{"uid":"cap_vPckq7wtayfqPELPa1BEc","slug":"verity-suite-ground-calibrated-question-answering-abb07dcd","name":"Verity Suite Ground — Calibrated Question Answering","description":"The trust fabric for AI agents — calibrated, fail-closed services agents pay per call.","url":"https://verity-suite.onrender.com/ground","method":"POST","headers":{},"bodySchema":{"type":"object","required":["question"],"properties":{"context":{"type":"string","description":"optional context to consider"},"question":{"type":"string","description":"the question to answer"}}},"responseSchema":{"type":"object","title":"ground_out","required":["answer","confidence"],"properties":{"answer":{"type":"string","title":"Answer","description":"the answer, or an honest statement that it cannot be determined"},"caveats":{"type":"array","items":{"type":"string"},"title":"Caveats","description":"gaps, assumptions, or uncertainties"},"sources":{"type":"array","items":{"type":"string"},"title":"Sources","description":"real sources actually used (empty if none)"},"confidence":{"type":"number","title":"Confidence","maximum":1,"minimum":0,"description":"calibrated probability the answer is correct"}}},"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"0.25","displayCostAsset":"USDC","priceDynamic":false,"priceHint":null,"priceStatus":"priced","priceSource":"registry","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_FwtO6dUUA7CPcwbJsGxAM","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.25","costPer":"request","priority":0,"asset":null,"unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Answers a question with a calibrated confidence score, caveats, and sources, designed for AI agents that need reliable, fail-closed factual grounding","exampleAgentPrompt":"Using Verity Suite's grounding endpoint, answer this question with a calibrated confidence score: 'Did the United States ratify the Paris Climate Agreement?' — here's some context: 'The user is writing a policy brief and needs a reliable, sourced answer with any important caveats noted.'","exampleUseCases":[{"title":"Fact-check medical claim with confidence","prompt":"I need you to fact-check this claim for me using a service that gives an honest confidence score and flags any caveats: 'Metformin is approved by the FDA as a first-line treatment for type 2 diabetes.' The answer will go into a patient-facing health summary, so I need sourced grounding and I'd rather get an honest 'uncertain' than a confident wrong answer."},{"title":"Verify legal precedent before brief","prompt":"Before I finalize this litigation brief, can you verify whether the Supreme Court ruling in Chevron U.S.A. v. Natural Resources Defense Council established the two-step deference doctrine for administrative agencies? I need a calibrated confidence score and any important caveats — if there's ambiguity or the answer can't be confirmed, say so explicitly rather than guessing."},{"title":"Ground financial data in due diligence","prompt":"We're running due diligence on an acquisition target and I need a reliable, sourced answer to this question: 'Was Silicon Valley Bank supervised by the Federal Reserve at the time of its March 2023 collapse?' Please use a grounding service that returns an explicit confidence level and notes any gaps or assumptions — this is going into an investor report so accuracy matters more than fluency."}],"resultDescription":"Returns a structured object with: a direct answer (or an honest statement that the answer cannot be determined), a calibrated confidence score between 0 and 1 representing the probability the answer is correct, an optional list of caveats noting gaps or assumptions, and an optional list of actual sources used.","failureModes":["Missing required 'question' field returns a validation error","Question is too ambiguous to answer confidently — returns low confidence score with honest uncertainty statement","Sources list may be empty if no verifiable references were used","Context field ignored if not relevant to the question","Service may be unavailable on Render's free tier due to cold start or resource limits"],"whenToPreferThis":"Choose this endpoint when an AI agent needs a calibrated, uncertainty-aware answer to a factual question — especially in high-stakes or trust-sensitive workflows where overconfident or hallucinated answers are unacceptable. Prefer it over generic LLM completions when you need an explicit confidence score, structured caveats, and sourced grounding rather than a fluent but potentially fabricated response.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-09-13T18:35:25.297Z","isFirstParty":false}