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Publication Records Declared Bound Audit
x402
Publication Records Declared Bound Audit is a paid API for AI agents from www.mahastrategies.com, paid per call via x402, $0.010162/call, status unknown (last checked 2026-10-16).
Audits declared nonnegative integer aggregate counts in publication records against caller-supplied inclusive bounds, verifying consistency across source, subject, snapshot, and unit dimensions.
Price / call$0.010162
Success—
StatusUnknown
How this service works
Compare exact nonnegative integer aggregate counts with one inclusive caller-supplied bound matching every source, subject, snapshot and unit Supplied-record analysis, not independent certification. Full contract at the free describe URL.
Output
Returns an audit result indicating whether each declared nonnegative integer aggregate count in the publication records satisfies the caller-supplied inclusive bounds, with per-record pass/fail status covering all source, subject, snapshot, and unit dimensions. This is a supplied-record analysis, not independent certification.
Example use cases
Research citation count compliance check
“I have 15 publication records with declared citation counts and I want to verify each one is within the inclusive bounds I specify — can you audit these public data measurements and tell me which ones pass and which ones fail?”
Synthetic dataset aggregate bound validation
“Run a bound audit on my synthetic publication dataset — I have 10 measurements with nonnegative integer counts and I need to confirm they all fall within the caller-supplied inclusive bounds across every source, subject, snapshot, and unit combination.”
Multi-snapshot publication metrics consistency check
“Check whether the aggregate counts in these 25 declared publication snapshots are consistent with the inclusive bounds I'm providing — data class is public, and flag any count that exceeds or mismatches the declared limit.”
Technical details
Endpoint
POSThttps://www.mahastrategies.com/api/v1/intel/publication-records/declared-bound-audit?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need to audit declared integer aggregate counts in publication records against caller-specified inclusive bounds across multiple dimensions (source, subject, snapshot, unit), particularly for up to 32 measurements at a time. It is best suited for compliance checks on supplied data — not for independent certification or external verification of publication claims.
Side effects
- Bounds array exceeds 32 items — request rejected
- Measurements array is empty or exceeds 32 items — validation error
- nonpersonalMetadata is not set to true — request rejected
- dataClass is not 'public' or 'synthetic' — enum validation error
- Mismatched array lengths between bounds and measurements — error response
- Negative integer values provided — violates nonnegative constraint
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| bounds | array | |
| dataClass | string | |
| measurements | array | |
| nonpersonalMetadata | boolean |
Tags
x402
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