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SignalHarness Search Result Score Normalizer
x402
SignalHarness Search Result Score 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 raw search result scores from caller-supplied data into a consistent, comparable scale
Price / call$0.005
Success—
StatusUnknown
How this service works
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Output
Returns a JSON object containing normalized score analysis, a warnings array (e.g. reminders to verify caller-supplied data), the original service_id, and a signed receipt with payment details, execution metadata, and a SHA-256 result hash for auditability.
Example use cases
Unifying multi-source search scores
“I ran the same query across three different search APIs and got back scores in totally different ranges — can you normalize all these scores into a common 0-to-1 scale so I can rank the combined results? Here's the raw JSON with all the scores.”
Cleaning vector similarity scores for display
“My vector search returned cosine similarity scores but they're all over the place — some are negative, some above 1 due to floating point issues. Can you normalize these scores so they're clean and consistent before I show them to users?”
Preprocessing scores for a ranking pipeline
“Before I feed these search result scores into my re-ranking model, I need to normalize them to remove scale bias — here's the JSON blob of raw scores from my retrieval step, please normalize them.”
Technical details
Endpoint
POSThttps://signalharness.ai/api/agent/services/search_result_score_normalize/invokeWhen to prefer
Choose this endpoint when you need a lightweight, pay-per-call microservice to normalize search result scores on the fly without spinning up custom normalization infrastructure. Particularly useful in agent pipelines that aggregate results from heterogeneous search backends with incompatible score ranges.
Side effects
- Invalid or malformed JSON in request_json field — returns error
- Input JSON exceeds 65536 character limit — rejected
- Empty or too-short input string (minLength 2) — rejected
- Caller-supplied data fails internal schema validation — may return with warnings rather than hard failure
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| request_json | string |
Output
Schema · Response
{
"type": "json",
"example": {
"replay": false,
"result": {
"warnings": [
"Verify the caller-supplied data before relying on this result."
],
"service_id": "search_result_score_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_score_normalize",
"executionId": "example-execution",
"startedAtMs": 0,
"amountAtomic": "5000",
"resultSha256": "9a7730e95f7e13dbc9252299fd4c13b3267bfbd7f72ec3f3caeae829be5246da",
"serviceVersion": "1.0.0",
"settlementReference": "0x0000000000000000000000000000000000000000000000000000000000000000"
},
"artifacts": [],
"requestId": "example-request",
"executionId": "example-execution"
}
}Tags
x402
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