{"uid":"cap_0HiXXo_YnnOhi7SKWQ0sz","slug":"agent-conflict-detector-c8a379e2","name":"Agent Conflict Detector","description":"Detect contradictory facts, negations and numeric mismatches before an agent acts","url":"https://agent-product-normalizer.vercel.app/api/v1/detect-conflicts","method":"GET","headers":{},"bodySchema":{"type":"object","$schema":"https://json-schema.org/draft/2020-12/schema","required":["input"],"properties":{"input":{"type":"object","required":["type","method"],"properties":{"type":{"type":"string","const":"http"},"method":{"enum":["GET"],"type":"string"},"queryParams":{"type":"object","required":["text"],"properties":{"text":{"type":"string","maxLength":20000,"description":"Facts or claims to check for contradictions"}},"additionalProperties":true}},"additionalProperties":false},"output":{"type":"object","required":["type"],"properties":{"type":{"type":"string"},"example":{"type":"object"}}}}},"responseSchema":null,"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"0.002","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":"$0.002/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.002","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.002","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_sgjd_26qVCUzAd1DAs1_O","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.002","costPer":"request","priority":0,"asset":"0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913","unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Detects contradictory facts, negations, and numeric mismatches in a block of text before an agent acts on it","exampleAgentPrompt":"Before you proceed, check this set of facts for contradictions, negations, or numeric mismatches: 'The shipment weighs 5kg. The shipment weighs 8kg. Delivery is scheduled for Monday. Delivery is not scheduled for Monday.'","exampleUseCases":[{"title":"Pre-action fact consistency check","prompt":"Before my agent books the hotel, check this context for contradictions: 'Check-in is June 10. Check-out is June 8. The room sleeps 2 guests. The booking is for 4 guests.' Are there any conflicts I should resolve first?"},{"title":"Agent memory conflict scan","prompt":"My agent has accumulated these notes from multiple sources and I want to make sure they don't contradict each other before handing off to the next step — can you scan them for any conflicting facts or negations?"},{"title":"Numeric mismatch detection in order data","prompt":"Here's a block of order summary text with prices and quantities from two different sources — check it for any numeric mismatches or contradictions before we process the payment."}],"resultDescription":"A structured report identifying any contradictory facts, negations, or numeric mismatches found in the input text, likely including the specific conflicting claims or values and their locations in the text, so the agent can resolve inconsistencies before acting.","failureModes":["Text exceeds 20,000 character limit — request will be rejected or truncated","No conflicts found — endpoint returns an empty or affirmative result, which the caller must handle correctly","Ambiguous phrasing may produce false positives if natural language is imprecise","Payment failure via x402 protocol results in 402 response and no analysis","Malformed or missing 'text' query parameter returns an error response"],"whenToPreferThis":"Choose this endpoint when an AI agent has accumulated facts from multiple sources (memory, tool outputs, user input) and needs to verify logical consistency before taking a consequential action. Ideal for pre-action safety checks, agent handoff validation, or any workflow where conflicting data could cause downstream errors. Prefer it over general-purpose LLM prompting when you want a fast, cheap, dedicated conflict-detection pass without spinning up a full reasoning chain.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-09-18T06:50:21.141Z","isFirstParty":false}