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Dataset Export Roundtrip Check
x402
Dataset Export Roundtrip Check is a paid API for AI agents from www.mahastrategies.com, paid per call via x402, $0.0219/call, status unknown (last checked 2026-10-15).
Compares before and after parsed dataset exports to detect cell type changes, field presence differences, and field order changes, without returning cell values.
Price / call$0.0219
Success—
StatusUnknown
How this service works
Compare parsed exports for cell types, field presence and order changes. No automatic correction; cell values are not returned.
Output
A structured report indicating whether cell types changed between the before and after exports, which fields are present or absent in each version, and whether field order differs. No actual cell values are returned.
Example use cases
ETL pipeline column drift detection
“I just ran my ETL pipeline and I want to make sure the exported dataset hasn't dropped any fields or changed column types. Here are the before and after export arrays — data class is public. Can you check for any structural differences?”
Synthetic data export schema audit
“We generated a synthetic dataset and then exported it through our serialization layer. Can you compare these before and after arrays to see if any field order or type changes crept in? Data class is synthetic.”
Pre-release dataset export regression check
“Before we ship this release, can you do a roundtrip export check on our dataset? I have the original export as the before array and the post-processing version as the after array — data class is public — and I need to know if anything structural changed.”
Technical details
Endpoint
POSThttps://www.mahastrategies.com/api/v1/verify/datasets/export-roundtrip?utm_source=zero.xyzWhen to prefer
Use this endpoint when you need a privacy-safe structural audit of dataset exports — specifically to catch field type regressions, missing fields, or reordered columns — without exposing raw cell values. Prefer it over full data-diff tools when cell-level content is sensitive or irrelevant and only schema-level changes matter. Best suited for synthetic or public data classes.
Side effects
- Array exceeds 500 item limit — request rejected
- Invalid dataClass value (not 'synthetic' or 'public') — validation error
- Malformed array items that cannot be parsed — parsing error returned
- Empty before or after array — may return trivial or incomplete comparison
- Network timeout for large array payloads
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| after | array | |
| before | array | |
| dataClass | string |
Tags
x402
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