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Account Research Coverage — String Normalisation + Date by Category Pivot
x402
Account Research Coverage — String Normalisation + 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 2026-10-15).
Normalises string fields and produces a date-by-category pivot report for up to 200 account research coverage rows, delivering two analytical reports per call.
Price / call$0.01
Success—
StatusUnknown
How this service works
Account research coverage — String normalisation + Date by category pivot: String normalisation + Date by category pivot 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
Two analytical reports: (1) a string-normalised version of the input records with cleaned company_group and other text fields, and (2) a date-by-category pivot table showing the selected numeric field (researched_accounts or target_accounts) broken down by date and company_group — all computed locally with no external lookups.
Example use cases
Sales coverage gap pivot report
“I have a CSV of up to 150 account research coverage rows with company groups, dates, and counts of researched and target accounts — please normalise the company group strings and pivot the target_accounts field by date and category so I can see which groups have coverage gaps over time.”
Monthly research tracking by group
“Here are 200 rows of account research data spanning October 2026, each with a row_id, company_group, date, and both researched_accounts and target_accounts values — normalise the text fields and give me a date-by-category pivot on researched_accounts so I can track research progress by group each day.”
Data quality cleanup before board report
“Before I present to leadership, I need to clean up this account research dataset — 80 rows with messy company_group strings and date-stamped coverage counts — please run the string normalisation and produce a date pivot report using the researched_accounts field.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-company-08-035?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have up to 200 account research coverage records and need both string normalisation of categorical fields and a date-by-category pivot in a single low-cost call ($0.01 USDC). It is best suited for offline batch analytics on supplied data rather than live lookups or predictive modelling. Prefer it over general-purpose analytics tools when you need two bundled reports (normalisation + pivot) with a predictable flat price and no external data access.
Side effects
- Input array exceeds 200 rows — request rejected
- Missing required fields (row_id, company_group, date, researched_accounts, target_accounts) — validation error
- Date field does not match YYYY-MM-DD pattern — schema validation failure
- Numeric fields outside allowed range (±1 trillion) — rejected
- Empty rows array — minimum 1 item required
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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