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Robotics Telemetry Required Field Coverage Checker
x402
Robotics Telemetry Required Field Coverage Checker is a paid API for AI agents from www.mahastrategies.com, paid per call via x402, $0.010147/call, status unknown (last checked 2026-10-16).
Checks whether required fields are present across robotics telemetry dataset rows, returning null for each missing required field rather than treating absence as an error
Price / call$0.010147
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 robot/frame/clock/calibration-pinned telemetry export Supplied-record analysis, not independent certification. Full contract at the free describe URL.
Output
Returns a per-row coverage report indicating the presence or absence (null) of each requested required field across the submitted telemetry rows, allowing callers to identify exactly which records are missing which mandatory fields without treating absence as an invalid credential or artifact error.
Example use cases
Pre-export telemetry field audit
“Before I export this batch of 20 robot telemetry records, can you check whether all four required fields — 'frame_id', 'clock_sync', 'sensor_revision', and 'calibration_ref' — are present in each row? The data class is synthetic.”
Robot calibration data completeness check
“I have 15 rows of public robotics calibration telemetry and I need to verify that 'robot_id', 'calibration_pin', and 'revision_tag' are all present — return null for any row where a required field is missing.”
Scientific dataset pin presence validation
“Can you scan these 8 rows of non-personal synthetic robot sensor data and confirm whether the required scientific pins — 'subject_id', 'scope_label', 'content_hash', and 'frame_clock' — exist in each record?”
Technical details
Endpoint
POSThttps://www.mahastrategies.com/api/v1/compute/robotics-telemetry/required-field-coverage?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need to audit robotics or scientific telemetry rows for required field presence before export or processing, and you want null-safe results (missing = null, not an error) rather than hard failures. Prefer it over general schema validators when working specifically with robot/frame/clock/calibration-pinned telemetry data that must remain non-personal and fits within the 32-row, 8-field constraints.
Side effects
- rows array empty or exceeds 32 item limit — validation error
- requiredFields array empty or exceeds 8 item limit — validation error
- dataClass not one of 'public' or 'synthetic' — enum validation failure
- nonpersonalMetadata not set to true (const constraint) — request rejected
- malformed row objects that cannot be parsed — may return partial or error results
- network timeout on large row batches near the 32-row limit
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| dataClass | string | |
| requiredFields | array | |
| nonpersonalMetadata | boolean |
Tags
x402
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