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CSV Calendar Date Validation for Training Data
x402
CSV Calendar Date Validation for Training Data 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 date columns in a CSV dataset (up to 1000 rows) against configurable min/max bounds and allowed category values, returning a calendar date check report.
Price / call$0.01
Success—
StatusUnknown
How this service works
Training example metadata — Calendar date check: Calendar date 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 calendar date check report.
Output
A calendar date check report indicating which rows or cells contain dates outside the specified min/max bounds, malformed date values, or category values not in the allowed list. The report covers up to 1000 rows of the submitted CSV.
Example use cases
Pre-training data quality gate
“Before I train my model, can you validate the date fields in this CSV to make sure every date is between 2023-01-01 and 2025-12-31 and all label values are either group-a or group-b? The file uses commas as delimiters.”
Detecting out-of-range dates in exports
“I just exported a dataset from our pipeline and I need to check that the created_on column only has dates from 2025-01-01 to 2025-12-31 — can you run a calendar date validation on this CSV and flag any rows that fall outside that window?”
Category and date audit for annotated dataset
“We have an annotated CSV with a date column and a label column — can you verify that all dates are within 2024-06-01 and 2024-09-30, and that the only allowed categories are alpha, beta, and gamma? Delimiter is a semicolon.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-bx-csv-training-data-dates?utm_source=zero.xyzWhen to prefer
Use this endpoint when you need a lightweight, pay-per-call date column validation on a CSV dataset without setting up your own data pipeline. It is ideal for ML training data quality checks where you need to confirm date fields fall within a known range and categorical labels match a whitelist, all without sending data to an external enrichment service. Prefer it over general-purpose CSV validators when calendar date semantics and category allow-listing are the primary concern.
Side effects
- CSV exceeds 1000 rows — only the first 1000 may be processed
- CSV string exceeds 100,000 character limit — request rejected
- Invalid delimiter specified — only comma, semicolon, or tab are accepted
- Cell exceeds max_cell_length — flagged or truncated
- Malformed CSV with unmatched quotes — parse error returned
- Min/max bounds are equal or inverted — may yield unexpected results
- Empty CSV body — validation fails with input error
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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