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Training Example Metadata — Required Cell Check
x402
Training Example Metadata — 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 2026-10-24).
Validates that required cells in a CSV training dataset are non-empty and conform to declared constraints, returning a required-cell check report.
Price / call$0.01
Success—
StatusUnknown
How this service works
Training example metadata — Required cell check: Required cell 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 required cell check report.
Output
A required-cell check report for up to 1000 rows of the submitted CSV, indicating which rows and columns have missing or invalid required cells, along with any constraint violations (out-of-range values, disallowed categories, or oversized cells).
Example use cases
ML dataset pre-training integrity check
“Before I kick off training, can you validate this CSV training dataset to make sure none of the required cells are empty and all category labels are from the allowed list ['class-0','class-1','class-2']? Use a comma delimiter and flag anything that looks wrong.”
Data pipeline quality gate for CSV exports
“I just got a new batch of labeled training examples as a CSV — can you run a required cell check on it with semicolon delimiter to confirm there are no blanks in mandatory columns and that numeric weights stay between 0 and 100?”
Training data audit before annotation review
“I need to audit this training example CSV before handing it back to the annotation team. Please check that all required cells are filled in, category values are only 'positive', 'negative', or 'neutral', and no cell is longer than 200 characters.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-bx-csv-training-data-required?utm_source=zero.xyzWhen to prefer
Use this endpoint when you need a fast, offline (no external enrichment) validation of required cell presence and constraint compliance in a CSV training dataset of up to 1000 rows. Prefer this over generic CSV validators when working with machine learning training data that has declared column contracts including category allowlists and numeric ranges. It is cost-effective at $0.01 USDC per call for lightweight data quality gates in ML pipelines.
Side effects
- CSV exceeds 100,000 character limit — request rejected
- CSV contains more than 1000 rows — only first 1000 may be processed
- Invalid delimiter specified — must be comma, semicolon, or tab
- Malformed CSV that cannot be parsed — parsing error returned
- allowed_categories list exceeds 100 items — request rejected
- min/max values outside allowed bounds (-1e12 to 1e12) — validation 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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