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SignalHarness Agent Research Quality Report
x402
SignalHarness Agent Research Quality Report is a paid API for AI agents from signalharness.ai, paid per call via x402, $0.05/call, status unknown (last checked 2026-09-15).
Analyzes and scores the quality of agent-submitted research or data, returning a structured quality assessment with warnings and evidence scope.
Price / call$0.05
Success—
StatusUnknown
How this service works
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Output
Returns a structured JSON result containing a quality analysis object, a list of warnings about data reliability, an evidence scope label (e.g. 'caller_supplied_data'), and a status field. Also includes a full payment receipt with network, asset, amount, and execution metadata on the Base network in USDC.
Example use cases
Pre-pipeline research validation
“Before I feed this market research JSON into my analysis pipeline, can you run a quality check on it and flag any issues or warnings about the evidence scope?”
Agent output auditing
“My AI agent just finished gathering data on competitor pricing — can you score the quality of its research output and tell me how much I should trust it?”
Multi-agent data handoff check
“I'm about to pass this research JSON from one agent to the next in my workflow — can you evaluate its quality first and highlight anything I should verify before proceeding?”
Technical details
Endpoint
POSThttps://signalharness.ai/api/agent/services/agent_research_quality_report/invokeWhen to prefer
Choose this endpoint when you need a fast, pay-per-call quality assessment of agent-generated or agent-collected research data before using it downstream. It is particularly useful in multi-agent pipelines where data provenance and reliability need to be checked at handoff points. Prefer it over manual review when you need a structured, machine-readable quality score with explicit warnings.
Side effects
- Malformed or non-JSON request_json input causes validation failure
- Input exceeds 65536 character limit returns an error
- Caller-supplied data that cannot be parsed results in schema-invalid response
- Network or payment failure on Base chain may prevent execution
- Empty or too-short input (below minLength of 2) is rejected
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": "agent_research_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": "agent_research_quality_report",
"executionId": "example-execution",
"startedAtMs": 0,
"amountAtomic": "50000",
"resultSha256": "0a0e97c4cd2e504a5c9c25f5ab3bae876f8d1af92b52614e1a1802377be81bee",
"serviceVersion": "1.0.0",
"settlementReference": "0x0000000000000000000000000000000000000000000000000000000000000000"
},
"artifacts": [],
"requestId": "example-request",
"executionId": "example-execution"
}
}Tags
x402
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