{"uid":"cap_-pXbVVcjC-5LqlLPEdq_y","slug":"agentdiet-context-window-distiller-df051df8","name":"AgentDiet Context Window Distiller","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/api?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":{"url":{"type":"string"},"mode":{"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":"0.001","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":"$0.001/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.001","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.001","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_-dKFZf-TUCwu9XfE66P_x","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.001","costPer":"request","priority":0,"asset":"0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913","unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Compresses and distills AI agent context windows to reduce token count by up to 85-91% while preserving semantic content","exampleAgentPrompt":"Fetch and compress the content at https://example.com/long-article using AgentDiet so it fits into my context window with minimal tokens — I need the distilled output and the compression ratio achieved.","exampleUseCases":[{"title":"Compress research page for agent","prompt":"Grab the content from https://arxiv.org/abs/2401.00001 and run it through AgentDiet's context distiller so I can include it in my prompt without blowing out my token budget — show me the compression ratio."},{"title":"Reduce LLM pipeline context costs","prompt":"My agent is fetching docs from https://docs.example.com/reference and it's eating up 80% of my context window — can you use AgentDiet to compress that page content and tell me how much token reduction I get?"},{"title":"Distill web content for A2A workflow","prompt":"Before passing this URL's content to the next agent in my pipeline, compress it with AgentDiet using GET mode so the downstream model only sees the essential information — what's left after de-bloating?"}],"resultDescription":"Returns a JSON object with a 'status' field (ok/error), a 'data' object containing the compressed/distilled content, and a 'roi_proof' object including 'compression_ratio_pct' showing the percentage of tokens removed (e.g. 91.4%).","failureModes":["Invalid or unreachable URL returns error status","Unsupported HTTP method returns validation error","Content already minimal yields low compression ratio","Payment not settled in USDC on Base causes 402 rejection","Missing required 'type' or 'method' fields returns schema validation error"],"whenToPreferThis":"Choose AgentDiet when your AI agent pipeline needs to fetch external web content and then pass it to an LLM, but the raw content is too large for the context window or would consume excessive tokens and increase cost. Ideal for A2A, MCP, and automated agent workflows where token efficiency matters and deterministic compression (not lossy summarization) is preferred. Best for pipelines already using x402/L402 micropayment protocols on Base.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-22T12:43:56.014Z","isFirstParty":false,"canonicalSlug":"agentdiet-context-window-distiller-10ea96b4"}