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CSV Training Data Whitespace Audit
x402
CSV Training Data Whitespace Audit 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 CSV file's whitespace formatting and declared table contract, checking up to 1000 rows for whitespace issues in cells, headers, and values.
Price / call$0.01
Success—
StatusUnknown
How this service works
Training example metadata — Whitespace audit: Whitespace audit 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 whitespace audit report.
Output
Returns a whitespace audit report for the submitted CSV, identifying cells, rows, or headers with leading/trailing whitespace, unexpected spacing, or values that violate the declared contract (allowed categories, numeric bounds, or max cell length), covering up to 1000 rows.
Example use cases
ML training data pre-flight check
“Before I kick off my model training run, can you audit this CSV for whitespace problems? It has comma-separated columns and the only valid labels are 'cat' and 'dog' — flag anything that looks off in terms of extra spaces or bad cell lengths.”
Data pipeline quality gate
“I need to validate this semicolon-delimited training dataset CSV for whitespace issues before it goes into our pipeline — max cell length should be 500, and the allowed category values are 'positive', 'negative', and 'neutral'.”
Checking imported CSV from external source
“We just got a CSV export from a third-party vendor for our training data — can you run a whitespace audit on it with a tab delimiter and make sure none of the cells exceed 200 characters? Allowed categories are just 'A' and 'B'.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-bx-csv-training-data-whitespace?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need a fast, low-cost whitespace-specific audit of a CSV training dataset (up to 1000 rows) before ingesting it into a machine learning pipeline. It is purpose-built for training data quality checks including category validation, numeric bounds, and cell length limits, and supports quoted cells — making it more appropriate than a generic CSV linter when the focus is on whitespace hygiene and declared schema contracts for ML data.
Side effects
- CSV exceeds 100,000 character limit — request rejected
- CSV has fewer than 1 character — rejected as empty
- Delimiter not one of comma, semicolon, or tab — validation error
- max_cell_length outside 1–5000 range — parameter error
- allowed_categories list exceeds 100 items — parameter error
- Malformed CSV that cannot be parsed — error response
- Payment of 0.01 USDC not provided — 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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