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Machine Utilisation Imports — Header Contract Check
x402
Machine Utilisation Imports — Header Contract 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 the CSV header contract for machine utilisation import files, checking column names, types, and categorical constraints against a declared schema for up to 1000 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Machine utilisation imports — Header contract check: Header contract 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 header contract check report.
Output
Returns a header contract check report indicating whether the CSV conforms to the declared schema: column presence, order, naming, allowed category values, numeric range compliance, cell length limits, and any violations found across up to 1000 rows.
Example use cases
Pre-import CSV header validation
“Before I import this machine utilisation file, can you validate its CSV headers against the expected contract? The file uses comma delimiters and machine_id should only be 'line-1', 'line-2', or 'line-3'.”
Catch bad category values in shift data
“I've got a machine utilisation CSV with running_hours and scheduled_hours columns — please check the header contract and flag any machine_id values that aren't in my allowed list: 'press-a', 'press-b', 'press-c'.”
Validate OEE data before pipeline ingestion
“Run a header contract check on this machine utilisation CSV — columns are observation_id, observed_on, machine_id, running_hours, scheduled_hours — and make sure all numeric values stay between 0 and 24 hours.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-bx-csv-machines-schema?utm_source=zero.xyzWhen to prefer
Use this endpoint when you need a lightweight, schema-aware pre-import validation of machine utilisation CSV files specifically, without triggering any data storage or enrichment. It is ideal for CI/CD data pipelines, ETL pre-checks, and agent-driven data ingestion workflows where you want to catch header and category contract violations before committing data downstream. Prefer this over generic CSV validators when you need domain-specific column expectations for machine utilisation data (observation_id, machine_id, running_hours, scheduled_hours).
Side effects
- CSV exceeds 1000 rows — only first 1000 are validated
- Delimiter mismatch causes all columns to be read as one
- Allowed categories list empty — no category validation performed
- CSV exceeds 100,000 character limit — request rejected
- Cell length exceeds max_cell_length — flagged as violation
- Missing required columns — contract check fails with column not found error
- Malformed quoted cells may cause parse errors
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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