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Machine Utilisation Imports — Record Key Uniqueness Validator
x402
Machine Utilisation 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 2026-10-15).
Validates that all record keys in a machine utilisation CSV import are unique, checking up to 1000 rows for duplicate primary keys.
Price / call$0.01
Success—
StatusUnknown
How this service works
Machine utilisation imports — Record key uniqueness: Record key uniqueness for Machine utilisation 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
Returns a record key uniqueness report for the submitted machine utilisation CSV, identifying whether all primary/record keys are unique, flagging any duplicate keys found, and summarising the validation outcome across up to 1000 rows.
Example use cases
Pre-import data quality gate
“Before I push this machine utilisation CSV to our database, check that every observation_id is unique — I don't want any duplicate keys sneaking in. The file uses comma delimiters and the machine groups are group-a through group-d.”
Scheduled ETL pipeline validation
“I have a daily export of machine running hours as a CSV with semicolon delimiters. Validate that all the record keys are unique so our ETL pipeline doesn't fail on duplicate primary keys tonight.”
Auditing a third-party equipment data feed
“We received a CSV from our equipment vendor with columns observation_id, observed_on, machine_id, running_hours, scheduled_hours. Can you check whether any observation_id appears more than once in that file?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-bx-csv-machines-keys?utm_source=zero.xyzWhen to prefer
Use this endpoint when you specifically need to validate record key uniqueness in machine utilisation CSV imports, particularly when working with industrial equipment data (running hours, scheduled hours, machine IDs) and need a pre-import data quality check. It is purpose-built for this domain schema rather than being a generic CSV deduplication tool, making it more appropriate than generic validators when the data matches the machine utilisation schema.
Side effects
- CSV exceeds 1000 rows — only up to 1000 rows are validated
- Malformed CSV that cannot be parsed returns a parse error
- Delimiter mismatch between declared and actual CSV format causes incorrect parsing
- Cell content exceeding max_cell_length causes rejection
- Empty CSV input triggers a minimum-length validation error
- Category values not present in allowed_categories may be flagged
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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