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Sky Observations Unit-Label Consistency Checker
x402
Sky Observations Unit-Label Consistency Checker is a paid API for AI agents from www.mahastrategies.com, paid per call via x402, $0.012327/call, status unknown (last checked 2026-10-20).
Audits quantity and unit labels within a supplied set of sky observation measurements for consistency, including coordinate, clock, model, and calibration labels.
Price / call$0.012327
Success—
StatusUnknown
How this service works
Audit quantity/unit labels in the exact supplied frame, including coordinate/clock or model/calibration Supplied-record analysis, not independent certification. Full contract at the free describe URL.
Output
Returns an audit report identifying unit-label inconsistencies found within the supplied observation measurements, including flagged fields related to coordinates, clock, model, and calibration labels. Does not provide independent certification — analysis is based solely on the supplied record frame.
Example use cases
Telescope pipeline unit validation
“I have 20 synthetic sky observation records from my telescope pipeline and I need to check whether all the quantity and unit labels are consistent — especially coordinate and clock fields. Can you run a unit-label consistency audit on them?”
Calibration data label audit
“Before I submit this batch of public sky observations to our calibration pipeline, can you audit the model and calibration unit labels across all 15 records to make sure nothing is mislabeled or inconsistent?”
Observatory data QA before archiving
“We have 32 sky measurement records marked as synthetic that we're about to archive — can you check them for any unit-label inconsistencies in the coordinate, clock, or measurement fields so we can fix issues before storage?”
Technical details
Endpoint
POSThttps://www.mahastrategies.com/api/v1/celestial/sky-observations/unit-label-consistency?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need to audit unit and quantity label consistency within a bounded set of sky observation records (up to 32), particularly when records include coordinate, clock, model, or calibration labels. It is not a substitute for independent scientific certification but is well-suited for pre-submission QA, pipeline validation, or data hygiene checks on synthetic or public celestial datasets.
Side effects
- Measurements array is empty or exceeds 32 items — returns validation error
- dataClass not set to 'public' or 'synthetic' — request rejected
- nonpersonalMetadata not set to true — request rejected
- Malformed measurement objects — may produce incomplete audit results
- Network timeout for large measurement batches near the 32-item limit
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| dataClass | string | |
| measurements | array | |
| nonpersonalMetadata | boolean |
Tags
x402
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