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Library Loan Imports — Record Key Uniqueness Validator
x402
Library Loan Imports — Record Key Uniqueness Validator is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-12).
Validates that all record keys in a library loan CSV are unique, checking up to 1000 rows for duplicate primary key violations.
Price / call$0.01
Success—
StatusUnknown
How this service works
Library loan imports — Record key uniqueness: Record key uniqueness for Library loan imports. Validate a declared CSV table contract, up to 1000 rows. Quoted cells supported; no external enrichment. Specialised preset in a shared 50-profile, 20-operation engine. 0.01 USDC includes one CSV record key uniqueness report.
Output
A record key uniqueness report indicating whether all row keys in the CSV are distinct, identifying any duplicate keys found, their row positions, and a pass/fail summary for the declared loan import contract — covering up to 1000 rows.
Example use cases
Pre-import loan data quality check
“Before I upload this batch of library loans, can you check the CSV for any duplicate loan_id keys? Here's the file content with comma-separated columns — I need to make sure every record key is unique.”
Branch loan reconciliation validation
“I have a CSV of loan records from multiple branches (group-a and group-b) and I need to confirm there are no repeated record keys before merging the datasets. Can you run a key uniqueness check on it?”
Automated daily loan intake validation
“Every morning we receive a fresh loans import CSV — can you validate that all the loan record keys are unique in today's file so we catch any duplicates before they hit the database?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-bx-csv-loans-keys?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need to specifically validate record key uniqueness in library loan CSV imports, particularly when preparing data for a library management system ingestion pipeline. It is purpose-built for the loan domain (loan_id, branch_id, borrowed_on, loan_days, overdue_days schema) and handles quoted cells correctly. Prefer it over generic CSV validators when you need a domain-aware preset that understands library loan data structures and allowed branch category values.
Side effects
- CSV exceeds 100,000 character limit — request rejected
- More than 1000 rows submitted — only first 1000 processed or error returned
- Invalid delimiter specified — must be comma, semicolon, or tab
- Cell content exceeds max_cell_length limit — row may be rejected
- Malformed CSV (unclosed quotes, inconsistent columns) — parse error returned
- Empty CSV string submitted — validation cannot proceed
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| csv | string | |
| maximum | number | |
| minimum | number | |
| delimiter | string | |
| max_cell_length | integer | |
| allowed_categories | array |
Tags
x402
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