{"uid":"cap_oyHsTaWg1ZtJgTr83CDPi","slug":"signalharness-rag-document-prepare-f80bdfb9","name":"SignalHarness RAG Document Prepare","description":"Explore 330 pay-per-call x402 API services and 27 agent-native digital products, with Base USDC pricing, secure Polar checkout, and free discovery.","url":"https://signalharness.ai/api/agent/services/rag_document_prepare/invoke","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"request_json":{"type":"string","maxLength":65536,"minLength":2}}},"responseSchema":{"type":"json","example":{"replay":false,"result":{"warnings":["Verify the caller-supplied data before relying on this result."],"service_id":"rag_document_prepare","analysis_json":"{\"example\":\"schema-valid caller-supplied data\"}","evidence_scope":"caller_supplied_data"},"status":"succeeded","receipt":{"asset":"0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913","usage":[],"status":"succeeded","network":"eip155:8453","artifacts":[],"endedAtMs":0,"latencyMs":0,"paymentId":"example-payment","receiptId":"example-receipt","requestId":"example-request","serviceId":"rag_document_prepare","executionId":"example-execution","startedAtMs":0,"amountAtomic":"10000","resultSha256":"604f1fcc3bbd4882765c4ac89b435bc259c59f83189d7eed83daea8c840119f5","serviceVersion":"1.0.0","settlementReference":"0x0000000000000000000000000000000000000000000000000000000000000000"},"artifacts":[],"requestId":"example-request","executionId":"example-execution"}},"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_zH8nCh7_jvt0k_2sJX0Yy","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":"Prepares and analyzes caller-supplied document data for use in retrieval-augmented generation (RAG) pipelines, returning structured analysis JSON with validation warnings.","exampleAgentPrompt":"I need to prepare this document data for my RAG pipeline — can you run it through the SignalHarness rag_document_prepare service and give me back the structured analysis JSON so I can use it for retrieval?","exampleUseCases":[{"title":"Knowledge base document ingestion","prompt":"I have a JSON blob of product documentation I want to add to my RAG knowledge base — can you prepare and analyze it so it's ready for embedding and retrieval?"},{"title":"Pre-embedding document validation","prompt":"Before I embed these support articles into my vector store, can you run them through the RAG document prepare service to validate and structure the content?"},{"title":"Structured extraction for agent memory","prompt":"I've got a set of research notes in JSON format that I want my agent to be able to retrieve later — please prepare them through the RAG document pipeline and return the analysis JSON."}],"resultDescription":"Returns a JSON object containing: an analysis_json field with structured caller-supplied data, a warnings array (e.g. data verification reminders), evidence_scope indicating the data source, a status field ('succeeded'), and a signed receipt with payment details, execution IDs, latency, network info (Base/eip155:8453), amount paid in atomic USDC units, and a SHA256 hash of the result for integrity verification.","failureModes":["Invalid or malformed request_json input (too short, not valid JSON) returns an error","request_json exceeding 65536 characters rejected with payload-too-large error","Payment failure via x402 protocol results in 402 response and no processing","Network or execution timeout may result in failed status in receipt","Caller-supplied data flagged with verification warnings if schema is ambiguous"],"whenToPreferThis":"Choose this endpoint when you need to prepare and validate document data specifically for RAG (retrieval-augmented generation) workflows, especially when you want a pay-per-call model with cryptographic receipts on the Base network. Prefer it over general-purpose chunking or embedding tools when you need built-in audit trails via SHA256 result hashes and USDC micropayment receipts, or when operating in an agent-native x402 payment environment.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-09-15T19:01:31.364Z","isFirstParty":false}