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Evaluation Run Imports — Required Cell Check
x402
Evaluation Run Imports — 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 2026-10-19).
Validates that required cells in a CSV table of evaluation run import records are populated, supporting up to 1000 rows and quoted cells.
Price / call$0.01
Success—
StatusUnknown
How this service works
Evaluation run imports — Required cell check: Required cell check for Evaluation run imports. 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 indicating which rows and columns have missing or empty required cells in the submitted CSV, covering up to 1000 rows with support for quoted cells and configurable delimiters.
Example use cases
Pre-import validation of ML evaluation data
“Before I upload this evaluation run CSV to our system, can you check that all required cells are filled in? The file uses comma delimiters and has columns evaluation_id, evaluated_on, dataset_id, correct_count, example_count — flag any rows with missing required values.”
Automated pipeline data quality gate
“We receive evaluation run import CSVs from partners and need to validate them before processing. Can you run a required cell check on this CSV using a comma delimiter, with allowed dataset categories group-a and group-b, and make sure no mandatory fields are blank?”
Debugging a failing evaluation import
“My evaluation import keeps failing and I think some required cells might be empty. Can you check this CSV — it uses semicolon delimiters and has evaluation records with fields evaluation_id, evaluated_on, dataset_id, correct_count, and example_count — and tell me which rows are missing required data?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-bx-csv-evaluations-required?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need to validate that all required fields are populated in a CSV containing evaluation run import records, especially when working with declared CSV table contracts up to 1000 rows. Ideal for pre-import quality gates, partner data validation pipelines, and debugging missing-field issues in ML evaluation datasets. Prefer this over generic CSV validators when your data specifically follows the evaluation run schema (evaluation_id, evaluated_on, dataset_id, correct_count, example_count).
Side effects
- CSV exceeds 1000 row limit — report may be truncated or rejected
- CSV string exceeds 100,000 character maximum — request rejected
- Invalid delimiter specified — must be comma, semicolon, or tab
- Cell content exceeds max_cell_length — cell flagged or truncated
- Malformed CSV (unbalanced quotes) — parsing error returned
- Allowed categories list exceeds 100 items — request rejected
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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