{"uid":"cap_fYzdgTHIVVJITQxdCqQdO","slug":"signalharness-model-output-consensus-analyze-6b1694f8","name":"SignalHarness Model Output Consensus Analyze","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_consensus_analyze/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_consensus_analyze","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_consensus_analyze","executionId":"example-execution","startedAtMs":0,"amountAtomic":"25000","resultSha256":"23fd4698aecf730fa18abbb2a0df7a72e76a112142bab949c017f2d844c0d22a","serviceVersion":"1.0.0","settlementReference":"0x0000000000000000000000000000000000000000000000000000000000000000"},"artifacts":[],"requestId":"example-request","executionId":"example-execution"}},"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"0.025","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":"$0.025/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.025","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.025","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_uDu5kZc1Fdnp7XwGV-731","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.025","costPer":"request","priority":0,"asset":"0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913","unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Analyzes caller-supplied JSON data to evaluate consensus or consistency across model outputs, returning structured analysis with warnings and evidence scope.","exampleAgentPrompt":"Can you run a consensus analysis on these three model outputs I collected and tell me if they agree? Here's the JSON: {\"model_a\": \"positive\", \"model_b\": \"positive\", \"model_c\": \"negative\"}.","exampleUseCases":[{"title":"Multi-model sentiment agreement check","prompt":"I got sentiment predictions from three different LLMs on a customer review and I want to know if they agree — can you run consensus analysis on this JSON: {\"gpt4\": \"positive\", \"claude\": \"positive\", \"gemini\": \"neutral\"}?"},{"title":"Detecting conflicting classification outputs","prompt":"My pipeline ran the same document through two classifiers and got different labels — can you analyze this output JSON for consensus and flag where they disagree: {\"classifier_1\": \"spam\", \"classifier_2\": \"not_spam\"}?"},{"title":"Validating ensemble model predictions","prompt":"I have an ensemble of five models that each predicted a risk score for this loan application — can you analyze this JSON and tell me if there's consensus or significant divergence: {\"model_scores\": [0.82, 0.79, 0.85, 0.80, 0.91]}?"}],"resultDescription":"Returns a JSON object containing an analysis_json field with structured consensus findings, a warnings array (e.g. reminders to verify caller-supplied data), and an evidence_scope field indicating the data provenance (caller_supplied_data). Wrapped in a receipt with payment metadata including paymentId, requestId, executionId, latencyMs, and a resultSha256 for integrity verification.","failureModes":["Malformed or invalid JSON in request_json field causes rejection","Input JSON exceeding 65536 character limit is refused","Caller-supplied data that does not represent model outputs may yield low-utility analysis","Analysis warnings indicate results are not independently verified — reliance risk","Payment failure on Base network prevents execution"],"whenToPreferThis":"Choose this endpoint when you need a lightweight, pay-per-call consensus analysis on JSON-encoded model outputs without standing up your own evaluation infrastructure. Ideal for multi-model pipelines where you want a third-party check on output agreement. Best suited for structured JSON data from LLMs, classifiers, or scoring models. Prefer alternatives if you need real-time streaming analysis, very large payloads, or domain-specific model evaluation frameworks.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-09-15T19:01:33.967Z","isFirstParty":false}