduplication + IQR Outlier Flags
x402
Account Research Coverage — Record Quality Audit + Exact Row Deduplication + 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 2026-10-15).
Runs three analytical reports on account research coverage data: a record quality audit, exact row deduplication, and IQR-based outlier detection on researched_accounts or target_accounts fields.
Price / call$0.01
Success—
StatusUnknown
How this service works
Account research coverage — Record quality audit + Exact row deduplication + IQR outlier flags: Record quality audit + Exact row deduplication + IQR outlier flags for supplied account research coverage records (researched_accounts, target_accounts). 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
Three independent analytical reports: (1) a record quality audit identifying missing, malformed, or invalid fields across the supplied rows; (2) an exact row deduplication report listing fully duplicate records; and (3) IQR outlier flags identifying rows where the selected numeric field (researched_accounts or target_accounts) falls outside the interquartile range bounds. All analysis is performed locally on supplied data with no external lookups.
Example use cases
Pre-analysis data quality check
“Before I run my quarterly analysis, can you audit this list of account research coverage records for quality issues, exact duplicate rows, and IQR outliers in the researched_accounts field? Here are my rows grouped by company_group with dates.”
Sales ops deduplication audit
“I think my CRM export has some duplicate entries — can you run exact row deduplication plus a record quality audit on these target_accounts coverage records across my company groups? I want to clean this up before reporting.”
Outlier flagging for target accounts
“Can you flag any statistical outliers in my target_accounts numbers using IQR detection, and also run a quality audit and deduplication pass on these 150 rows of account research data by company group and date?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-company-08-220?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need a combined data quality, deduplication, and outlier detection pass on account research coverage data in a single call. It is purpose-built for researched_accounts and target_accounts metrics grouped by company and date, making it ideal for CRM data hygiene, pre-analysis validation, or sales ops cleanup workflows. It does not perform live lookups, predictions, or external enrichment — prefer it when you want deterministic, local statistical analysis on your supplied dataset.
Side effects
- Fewer than 1 row submitted — rejected by schema minItems constraint
- More than 200 rows submitted — rejected by schema maxItems constraint
- Invalid date format (not YYYY-MM-DD) — row fails validation
- Missing required fields (row_id, company_group, date, researched_accounts, target_accounts) — row rejected
- Numeric values outside allowed range (±1,000,000,000,000) — schema validation error
- Invalid field enum value (not researched_accounts or target_accounts) — request rejected
- All rows are identical — deduplication report flags entire dataset
- Too few rows for meaningful IQR calculation — outlier report may be limited
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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