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Machine Utilisation Imports — Required Cell Check
x402
Machine Utilisation Imports — Required Cell Check 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 required cells are present and non-empty in a machine utilisation CSV dataset, up to 1000 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Machine utilisation imports — Required cell check: Required cell check 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 required cell check report.
Output
A required cell check report indicating which rows and columns have missing or empty required values in the machine utilisation CSV, along with a summary of validation findings.
Example use cases
Pre-import data completeness check
“Before I import this machine utilisation file into our system, can you validate it for missing required cells? The CSV uses commas as delimiters and has columns like observation_id, machine_id, running_hours, and scheduled_hours — I need to know if any mandatory fields are blank.”
Automated ETL pipeline validation
“As part of our nightly ETL pipeline, check this machine utilisation CSV for any missing required cells — it's comma-separated, up to 1000 rows, with allowed categories group-a and group-b, and flag anything that would break the import.”
Equipment hours audit before reporting
“We're about to generate our monthly equipment utilisation report — can you first check this CSV to make sure all required cells like running_hours and scheduled_hours are filled in? Use comma as the delimiter and let me know which rows are incomplete.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-bx-csv-machines-required?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need to verify that all required cells are populated in a machine utilisation CSV before importing or processing the data. It is specifically tailored for machine utilisation data schemas (observation_id, observed_on, machine_id, running_hours, scheduled_hours) and is ideal for pre-import validation pipelines, data quality gates, or ETL checks where missing mandatory fields would cause downstream failures.
Side effects
- CSV exceeds 1000 rows — only up to 1000 rows are supported
- CSV string exceeds 100,000 character limit — request rejected
- Invalid delimiter specified — must be comma, semicolon, or tab
- Cell content exceeds max_cell_length — validation error returned
- Malformed CSV (unmatched quotes or inconsistent columns) — parse error
- Category value not in allowed_categories list — flagged as invalid
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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