{"uid":"cap_1PUz2kfsJ3m89kMEwdavi","slug":"agent-onchain-intelligence-consumption-footprint-decision-procedure-2ecbdd08","name":"Agent Onchain Intelligence Consumption Footprint Decision Procedure","description":"Paid agent-facing brief on agent onchain intelligence consumption footprint: post-settlement opacity and query-pattern leak decision procedure. How an agent that buys on-chain intelligence feeds (Arkham-style entity/intent data) via x402 avoids leaking what it cares about through its own payment patterns. The payment itself reveals intent: which endpoint was bought, from which wallet, how often, at what times. Decision rule. Blunt decision procedure, not marketing.","url":"https://k2so.wrong.systems/api/services/agent-onchain-intelligence-consumption-footprint?utm_source=zero.xyz","method":"GET","headers":{},"bodySchema":{"type":"object","$schema":"https://json-schema.org/draft/2020-12/schema","required":["input"],"properties":{"input":{"type":"object","required":["type","method"],"properties":{"type":{"type":"string","const":"http"},"method":{"enum":["GET","HEAD","DELETE"],"type":"string"},"queryParams":{"type":"object","properties":{"meta":{"enum":["0","1"],"type":"string","description":"Set to 1 for free metadata JSON (no payment required)"},"topic":{"type":"string","description":"Optional topic override for the decision procedure"}}}},"additionalProperties":false},"output":{"type":"object","required":["type"],"properties":{"type":{"type":"string"},"example":{"type":"object","title":"agent onchain intelligence consumption footprint: post-settlement opac paid response","$schema":"https://json-schema.org/draft/2020-12/schema","required":["ok","paid","service","provider","result"],"properties":{"ok":{"type":"boolean"},"paid":{"type":"boolean"},"result":{"type":"object","required":["ok","service"],"properties":{"ok":{"type":"boolean","description":"Handler success"},"brief":{"type":"string","description":"Decision procedure prose for agents"},"model":{"type":"string"},"topic":{"type":"string"},"service":{"type":"string","description":"Service slug"},"procedure":{"type":"string"},"generatedAt":{"type":"string","description":"ISO-8601 timestamp"},"generationSource":{"enum":["llm","reasoning","deterministic"],"type":"string"}}},"payment":{"type":"object","properties":{"code":{"type":"string"},"payer":{"type":"string"},"detail":{"type":"string"},"selfPay":{"type":"boolean"},"transaction":{"type":"string"}}},"service":{"type":"string"},"provider":{"type":"string","const":"K-2SO"}}}}}}},"responseSchema":null,"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"0.002","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":"$0.002/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.002","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.002","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_O04nn4KtE5aB1QbmB0THI","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.002","costPer":"request","priority":0,"asset":"0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913","unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Returns a paid LLM-generated decision procedure brief explaining how an AI agent should track, measure, and reason about its own onchain intelligence consumption footprint on Base.","exampleAgentPrompt":"Give me the decision procedure for how an autonomous agent should track and reason about its own onchain intelligence consumption footprint — I need the full prose brief from K-2SO.","exampleUseCases":[{"title":"Auditing agent API spend on Base","prompt":"My autonomous agent has been making paid x402 API calls on Base and I want to understand how it should track and audit its own intelligence consumption footprint — can you get me the decision procedure brief for that?"},{"title":"Building agent self-governance for data costs","prompt":"I'm building an autonomous agent that needs to self-govern its paid data usage on Base. Get me K-2SO's decision procedure on how an agent should reason about its onchain intelligence consumption footprint."},{"title":"Onboarding new agent to x402 cost awareness","prompt":"I'm onboarding a new AI agent to the x402 ecosystem and want it to understand how to monitor its own per-call onchain intelligence consumption — fetch me the decision procedure brief for the agent onchain intelligence consumption footprint service."}],"resultDescription":"A JSON object containing a plain-prose decision procedure brief (120+ words) tailored to how an AI agent should evaluate and manage its onchain intelligence consumption footprint, along with the model used (e.g. deepseek/deepseek-v4-flash-0731), the topic, generation source (llm/reasoning/deterministic), ISO-8601 timestamp, service slug, and provider identifier (K-2SO).","failureModes":["HTTP 402 returned if USDC payment not settled — agent must pay exact amount and retry with PAYMENT-SIGNATURE header","Invalid method (non-GET/HEAD/DELETE) returns 405","Malformed query params may result in 400 bad request","Service temporarily unavailable returns 503","LLM generation failure may fall back to deterministic source or return error"],"whenToPreferThis":"Choose this endpoint when an autonomous agent needs structured, prose-form guidance on how to track, measure, and govern its own onchain intelligence consumption footprint on Base — particularly in x402 payment ecosystems where per-call USDC costs accumulate. Prefer over generic documentation when the agent needs machine-readable decision procedures it can act on directly.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-20T18:55:38.643Z","isFirstParty":false,"canonicalSlug":"agent-onchain-intelligence-consumption-footprint-decision-procedure-2ecbdd08"}