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Maha Strategies Audit Export Normalizer
x402
Maha Strategies Audit Export Normalizer is a paid API for AI agents from www.mahastrategies.com, paid per call via x402, $0.018/call, status unknown (last checked 2026-09-14).
Normalizes up to 100 metadata events into a deterministic, deduplicated, and validated order, rejecting duplicate identifiers and malformed timestamps or digests.
Price / call$0.018
Success—
StatusUnknown
How this service works
Prepare an audit-event export for deterministic comparison. Normalize up to 100 metadata events and reject duplicate IDs, malformed times or digests. Does not prove events occurred or establish provenance or completeness against an external system.
Output
Returns a structured object containing the normalized and deduplicated event result, a deterministic input digest, a receipt digest, offer ID ('audit-export-normalizer'), version ('maha-microproducts/0.1'), amount in base units, and boundary markers. Does not verify event provenance or completeness against any external system.
Example use cases
Pre-export audit log cleanup
“Before I export this audit log, normalize these 80 metadata events tagged as 'synthetic' into deterministic order and reject any that have duplicate IDs or broken timestamps.”
Compliance pipeline deduplication
“I need to deduplicate and sort these 45 public-class audit events into a consistent order before sending them to our compliance archive — can you run them through the normalizer?”
Audit batch validation before ingestion
“I've got a mixed batch of 60 audit metadata events with dataClass 'public' that might have malformed digests or duplicate identifiers — normalize and validate them so only clean, ordered records come out.”
Technical details
Endpoint
POSThttps://www.mahastrategies.com/api/v1/micro/audit-export-normalizerWhen to prefer
Choose this endpoint when you need a lightweight, deterministic normalization pass over a batch of audit metadata events — particularly when deduplication and malformed-record rejection are required before downstream archival or compliance export. It is not suitable when you need to verify event provenance, prove completeness, or validate against an external audit system.
Side effects
- Malformed timestamps or digests cause individual events to be rejected rather than normalized
- Duplicate identifiers are silently dropped without notification of which were removed
- Batch exceeds 100 events — request is rejected
- Empty events array — minimum 1 event required
- Invalid dataClass value (must be 'public' or 'synthetic') causes request rejection
- Missing required body fields returns a schema validation error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| inputrequired | object | |
| output | object |
Tags
x402
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