SignalHarness Search Result Normalizer is a paid API for AI agents from signalharness.ai, paid per call via x402, $0.005/call, status unknown (last checked 2026-09-15).
Normalizes and standardizes caller-supplied search result JSON into a consistent schema-valid format
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Returns a normalized analysis_json containing the standardized search result data, along with any warnings (e.g. about caller-supplied data), a service_id, evidence_scope, status, and a full execution receipt including payment details, result SHA-256 hash, network info, and timing metadata.
POSThttps://signalharness.ai/api/agent/services/search_result_normalize/invokeChoose this endpoint when you need to normalize or standardize search result JSON from heterogeneous sources into a consistent schema, especially in agentic pipelines that aggregate results from multiple search APIs. It is well-suited for pre-ingestion validation and normalization steps where consistency is critical. At $0.005 USDC per call it is cost-effective for high-frequency normalization tasks.
| Field | Type | Description |
|---|---|---|
| request_json | string |
{
"type": "json",
"example": {
"replay": false,
"result": {
"warnings": [
"Verify the caller-supplied data before relying on this result."
],
"service_id": "search_result_normalize",
"analysis_json": "{\"example\":\"schema-valid caller-supplied data\"}",
"evidence_scope": "caller_supplied_data"
},
"status": "succeeded",
"receipt": {
"asset": "0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913",
"usage": [],
"status": "succeeded",
"network": "eip155:8453",
"artifacts": [],
"endedAtMs": 0,
"latencyMs": 0,
"paymentId": "example-payment",
"receiptId": "example-receipt",
"requestId": "example-request",
"serviceId": "search_result_normalize",
"executionId": "example-execution",
"startedAtMs": 0,
"amountAtomic": "5000",
"resultSha256": "995c0485b9adf5e441a14775a53a69a601de0d76ca0c6c6f1f2e639917257b47",
"serviceVersion": "1.0.0",
"settlementReference": "0x0000000000000000000000000000000000000000000000000000000000000000"
},
"artifacts": [],
"requestId": "example-request",
"executionId": "example-execution"
}
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