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SignalHarness RAG Document Prepare
x402
SignalHarness RAG Document Prepare is a paid API for AI agents from signalharness.ai, paid per call via x402, $0.01/call, status unknown (last checked 2026-09-13).
Prepares and analyzes caller-supplied document data for use in retrieval-augmented generation (RAG) pipelines, returning structured analysis JSON with validation warnings.
Price / call$0.01
Success—
StatusUnknown
How this service works
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Output
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.
Example use cases
Knowledge base document ingestion
“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?”
Pre-embedding document validation
“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?”
Structured extraction for agent memory
“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.”
Technical details
Endpoint
POSThttps://signalharness.ai/api/agent/services/rag_document_prepare/invokeWhen to prefer
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.
Side effects
- 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
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| request_json | string |
Output
Schema · Response
{
"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"
}
}Tags
x402
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