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Account Research Coverage — String Normalisation + Keyed Dataset Comparison
x402
Account Research Coverage — String Normalisation + Keyed Dataset Comparison 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).
Normalises strings and compares two supplied account research coverage datasets (researched_accounts vs target_accounts) across up to 200 rows, producing 2 independent analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Account research coverage — String normalisation + Keyed dataset comparison: String normalisation + Keyed dataset comparison for supplied account research coverage records (researched_accounts, target_accounts). 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 2 independent analytical reports: (1) a string normalisation report cleaning company_group and other text fields across both supplied datasets, and (2) a keyed dataset comparison report identifying matches, mismatches, and gaps between the rows and other datasets on researched_accounts and target_accounts, keyed by row_id, company_group, and date. No live data, predictions, or external lookups are included.
Example use cases
Coverage gap audit by company group
“I have two snapshots of our account research coverage for October 2026 — the first is what we actually researched per group, the second is our target list. Can you normalise the company group names and run a keyed comparison to show me where we're falling short of targets for groups like group-a and group-b?”
Sales team benchmark reconciliation
“Our sales ops team has two versions of the researched_accounts vs target_accounts data for the same date range — one from the CRM export and one from the planning sheet. Can you normalise the strings and compare them row by row to find any discrepancies?”
Weekly account research coverage check
“Here are this week's account research coverage records for our two company groups with dates from 2026-10-01 to 2026-10-04, plus last week's targets. Run the string normalisation and keyed dataset comparison so I can see which rows have coverage mismatches between what was researched and what was targeted.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-company-08-036?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have two structured account research coverage datasets (up to 200 rows each) and need both string normalisation of company group labels and a keyed row-by-row comparison of researched_accounts vs target_accounts — all computed locally without any live lookup, external data enrichment, or prediction. Ideal for data quality checks, coverage gap audits, or reconciling CRM exports against planning targets when you need deterministic, offline analytical output at minimal cost.
Side effects
- More than 200 rows submitted — request rejected or truncated
- Missing required fields (row_id, company_group, date, researched_accounts, target_accounts) — validation error
- Date field not in YYYY-MM-DD format — pattern validation failure
- Numeric values outside allowed range (-1,000,000,000,000 to 1,000,000,000,000) — schema rejection
- Empty rows array — minItems:1 violation
- Payment not completed or insufficient USDC — 402 response blocking access
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| other | array |
Tags
x402
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