{"uid":"cap_CeeVpuTsMlbqCYzyGYpGm","slug":"agentdiet-citation-search-87f1be28","name":"AgentDiet Citation Search","description":"Deterministic B2A/A2A/MCP/x402/MPP/L402 execution and intelligence node at https://rag-diet.agentdiet.dev settling in USDC on Base.","url":"https://rag-diet.agentdiet.dev/v1/citation-search?utm_source=zero.xyz","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","POST"],"type":"string"},"queryParams":{"type":"object","properties":{"query":{"type":"string"}}}},"additionalProperties":false},"output":{"type":"object","required":["type"],"properties":{"type":{"type":"string"},"example":{"type":"object"}}}}},"responseSchema":{"type":"json","example":{"data":{},"status":"ok","roi_proof":{"compression_ratio_pct":91.4}}},"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"0.01","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":"$0.01/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_qZuhSAQKVCl1FXBvwiS_B","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.01","costPer":"request","priority":0,"asset":"0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913","unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Searches an indexed knowledge base and returns compressed, citation-backed results optimized for minimal token usage in AI agent context windows.","exampleAgentPrompt":"Search AgentDiet's citation index for 'transformer attention mechanisms' and give me the compressed, cited results — I need them to fit in a tight context window.","exampleUseCases":[{"title":"Research fact-checking with citations","prompt":"Search for 'climate change effects on ocean salinity' and return cited sources — I want compressed results I can feed into my next LLM call without blowing up my context."},{"title":"Agent knowledge retrieval pipeline","prompt":"Query AgentDiet's citation search for 'USDC stablecoin on Base blockchain' and bring back the distilled, citation-backed answer so I can use it in my reasoning step."},{"title":"Token-efficient document lookup","prompt":"I need to look up 'retrieval augmented generation best practices' and get back a highly compressed summary with citations — keep it under a few hundred tokens so my agent doesn't run out of context."}],"resultDescription":"Returns a JSON object with a 'data' field containing the search results and citations, a 'status' field ('ok' on success), and a 'roi_proof' object showing the compression_ratio_pct (e.g. 91.4%) achieved — confirming how much token reduction was applied to the retrieved content.","failureModes":["Missing required 'query' parameter returns an error or empty data","Invalid HTTP method (not GET or POST) rejected by schema validation","Payment failure via x402/USDC may result in 402 Payment Required response","Empty or vague queries may return low-relevance citations","Rate limits or node unavailability may return 5xx errors","Query too long or malformed may trigger schema validation failure"],"whenToPreferThis":"Choose this endpoint when an AI agent needs to retrieve cited, factual information while aggressively conserving context window tokens — the built-in compression (up to 91%+ ratio) makes it ideal for pipelines where retrieved content must be passed to downstream LLM calls. Prefer it over plain web search or RAG endpoints when you need both citation provenance and token efficiency in a single call, and when your payment infrastructure supports x402/USDC on Base.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-22T12:43:37.023Z","isFirstParty":false,"canonicalSlug":"agentdiet-citation-search-87f1be28"}