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SignalHarness RAG Answer Quality Report
x402
SignalHarness RAG Answer Quality Report is a paid API for AI agents from signalharness.ai, paid per call via x402, $0.05/call, status unknown (last checked 2026-09-13).
Analyzes and scores the quality of answers produced by a RAG (Retrieval-Augmented Generation) pipeline, returning a structured quality report with warnings and evidence scope.
Price / call$0.05
Success—
StatusUnknown
How this service works
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Output
Returns a JSON object containing an analysis_json field with the quality assessment, a list of warnings (e.g. about caller-supplied data reliability), and an evidence_scope field indicating whether the evaluation is based on caller-supplied data. Also includes a full execution receipt with payment and timing metadata.
Example use cases
Catching hallucinations in a RAG chatbot
“I'm running a customer support chatbot backed by a RAG pipeline — can you evaluate this answer it just gave against the retrieved context and tell me if it's hallucinating or if the quality looks good?”
QA audit before deploying RAG responses
“Before we ship these RAG-generated answers to production, can you run a quality report on each one to flag anything that looks low-quality or unsupported by the source documents?”
Benchmarking a new RAG retriever
“I just swapped in a new retriever for my RAG system — can you analyze the answer quality from a sample query I ran so I can compare it against our old baseline?”
Technical details
Endpoint
POSThttps://signalharness.ai/api/agent/services/rag_answer_quality_report/invokeWhen to prefer
Choose this endpoint when you need a programmatic, per-call quality assessment of RAG pipeline outputs — especially when you want a structured JSON report with explicit warnings and evidence scope. Prefer it over manual review or generic LLM prompting when you need reproducible, receipt-backed evaluations at $0.05 per call via USDC on Base.
Side effects
- Malformed or invalid request_json payload returns an error
- request_json exceeds 65536 character limit
- Missing required fields in request_json cause processing failure
- Payment failure over x402 protocol prevents execution
- Low-quality or ambiguous input data may produce unreliable quality scores (warned via warnings array)
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": "rag_answer_quality_report",
"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": "rag_answer_quality_report",
"executionId": "example-execution",
"startedAtMs": 0,
"amountAtomic": "50000",
"resultSha256": "d1161a5c9c3281fcf87abb52fb32c8196aa74b487b574c62e55c782623f5b4ce",
"serviceVersion": "1.0.0",
"settlementReference": "0x0000000000000000000000000000000000000000000000000000000000000000"
},
"artifacts": [],
"requestId": "example-request",
"executionId": "example-execution"
}
}Tags
x402
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