{"uid":"cap_DZ8-A7wf3qcI-F0A7WtRr","slug":"signalharness-multi-agent-trace-compare-8ff067cb","name":"SignalHarness Multi-Agent Trace Compare","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/multi_agent_trace_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":"multi_agent_trace_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":"multi_agent_trace_compare","executionId":"example-execution","startedAtMs":0,"amountAtomic":"15000","resultSha256":"f9b89e88c5feed8adccd165ccc339508f0c307332e99386015a9dd568ba81e5c","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_dsLDSBEMp9mPg8sFujtKH","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 execution traces from multiple AI agents to surface differences, warnings, and behavioral insights.","exampleAgentPrompt":"I ran the same task through two different agent configurations and want to understand where they diverged — can you compare these execution traces and flag any warnings or behavioral differences?","exampleUseCases":[{"title":"Debugging agent version regression","prompt":"I updated my agent's prompt and now it's behaving differently — here are trace logs from the old and new versions. Can you compare them and tell me what changed or went wrong?"},{"title":"Multi-agent coordination audit","prompt":"We have two agents that were supposed to collaborate on a research task but gave conflicting outputs. Can you analyze their traces side-by-side and identify where they diverged?"},{"title":"A/B evaluation of agent configurations","prompt":"I tested two agent setups on the same customer support scenario. Here are both trace JSONs — which one handled it better and were there any warnings in either run?"}],"resultDescription":"Returns a JSON analysis object containing a comparison of the submitted agent traces, any warnings about the data (e.g. caller-supplied data caveats), an evidence_scope field indicating data provenance, and a structured analysis_json with findings. Also includes a full receipt with payment metadata, execution IDs, latency, and a SHA-256 result hash for verification.","failureModes":["Malformed or invalid JSON in request_json field returns a validation error","Caller-supplied data that cannot be parsed as agent traces may yield low-confidence or empty analysis","Oversized payloads exceeding 65536 characters are rejected","Missing or incomplete trace data may result in warnings about insufficient evidence scope","Network or payment settlement failures may cause execution to not complete"],"whenToPreferThis":"Choose this endpoint when you need to programmatically compare execution traces from two or more AI agents, especially for debugging behavioral regressions, auditing multi-agent coordination, or running A/B evaluations of agent configurations. It is particularly useful when you want a structured analysis with explicit warnings and evidence provenance rather than a manual diff. Prefer this over general-purpose LLM analysis when you need a receipted, pay-per-call service with verifiable output hashes.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-09-15T18:30:03.111Z","isFirstParty":false}