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Planetary Measurements - Required Field Coverage Check
x402
Planetary Measurements - Required Field Coverage Check is a paid API for AI agents from www.mahastrategies.com, paid per call via x402, $0.010159/call, status unknown (last checked 2026-10-25).
Validates that all specified required fields are present (non-null) in a batch of planetary scientific dataset rows, flagging missing fields without performing credential or artifact validation.
Price / call$0.010159
Success—
StatusUnknown
How this service works
Check presence of required scientific dataset/method/revision/content pins; null is missing, not an invalid credential or artifact for target/site/convention/time/method-pinned planetary Supplied-record analysis, not independent certification. Full contract at the free describe URL.
Output
Returns a per-row coverage report indicating which required fields are present and which are null/missing for each submitted planetary measurement row, without performing any credential validation or independent certification.
Example use cases
Pre-analysis pipeline data completeness check
“I have 20 rows of public planetary measurement data and I need to make sure the fields 'semi_major_axis', 'eccentricity', and 'inclination' are all non-null before I run my orbital analysis — can you check them?”
Synthetic dataset field validation for research
“We generated a synthetic batch of 15 planetary records and need to confirm that 'albedo', 'mass', 'diameter', and 'rotation_period' are all present in every row — flag any that are missing fields.”
Quality gate for ingestion of scientific records
“Before I ingest these 30 planetary measurement rows into our database, check that 'planet_name', 'discovery_method', 'host_star', and 'orbital_period' are all populated — this is public data with nonpersonal metadata only.”
Technical details
Endpoint
POSThttps://www.mahastrategies.com/api/v1/celestial/planetary-measurements/required-field-coverage?utm_source=zero.xyzWhen to prefer
Use this endpoint when you need a fast, lightweight check that specific fields exist and are non-null in planetary measurement records, without needing full schema validation, credential verification, or external data fetching. Prefer it over general-purpose validators when working specifically with planetary or celestial scientific dataset rows in public or synthetic data classes.
Side effects
- Rows array is empty or exceeds 32 items — request rejected
- requiredFields array exceeds 8 items or is empty — validation error
- dataClass value not in ['public','synthetic'] enum — invalid input
- nonpersonalMetadata not set to true (const) — request rejected
- Malformed row objects — field presence cannot be determined
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| dataClass | string | |
| requiredFields | array | |
| nonpersonalMetadata | boolean |
Tags
x402
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