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Neural Interface Records - Schema Directionality Comparator
x402
Neural Interface Records - Schema Directionality Comparator is a paid API for AI agents from www.mahastrategies.com, paid per call via x402, $0.035229/call, status unknown (last checked 2026-10-16).
Compares closed export-field schema directionality for supplied neural interface records, flagging structural differences between before and after record sets.
Price / call$0.035229
Success—
StatusUnknown
How this service works
Compare closed export-field Supplied-record analysis, not independent certification. Full contract at the free describe URL.
Output
Returns a comparison of schema directionality between the before and after record arrays, indicating whether export fields maintain consistent direction, any structural divergences detected, and whether the supplied records conform to the closed export-field specification. This is a supplied-record analysis, not an independent certification.
Example use cases
Detect schema drift after record update
“I updated our neural interface records and need to know if the export-field directionality changed — can you compare the before and after record sets using synthetic data class and flag any structural differences?”
Validate closed export fields for public records
“Check whether the export-field schema directions are consistent between these two snapshots of our public neural interface records, with nonpersonal metadata only and no extra fields allowed.”
Pre-release schema consistency check
“Before we ship this neural interface record schema update, compare the old and new record sets for directionality differences — use the synthetic data class and allow extra fields on the consumer side.”
Technical details
Endpoint
POSThttps://www.mahastrategies.com/api/v1/compute/neural-interface-records/schema-directionality?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need to compare closed export-field schema directionality between two snapshots of neural interface records, particularly when validating structural consistency of before/after record states with either public or synthetic data classes. Prefer this over generic schema diff tools when the records are neural interface records and you need export-field-specific directionality analysis rather than raw field-level diffing.
Side effects
- before array must have at least 1 item — empty before arrays are rejected
- after array exceeds 32-item limit — request fails with validation error
- dataClass must be exactly 'public' or 'synthetic' — other values are rejected
- nonpersonalMetadata must be exactly true (const) — false or missing causes failure
- Schema mismatch or malformed record structure may return analysis error
- Network or provider downtime returns 5xx error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| after | array | |
| before | array | |
| dataClass | string | |
| nonpersonalMetadata | boolean | |
| consumerAllowsExtraFields | boolean |
Tags
x402
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