{"uid":"cap_vfHeo8cQBzfPWai7ieAs_","slug":"agentdiet-research-digest-87e19f88","name":"AgentDiet Research Digest","description":"Deterministic B2A/A2A/MCP/x402/MPP/L402 execution and intelligence node at https://status.agentdiet.dev settling in USDC on Base.","url":"https://status.agentdiet.dev/v1/research-digest?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_08gsy3wjihWQCE4iemNkV","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":"Returns a compressed, token-efficient research digest by distilling input queries into a summarized intelligence output, reducing context window bloat by up to 91%.","exampleAgentPrompt":"Can you pull a compressed research digest on 'large language model alignment techniques' — I want the token-efficient summary version that cuts out the bloat, like AgentDiet does?","exampleUseCases":[{"title":"Token-efficient market research for agents","prompt":"Get me a compressed research digest on 'decentralized AI compute markets' — I need it distilled down to the key intelligence, not the full verbose output, so my agent doesn't burn through its context window."},{"title":"Research briefing for autonomous workflow","prompt":"Fetch a research digest on 'USDC stablecoin adoption trends' using a GET query, and give me back the compressed summary with the compression ratio so I know how much I saved."},{"title":"Pre-flight intelligence check before reasoning task","prompt":"Before I send this to my reasoning agent, can you run a research digest on 'Ethereum Layer 2 scaling solutions' and return the distilled version — I want to keep my context slim and focused?"}],"resultDescription":"Returns a JSON object with a 'data' field containing the compressed research output, a 'status' field ('ok' on success), and a 'roi_proof' object showing the compression_ratio_pct (e.g. 91.4%), demonstrating how much token bloat was removed.","failureModes":["Missing or malformed 'query' parameter returns empty or error data payload","Payment not settled in USDC on Base results in 402 Payment Required response","Invalid HTTP method (not GET or POST) returns schema validation error","Upstream research source unavailable may return empty data with ok status","Rate limiting or quota exhaustion may result in failed requests"],"whenToPreferThis":"Choose this endpoint when an AI agent needs to retrieve research on a topic while aggressively minimizing token consumption. It is ideal for agentic pipelines where context window space is at a premium, for pre-processing research before feeding it into a reasoning step, or when you need verifiable proof of compression (roi_proof). Prefer it over raw web search or uncompressed retrieval when the downstream consumer is an LLM with limited context or when token cost is a concern.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-22T12:43:53.785Z","isFirstParty":false,"canonicalSlug":"agentdiet-research-digest-87e19f88"}