{"uid":"cap_Zr2NKtRn0eKhHY8Sx_74w","slug":"agentdiet-llm-context-window-distiller-llms-generator-390c1f0b","name":"AgentDiet LLM Context Window Distiller (llms-generator)","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/llms-generator?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"}}}},"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_DvhAaqPcGLVMkJgvnM9OL","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":"Fetches and compresses LLM-related content from a given URL, distilling it into a token-efficient context window summary with up to 91% compression ratio","exampleAgentPrompt":"Fetch and compress the content at https://example.com/long-article into a token-efficient context window summary — I need the distilled version to feed into my LLM without blowing my token budget.","exampleUseCases":[{"title":"RAG pipeline token reduction","prompt":"I'm building a RAG pipeline and one of my source documents at https://docs.myproject.com/architecture is too long to fit in my context window — can you compress it down using AgentDiet so I only pass the essential content to my model?"},{"title":"Agent context window management","prompt":"My AI agent is hitting token limits when reading https://news.ycombinator.com/item?id=39000000 — run it through the context distiller so I can get an 80%+ compressed version that still preserves the key information."},{"title":"Summarizing technical documentation for LLM ingestion","prompt":"I need to feed the content from https://platform.openai.com/docs/guides/function-calling into an LLM but it's way too verbose — can you run it through the RAG diet compressor and give me the lean version?"}],"resultDescription":"Returns a JSON object with a 'data' field containing the distilled content, a 'status' field ('ok' on success), and an 'roi_proof' object showing the compression_ratio_pct achieved (e.g. 91.4% compression). The compressed output is designed to be directly usable as LLM context.","failureModes":["Invalid or unreachable URL returns error status","URL content too short or already minimal — compression ratio may be negligible","Payment failure via x402/USDC results in 402 response before content is returned","Unsupported content type at URL (e.g. binary files) may return empty or malformed data","Rate limiting or network timeout if target URL is slow to respond"],"whenToPreferThis":"Choose this endpoint when an AI agent or RAG pipeline needs to ingest web content but faces token budget constraints. It is particularly valuable when fetching long documentation pages, news articles, or web content that needs to be compressed before being passed to an LLM. Prefer this over raw web scrapers when token efficiency and context window optimization are the primary concern, and you need a verifiable compression ratio as proof of reduction.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-22T12:43:38.175Z","isFirstParty":false,"canonicalSlug":"agentdiet-llm-context-window-distiller-llms-generator-390c1f0b"}