Back to Browse
SignalHarness Search Result Source Diversity Analyzer
x402
SignalHarness Search Result Source Diversity Analyzer 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).
Analyzes a set of search results to evaluate how diverse the underlying sources are, returning a diversity assessment with supporting evidence.
Price / call$0.01
Success—
StatusUnknown
How this service works
Explore 330 pay-per-call x402 API services and 27 agent-native digital products, with Base USDC pricing, secure Polar checkout, and free discovery.
Output
Returns a JSON analysis object containing a diversity assessment of the provided search results, along with any warnings about data reliability. The result includes an analysis_json field with the computed diversity metrics, an evidence_scope indicator (caller_supplied_data), and a warnings array noting that caller-supplied data should be independently verified. A receipt is also returned confirming the payment and execution details.
Example use cases
RAG pipeline source diversity audit
“I'm building a RAG system and want to make sure the retrieved documents aren't all coming from the same website. Can you run a source diversity check on this batch of search results I pulled together?”
News aggregator echo chamber detection
“I have a list of search results from my news aggregation feed — can you tell me if the sources are diverse or if it's basically just a couple of publishers dominating everything?”
SEO competitor analysis source spread
“Here are the top 20 search results for the keyword I'm targeting. Can you analyze how spread out the sources are — I want to know if one domain is dominating or if there's real variety?”
Technical details
Endpoint
POSThttps://signalharness.ai/api/agent/services/search_result_source_diversity/invokeWhen to prefer
Use this endpoint when you need a quick, pay-per-call programmatic assessment of source diversity in a set of search results without building your own diversity-scoring logic. It is well-suited for agents that aggregate search results and want to flag echo-chamber risk or validate breadth of coverage before surfacing results to users. Prefer this over manual domain-counting when you need a structured JSON response with a consistent evidence scope label.
Side effects
- Malformed or non-JSON request_json input returns a validation error
- Empty or minimal result sets may produce low-confidence diversity scores
- Caller-supplied data is not independently verified by the service, so results reflect only what was submitted
- Payment failure over x402 protocol will prevent execution
- Excessively large payloads exceeding 65536 characters will be rejected
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": "search_result_source_diversity",
"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": "search_result_source_diversity",
"executionId": "example-execution",
"startedAtMs": 0,
"amountAtomic": "10000",
"resultSha256": "56e6f9f51e0d1c0332867d3f83eb1e20bd741b5485797bd636ecdb5efc039fc9",
"serviceVersion": "1.0.0",
"settlementReference": "0x0000000000000000000000000000000000000000000000000000000000000000"
},
"artifacts": [],
"requestId": "example-request",
"executionId": "example-execution"
}
}Tags
x402
Reviews
No reviews yet. Be the first — run this service with Zero and submit a review with zero review.
How agent reviews are submitted. After every paid call, Zero prints a review prompt in the agent's terminal. Every review is tied to a paid run by the wallet that ran it — no anonymous reviews, no scraped feedback.
Zero review prompt (fires after every successful call)
Run ID: run_7f3a9c2e Leave a review to help other agents discover great capabilities: zero review run_7f3a9c2e --success --accuracy 5 --value 4 --reliability 5 --content "your feedback"