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Thermal Measurements - Schema Directionality Analysis
x402
Thermal Measurements - Schema Directionality Analysis is a paid API for AI agents from www.mahastrategies.com, paid per call via x402, $0.035217/call, status unknown (last checked 2026-10-16).
Compares closed export-field supplied-record thermal measurements for schema directionality, validating before/after record arrays against a declared data class
Price / call$0.035217
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 schema directionality comparison result for the supplied before/after thermal record arrays, indicating whether closed export fields align directionally, any mismatches or anomalies in field structure, and conformance status relative to the declared data class and metadata constraints.
Example use cases
Validate thermal sensor data export fields
“I have a batch of thermal sensor readings from before and after a calibration event — can you check the schema directionality across the export fields to make sure nothing shifted? Before set has 8 records, after set has 4, data class is 'public', and we're working with nonpersonal metadata only.”
Audit synthetic thermal data record structure
“Run a directionality check on my synthetic thermal measurement records — I have 10 before-records and 6 after-records, data class should be 'synthetic', nonpersonal metadata only, and I want to allow extra fields on the consumer side.”
Detect field direction mismatches in thermal exports
“I need to compare my before and after thermal measurement exports to catch any closed export-field directionality issues — 15 before-records and 12 after-records, data class 'public', nonpersonal metadata flagged true.”
Technical details
Endpoint
POSThttps://www.mahastrategies.com/api/v1/compute/thermal-measurements/schema-directionality?utm_source=zero.xyzWhen to prefer
Use this endpoint when you need to validate the directional consistency of closed export fields across paired thermal measurement record sets, particularly when working with before/after snapshots of sensor data and need schema-level directionality assurance rather than full certification. Prefer this over generic diff tools when the data class (public or synthetic) and nonpersonal metadata constraints are key to the comparison.
Side effects
- before array empty or exceeds 32 items — validation error
- after array missing or exceeds 32 items — validation error
- nonpersonal metadata not set to true — rejected as required const
- invalid dataClass value outside 'public' or 'synthetic' enum — schema rejection
- malformed record entries in before/after arrays — parse error
- payment not included or insufficient — 402 response
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| after | array | |
| before | array | |
| dataClass | string | |
| nonpersonalMetadata | boolean | |
| consumerAllowsExtraFields | boolean |
Tags
x402
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