# RAG Chunk Overlap Analyzer

> RAG Chunk Overlap Analyzer is a paid API for AI agents from signalharness.ai, paid per call via x402, $0.01/call, status unknown (last checked 2026-09-15).

Analyzes chunk overlap configuration in RAG (Retrieval-Augmented Generation) pipelines and returns structured analysis results

## Facts

- Endpoint: POST https://signalharness.ai/api/agent/services/rag_chunk_overlap_analyze/invoke
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-09-15
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/rag-chunk-overlap-analyzer-387a37ed
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_ytBxTx5486rKs06PWyPst

Status and success rate cover calls made through Zero and Zero's own probes. Third-party monitors may report differently.

## How to call it through Zero

Zero handles the 402 payment challenge and records the run. With the Zero CLI installed (`npm i -g @zeroxyz/cli`):

```sh
zero fetch --capability rag-chunk-overlap-analyzer-387a37ed -d '<json body>'
```

Example prompt: Can you analyze this RAG chunk overlap configuration for me and flag any issues? Here's the JSON: {"chunk_size": 512, "overlap": 128, "strategy": "sliding_window"}

## When to prefer this

Choose this endpoint when you need a quick, low-cost ($0.01 USDC) programmatic analysis of RAG chunk overlap parameters without standing up your own evaluation infrastructure. It is particularly useful for AI agent workflows that need to validate or audit chunking configurations as part of a larger pipeline, and when you want a structured JSON result with a verifiable receipt for auditing purposes.

## Known failure modes

- Malformed or invalid JSON in request_json field returns an error
- Oversized input exceeding 65536 characters is rejected
- Missing required request_json field causes a validation error
- Caller-supplied data warnings always present — results are not independently verified
- Network or payment settlement failures may result in no execution

## 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 object containing an analysis_json field with structured findings, a list of warnings about the supplied configuration, an evidence_scope indicator, and a full receipt with payment and execution metadata including latency, service version, and a SHA256 result hash.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "request_json": {
   "type": "string",
   "maxLength": 65536,
   "minLength": 2
  }
 }
}
```

## Response schema (JSON Schema)

```json
{
 "type": "json",
 "example": {
  "replay": false,
  "result": {
   "warnings": [
    "Verify the caller-supplied data before relying on this result."
   ],
   "service_id": "rag_chunk_overlap_analyze",
   "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_chunk_overlap_analyze",
   "executionId": "example-execution",
   "startedAtMs": 0,
   "amountAtomic": "10000",
   "resultSha256": "a672753083bc23ea611146cdf06bed9f6a5a46d5512b92b21e48fbd712507d00",
   "serviceVersion": "1.0.0",
   "settlementReference": "0x0000000000000000000000000000000000000000000000000000000000000000"
  },
  "artifacts": [],
  "requestId": "example-request",
  "executionId": "example-execution"
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/rag-chunk-overlap-analyzer-387a37ed/health.json
- [Zero catalog index](https://www.zero.xyz/llms.txt)
- [Other services from signalharness.ai](https://www.zero.xyz/host/signalharness.ai/llms.txt)