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Bibliographies - Declared-Bound Audit
x402
Bibliographies - Declared-Bound Audit is a paid API for AI agents from www.mahastrategies.com, paid per call via x402, $0.010176/call, status unknown (last checked 2026-10-20).
Compares exact nonnegative integer aggregate counts in bibliography records against one inclusive caller-supplied upper bound, validating that counts match across source, subject, snapshot, and unit dimensions.
Price / call$0.010176
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 a comparison result indicating whether each measurement falls within its corresponding inclusive declared bound, with per-dimension compliance status across source, subject, snapshot, and unit. This is supplied-record analysis, not independent certification.
Example use cases
Library collection count compliance check
“I have bibliography measurements [120, 85, 33] for public data with nonpersonalMetadata true — can you audit them against declared bounds [150, 100, 40] and tell me which, if any, exceed their inclusive bound?”
Synthetic dataset aggregate bound audit
“Run a declared-bound audit on these synthetic bibliography counts — measurements [5, 12, 30, 8] against bounds [5, 15, 30, 10] — with nonpersonalMetadata set to true, and confirm every measurement is within its bound.”
Snapshot count integrity validation
“Validate that my bibliography record counts [200, 75] don't exceed their declared bounds [200, 80] — data is public, nonpersonalMetadata is true — and flag any violations across source, subject, snapshot, and unit dimensions.”
Technical details
Endpoint
POSThttps://www.mahastrategies.com/api/v1/library/bibliographies/declared-bound-audit?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need to audit whether bibliography record aggregate counts comply with a single inclusive integer upper bound per measurement, across source, subject, snapshot, and unit dimensions, for either public or synthetic data. It is a lightweight supplied-record check, not independent certification, and is best used when you already have count measurements and want to verify they stay within declared limits.
Side effects
- Mismatched array lengths between bounds and measurements returns a validation error
- measurements or bounds containing negative integers are rejected (nonnegative integers only)
- Arrays exceeding 32 items are rejected
- Missing required nonpersonalMetadata:true field causes request failure
- Invalid dataClass value outside 'public' or 'synthetic' enum returns an error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| bounds | array | |
| dataClass | string | |
| measurements | array | |
| nonpersonalMetadata | boolean |
Tags
x402
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