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Evaluation Run Imports — Numeric Type Check
x402
Evaluation Run Imports — Numeric Type 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 all numeric columns in an evaluation run CSV conform to expected numeric types, ranges, and category constraints, returning a type-check report.
Price / call$0.01
Success—
StatusUnknown
How this service works
Evaluation run imports — Numeric type check: Numeric type 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 numeric type check report.
Output
A numeric type check report covering up to 1000 rows of the submitted CSV, identifying which cells or columns fail numeric type expectations, fall outside the specified min/max range, exceed cell length limits, or contain disallowed category values. The report is scoped to numeric column validation only and does not perform external data enrichment.
Example use cases
Pre-import ML evaluation data check
“Before I import this evaluation run CSV into our pipeline, can you validate that all numeric columns like correct_count and example_count are actually numbers, are between 0 and 10000, and that dataset_id only contains allowed values like group-a, group-b, or group-c?”
Catching bad data in evaluation export
“I exported evaluation results to a CSV and I need to make sure none of the numeric fields got corrupted — can you run a numeric type check on it using comma as the delimiter and flag anything outside the range -1000 to 1000000?”
Automated data quality gate for evaluation pipeline
“As part of our automated evaluation pipeline, check this CSV for numeric type violations before we proceed — the allowed category labels are experiment-1, experiment-2, and experiment-3, and numeric values should stay between 0 and 100.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-bx-csv-evaluations-types?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need to validate numeric column types and value ranges in an evaluation run CSV before import, particularly when your data follows the evaluation_id/evaluated_on/dataset_id/correct_count/example_count schema pattern. It is purpose-built for evaluation run import contracts, supports quoted cells, configurable delimiters, category allowlists, and min/max range bounds — making it ideal as a lightweight, low-cost data quality gate in ML evaluation pipelines.
Side effects
- CSV exceeds 100,000 character limit — request rejected
- More than 1000 rows submitted — only first 1000 may be evaluated
- Invalid delimiter specified — must be comma, semicolon, or tab
- Minimum value exceeds maximum value — configuration error
- Cell length exceeds max_cell_length limit — cell flagged or rejected
- Malformed CSV structure — unparseable rows cause partial or failed report
- Empty CSV submitted — validation cannot proceed
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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