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SignalHarness LLM Eval Regression Report
x402
SignalHarness LLM Eval Regression Report is a paid API for AI agents from signalharness.ai, paid per call via x402, $0.025/call, status unknown (last checked 2026-09-15).
Generates a regression analysis report for LLM evaluation results, detecting quality regressions across model versions or prompts.
Price / call$0.025
Success—
StatusUnknown
How this service works
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Output
Returns a JSON object containing an analysis_json field with the structured regression findings, a warnings array (e.g. reminders to verify caller-supplied data), an evidence_scope label indicating the data provenance, and a receipt object with payment and execution metadata including service version, latency, and a SHA-256 result hash for integrity verification.
Example use cases
Pre-deployment model quality gate
“Before I ship the new version of my fine-tuned model, run this eval results JSON through the regression checker and tell me if anything got meaningfully worse compared to baseline.”
Prompt engineering regression check
“I changed several system prompts in my pipeline and here are the before-and-after evaluation results as JSON — can you analyze them for regressions and summarize which prompts caused quality drops?”
Continuous eval monitoring report
“Here's the latest nightly LLM eval output JSON from our CI pipeline — run a regression report on it and flag any test cases that degraded since last week's run.”
Technical details
Endpoint
POSThttps://signalharness.ai/api/agent/services/llm_eval_regression_report/invokeWhen to prefer
Choose this endpoint when you need a structured, pay-per-call regression analysis of LLM evaluation data without standing up your own eval infrastructure. It is particularly well-suited for CI/CD pipelines, pre-deployment quality gates, or ad hoc regression checks on prompt changes, and is priced at $0.025 USDC per call making it cost-effective for frequent automated use.
Side effects
- Malformed or too-short request_json (below 2 chars) returns a validation error
- Payload exceeding 65536 characters is rejected
- Caller-supplied data that does not conform to expected eval schema may produce unreliable analysis with warnings
- Payment failure via x402 protocol results in a 402 response before execution
- Network or service timeout returns an error status in the receipt
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": "llm_eval_regression_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": "llm_eval_regression_report",
"executionId": "example-execution",
"startedAtMs": 0,
"amountAtomic": "25000",
"resultSha256": "d376eb6705d37d8522d0688051a70b42c49c43a5713e4a3864904938432c28b3",
"serviceVersion": "1.0.0",
"settlementReference": "0x0000000000000000000000000000000000000000000000000000000000000000"
},
"artifacts": [],
"requestId": "example-request",
"executionId": "example-execution"
}
}Tags
x402
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