{"uid":"cap_poxcdY1RYN44UXIAAmtq7","slug":"prama-dynamagh-intelligence-api-7d1c6312","name":"PRAMA-Dynamagh Intelligence API","description":"Paid machine intelligence with Evidence, provenance, PRAMAgraph structural evaluation, Decision, Ticket and capability-bound Consumer Result.","url":"https://prama-dynamagh.up.railway.app/v1/public/ask?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"query":{"type":"string","minLength":1},"intent":{"type":["string","null"],"description":"Optional application-level semantic hint; legacy alias. Takes precedence over requested_intent when present, including null. Not necessarily a Telegraph Intent_ID."},"request":{"type":"string","minLength":1},"requested_intent":{"type":["string","null"],"description":"Optional application-level semantic hint / request metadata. Not necessarily a Telegraph Intent_ID; Telegraph owns protocol resolution."}}},"responseSchema":null,"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"0.01","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":"$0.01/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.01","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.01","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_oKy-ym49KvytO-W468Lsl","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.01","costPer":"request","priority":0,"asset":"0x036CbD53842c5426634e7929541eC2318f3dCF7e","unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Answers queries using paid machine intelligence with structured evidence, provenance tracking, PRAMAgraph evaluation, and capability-bound consumer results.","exampleAgentPrompt":"Ask PRAMA-Dynamagh: 'What are the primary causes of lithium-ion battery degradation?' and return the structured decision along with the evidence and provenance it cites.","exampleUseCases":[{"title":"Evidence-backed research question","prompt":"I need a well-sourced answer to 'What regulatory frameworks govern AI liability in the EU?' — use PRAMA-Dynamagh and give me the decision plus the evidence and provenance behind it."},{"title":"Structured decision for business analysis","prompt":"Query PRAMA-Dynamagh with 'Is remote-first hiring correlated with higher employee retention?' and show me the structured evaluation result, including any evidence graph it returns."},{"title":"Provenance-tracked fact check","prompt":"Run 'Did global average sea surface temperatures reach a record high in 2023?' through PRAMA-Dynamagh and give me its decision along with the cited provenance so I can verify the sources."}],"resultDescription":"Returns a structured response containing a machine-intelligence-generated decision or answer, supporting evidence with provenance information, a PRAMAgraph structural evaluation, a ticket reference, and a capability-bound consumer result. The response is designed to be auditable and traceable.","failureModes":["Missing or empty 'query' and 'request' fields return a validation error","Payment failure via x402 protocol prevents query execution","Ambiguous intent forwarding may cause misrouted responses if intent field is malformed","Query too vague or malformed may return low-confidence or empty decision","Network/railway infrastructure downtime causes 5xx errors"],"whenToPreferThis":"Choose this endpoint when you need machine intelligence answers that include structured evidence, provenance tracking, and an auditable reasoning graph (PRAMAgraph) rather than a plain text response. It is particularly suitable for research, compliance, or fact-checking workflows where the sourcing and credentialing of the answer matters as much as the answer itself. Prefer it over generic LLM APIs when you need a ticket/consumer-result artifact alongside the response.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-27T18:32:48.161Z","isFirstParty":false,"canonicalSlug":"prama-dynamagh-intelligence-api-7d1c6312"}