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Training Example Metadata — CSV Header Contract Check
x402
Training Example Metadata — CSV 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 2026-10-12).
Validates a declared CSV table contract (headers, types, categories, numeric ranges, cell lengths) for training example metadata, returning a structured report for up to 1000 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Training example metadata — Header contract check: Header contract check for Training example metadata. 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
A structured CSV header contract check report indicating whether the submitted CSV conforms to the declared contract, including any violations of category constraints, numeric range bounds, cell length limits, delimiter format, or header expectations — covering up to 1000 rows.
Example use cases
ML training data schema check
“I have a CSV of training examples with columns example_id, created_on, label, text_length, and sample_weight. Can you validate it against our declared contract — comma-separated, categories must be 'group-a' or 'group-b', max 1000 characters per cell? Here's the CSV content.”
Catch invalid category labels before pipeline run
“Before I push this training CSV into the ML pipeline, can you run a header contract check to make sure all the label values are within the allowed set 'group-a' and 'group-b', using a comma delimiter and max cell length of 500?”
Numeric range validation for sample weights
“Can you validate my training data CSV to confirm all numeric fields fall between 0 and 1000, categories are only 'group-a' or 'group-b', and no cell exceeds 200 characters? Use comma as the delimiter.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-bx-csv-training-data-schema?utm_source=zero.xyzWhen to prefer
Use this endpoint when you need to validate a training data CSV against a formally declared header contract — checking column headers, category allowlists, numeric ranges, and cell lengths in a single pass. Prefer it over generic CSV linters when working specifically with ML training example datasets that have structured label and weight columns, and when you need a machine-readable compliance report without external data enrichment.
Side effects
- CSV exceeds 100,000 character limit — request rejected
- CSV contains fewer than 1 character — minLength violation
- Delimiter not one of comma, semicolon, or tab — enum validation error
- Cell length exceeds specified max_cell_length — flagged in report
- Numeric values outside specified minimum/maximum bounds — constraint violation reported
- Allowed categories array contains more than 100 items — schema error
- Payment not included or insufficient — 402 Payment Required
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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