{"uid":"cap_YclY6yIOYHAnQiCPlF3Ux","slug":"signalharness-model-output-format-comparator-b028f7a0","name":"SignalHarness Model Output Format Comparator","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_format_compare/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_format_compare","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_format_compare","executionId":"example-execution","startedAtMs":0,"amountAtomic":"15000","resultSha256":"174530b0091f3e0b45d79c56aaa8ee5164494253f20b0885763703ba534700a8","serviceVersion":"1.0.0","settlementReference":"0x0000000000000000000000000000000000000000000000000000000000000000"},"artifacts":[],"requestId":"example-request","executionId":"example-execution"}},"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"0.015","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":"$0.015/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.015","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.015","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_Me0ywrI_EIQUBiC7RW8_p","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.015","costPer":"request","priority":0,"asset":"0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913","unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Compares and analyzes model output formats from caller-supplied JSON data to surface structural and schema differences","exampleAgentPrompt":"Compare these two model output formats for me and tell me how they differ structurally — I'm passing in a JSON object with both the OpenAI and Anthropic response schemas and want to know if they're compatible.","exampleUseCases":[{"title":"LLM output schema standardization audit","prompt":"I have JSON samples from GPT-4 and Claude — can you compare their output formats and flag any structural mismatches or incompatibilities I should know about?"},{"title":"Multi-model pipeline compatibility check","prompt":"We're building a pipeline that routes between two models — run a format comparison on these two output JSON samples and tell me if the schemas are aligned enough to use interchangeably."},{"title":"AI response format regression check","prompt":"Our model was updated last week and I want to check if the output format changed — here's a JSON blob with the old and new response structures, please compare them and highlight any differences."}],"resultDescription":"Returns an analysis_json object containing the comparison findings between the supplied model output formats, along with any warnings about data reliability. The response also includes a receipt with payment metadata (paymentId, amountAtomic, network, latency) and an evidence_scope field indicating the data source was caller-supplied.","failureModes":["Malformed or invalid JSON in request_json returns a parse error","request_json below minimum length (2 chars) or above maximum (65536 chars) is rejected","Missing required request_json field causes a validation error","Caller-supplied data that is structurally ambiguous may trigger warnings in the analysis","Empty or trivially small JSON may produce low-confidence analysis results"],"whenToPreferThis":"Use this endpoint when you need a quick, low-cost ($0.015 USDC) programmatic comparison of two or more AI model output format schemas — especially in pipelines where you need to verify cross-model compatibility, detect output drift after model updates, or standardize response structures. Prefer this over manual inspection or custom diffing logic when you want a structured analysis result with audit-trail receipts on Base USDC.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-09-14T06:40:03.816Z","isFirstParty":false}