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Training Example Metadata — Blank Row Report
x402
Training Example Metadata — Blank Row Report 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 a CSV representing training example metadata and reports all blank (empty) rows found within it.
Price / call$0.01
Success—
StatusUnknown
How this service works
Training example metadata — Blank row report: Blank row report 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 blank row report report.
Output
A structured report identifying which rows in the submitted CSV are entirely blank, including row indices or counts of blank rows found, enabling the user to pinpoint data quality issues in their training dataset.
Example use cases
Pre-training dataset quality audit
“I have a CSV of training examples with columns example_id, created_on, label, text_length, and sample_weight — can you scan it for any completely blank rows before I feed it into my model? The delimiter is a comma and the allowed categories are group-a and group-b.”
Automated ML pipeline data validation
“As part of my ML pipeline, I need to validate this training metadata CSV and get a blank row report — the file uses tab-separated values, max cell length of 500, and I want to flag any row that's entirely empty before the next training run.”
Detecting data export gaps in labeled dataset
“My data export tool sometimes inserts blank lines into the CSV — can you run a blank row report on this training example metadata file using comma delimiter to find exactly which rows are empty so I can clean them up?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-bx-csv-training-data-empty-rows?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need a fast, focused blank-row detection report specifically for training example metadata CSVs, without needing external enrichment or complex schema inference. Ideal for ML data pipeline quality gates where you want a cheap ($0.01 USDC), deterministic check limited to 1,000 rows with support for quoted cells and configurable delimiters.
Side effects
- CSV exceeds 100,000 character limit — request rejected
- CSV contains more than 1,000 rows — validation limit exceeded
- Malformed CSV that cannot be parsed — parsing error returned
- Invalid delimiter specified — enum validation failure
- Cell content exceeds max_cell_length — validation error
- Empty CSV string submitted — minimum length violation
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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