{"uid":"cap_5ozb2W3FCwbWlXze-XReN","slug":"verity-suite-citation-endpoint-e3e2a7f6","name":"Verity Suite Citation Endpoint","description":"The trust fabric for AI agents — calibrated, fail-closed services agents pay per call.","url":"https://suite.veritylayer.dev/cite","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"statement":{"type":"string","title":"Statement","maxLength":2000,"minLength":1,"description":"the factual claim to find supporting sources for"},"domain_hint":{"anyOf":[{"type":"string","maxLength":2000},{"type":"null"}],"title":"Domain Hint","default":null,"description":"optional topic/field to focus the search (e.g. 'clinical', 'tax law')"}}},"responseSchema":null,"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"0.25","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":"$0.25/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.25","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.25","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_gqJ70sMNEazQiVCK_hQWL","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.25","costPer":"request","priority":0,"asset":"0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913","unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Finds and returns calibrated supporting citations for a factual statement, with a signed verdict on how strongly the sources establish the claim.","exampleAgentPrompt":"Can you find supporting citations for the claim 'regular aerobic exercise reduces the risk of type 2 diabetes by up to 50%' — focus on clinical sources — and tell me how strongly the evidence actually backs it up?","exampleUseCases":[{"title":"Fact-checking AI-generated health claims","prompt":"I need citations for the statement 'omega-3 fatty acids have been shown to reduce inflammation markers in adults with rheumatoid arthritis' — please search clinical literature and tell me how well-supported it is."},{"title":"Legal brief source verification","prompt":"Can you find authoritative sources supporting the claim 'employers in California are required to provide meal breaks after 5 hours of work'? Focus on tax law or employment law sources and give me a support score."},{"title":"Grounding AI agent outputs before publishing","prompt":"Before we publish this, check whether 'the global average temperature has risen by 1.1 degrees Celsius since pre-industrial times' is backed by credible sources and flag any caveats I should know about."}],"resultDescription":"Returns a verdict (supported, partially_supported, not_supported, or contradicted), a calibrated support score from 0 to 1, a list of citation objects, concrete reasons for the verdict (including why any candidate sources were rejected), optional caveats about coverage or recency, and an optional Ed25519-signed VerityLayer receipt for auditability.","failureModes":["Statement too vague or broad to retrieve relevant sources — low support score with explanatory reasons","Domain hint narrows search too aggressively, excluding valid sources — partial support returned","No credible sources found — verdict returns not_supported with support score near 0","Statement is contradicted by retrieved sources — verdict returns contradicted with reasons","Signing not configured — receipt field returns null","Statement exceeds 2000-character limit — request rejected with validation error","Network or upstream search failure — fail-closed behavior, error returned rather than hallucinated citations"],"whenToPreferThis":"Use this endpoint when an AI agent needs to ground a specific factual claim in real, verifiable sources before presenting it to a user or publishing it — especially when auditability matters (the signed receipt provides cryptographic proof of the result). Prefer this over generic search when you need a calibrated support score, structured citation objects, and explicit reasons why sources were accepted or rejected. The domain_hint parameter makes it particularly strong for domain-specific fact-checking (clinical, legal, financial). The fail-closed design means you get an honest 'not supported' rather than hallucinated references.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-09-14T12:51:24.987Z","isFirstParty":false}