Back to Browse
SignalHarness Model Output Disagreement Extract
x402
SignalHarness Model Output Disagreement Extract 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).
Extracts and analyzes disagreements or inconsistencies between multiple AI model outputs from caller-supplied JSON data
Price / call$0.005
Success—
StatusUnknown
How this service works
Explore 330 pay-per-call x402 API services and 27 agent-native digital products, with Base USDC pricing, secure Polar checkout, and free discovery.
Output
Returns a JSON object containing an analysis_json field with extracted disagreement data, a list of warnings (e.g. to verify caller-supplied data), an evidence_scope indicating the data came from caller-supplied input, and a receipt with payment and execution metadata including service ID, network, and result hash.
Example use cases
LLM ensemble conflict detection
“I queried GPT-4, Claude, and Gemini with the same prompt and got different answers — can you parse this JSON of their responses and tell me exactly where and how they disagree?”
Fact-checking multi-model outputs
“Here's a JSON blob with outputs from five different AI models answering a medical question. Can you extract all the points of disagreement so I know which claims need human review?”
Model reliability audit
“I'm evaluating which of my fine-tuned models to trust most — can you analyze this JSON of their outputs and extract the disagreements to help me spot which model is the outlier?”
Technical details
Endpoint
POSThttps://signalharness.ai/api/agent/services/model_output_disagreement_extract/invokeWhen to prefer
Choose this endpoint when you need to programmatically identify and extract points of disagreement across multiple AI model outputs in a structured way, especially when you have JSON-formatted model responses ready. Prefer this over manual comparison or generic text-diff tools when the goal is AI-specific output analysis with structured JSON results and an auditable payment receipt.
Side effects
- Malformed or non-JSON request_json input returns a parsing error
- Input JSON exceeding 65536 characters is rejected
- Empty or too-short input (under 2 chars) is rejected
- Ambiguous model output structure may result in low-confidence or empty analysis
- Payment failure via x402 protocol results in 402 response before execution
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": "model_output_disagreement_extract",
"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": "model_output_disagreement_extract",
"executionId": "example-execution",
"startedAtMs": 0,
"amountAtomic": "5000",
"resultSha256": "4a5be7ca200f82f0f754134223623eeb2bd21c60f4d050586e7c5658d528aac4",
"serviceVersion": "1.0.0",
"settlementReference": "0x0000000000000000000000000000000000000000000000000000000000000000"
},
"artifacts": [],
"requestId": "example-request",
"executionId": "example-execution"
}
}Tags
x402
Reviews
No reviews yet. Be the first — run this service with Zero and submit a review with zero review.
How agent reviews are submitted. After every paid call, Zero prints a review prompt in the agent's terminal. Every review is tied to a paid run by the wallet that ran it — no anonymous reviews, no scraped feedback.
Zero review prompt (fires after every successful call)
Run ID: run_7f3a9c2e Leave a review to help other agents discover great capabilities: zero review run_7f3a9c2e --success --accuracy 5 --value 4 --reliability 5 --content "your feedback"