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SignalHarness RAG Retrieval Result Normalizer
x402
SignalHarness RAG Retrieval Result Normalizer is a paid API for AI agents from signalharness.ai, paid per call via x402, $0.005/call, status unknown (last checked 2026-09-15).
Normalizes and validates RAG (Retrieval-Augmented Generation) retrieval result JSON into a standardized, schema-compliant format with warnings about data provenance.
Price / call$0.005
Success—
StatusUnknown
How this service works
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Output
Returns a structured JSON object containing: a normalized `analysis_json` string with the standardized retrieval data, a list of `warnings` about data provenance (e.g. reminding the caller to verify data), an `evidence_scope` field indicating the data source (e.g. 'caller_supplied_data'), a `service_id`, and a full payment receipt including request/execution IDs, USDC amount, network details, and a SHA256 hash of the result for integrity verification.
Example use cases
Standardize multi-source retrieval output
“I'm pulling retrieval results from three different vector stores and the schemas are all over the place — can you normalize this JSON from my Pinecone retrieval step into a consistent format so my downstream LLM agent can handle it? Here's the raw result: {"matches":[{"id":"doc_001","score":0.87,"metadata":{"text":"renewable energy trends"}}]}”
Validate RAG output before LLM ingestion
“Before I pass this retrieval result to my summarization agent, I want to make sure it's schema-valid and normalized — can you run this through the RAG result normalizer and flag any warnings? The raw JSON is: {"retrieved":[{"chunk_id":"c99","relevance":0.75,"content":"market analysis Q3 2024"}]}”
Clean up retrieval JSON in agentic pipeline
“My RAG pipeline is spitting out inconsistent result formats depending on which retriever fires — normalize this retrieval output so my orchestration layer gets a predictable structure: {"results":[{"ref":"paper_42","similarity":0.81,"snippet":"protein folding mechanisms in neural networks"}]}”
Technical details
Endpoint
POSThttps://signalharness.ai/api/agent/services/rag_retrieval_result_normalize/invokeWhen to prefer
Choose this endpoint when you need a lightweight, pay-per-call normalization step for RAG retrieval results within an agentic pipeline, especially when retrieval sources vary in schema or format. It is particularly useful when you want a receipt/audit trail (SHA256 hash, payment ID) for each normalization call, or when operating in a Base/USDC micropayment environment. Prefer alternatives if you need heavy-duty ETL, batch processing of many results at once, or normalization of non-RAG data types.
Side effects
- Invalid or malformed JSON in request_json field — returns parse error
- request_json string too short (< 2 chars) or too long (> 65536 chars) — returns validation error
- Payment failure via x402 protocol — service not invoked
- Caller-supplied data contains schema-incompatible structure — may return warnings rather than hard failure
- Network or execution timeout — receipt may show failed status
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_retrieval_result_normalize",
"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_retrieval_result_normalize",
"executionId": "example-execution",
"startedAtMs": 0,
"amountAtomic": "5000",
"resultSha256": "d0a857ce50979a8d3d0650dce54a1de2f0bbf2b4d809de732c28684099fe03cc",
"serviceVersion": "1.0.0",
"settlementReference": "0x0000000000000000000000000000000000000000000000000000000000000000"
},
"artifacts": [],
"requestId": "example-request",
"executionId": "example-execution"
}
}Tags
x402
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