{"uid":"cap_gHdBpUX1tytp8TFmtNaFe","slug":"signalharness-model-output-disagreement-extract-8ea65026","name":"SignalHarness Model Output Disagreement Extract","description":"Explore 330 pay-per-call x402 API services and 27 agent-native digital products, with Base USDC pricing, secure Polar checkout, and free discovery.","url":"https://signalharness.ai/api/agent/services/model_output_disagreement_extract/invoke","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"request_json":{"type":"string","maxLength":65536,"minLength":2}}},"responseSchema":{"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"}},"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"0.005","displayCostAsset":"USDC","priceDynamic":false,"priceHint":null,"priceStatus":"priced","priceSource":"probe","requiresHandshake":false,"reviewCount":0,"rating":{"score":"0.00","successRate":"0.00","reviews":0,"stars":null,"state":"unrated"},"availabilityStatus":"unknown","priceObserved":null,"sessionDeposit":null,"pricing":{"kind":"static","summary":"$0.005/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.005","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.005","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_w_35JWqd73SQRiI8kPPCW","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.005","costPer":"request","priority":0,"asset":"0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913","unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Extracts and analyzes disagreements or inconsistencies between multiple AI model outputs from caller-supplied JSON data","exampleAgentPrompt":"I ran the same question through three different LLMs and got different answers — can you extract and summarize where they disagree? Here's the JSON with all their outputs: {\"models\":[{\"name\":\"gpt-4\",\"answer\":\"Paris\"},{\"name\":\"claude-3\",\"answer\":\"London\"},{\"name\":\"gemini\",\"answer\":\"Paris\"}]}","exampleUseCases":[{"title":"LLM ensemble conflict detection","prompt":"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?"},{"title":"Fact-checking multi-model outputs","prompt":"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?"},{"title":"Model reliability audit","prompt":"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?"}],"resultDescription":"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.","failureModes":["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"],"whenToPreferThis":"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.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-09-15T19:01:34.949Z","isFirstParty":false}