# Return Reason Training Evaluation Text Overlap

> Return Reason Training Evaluation Text Overlap is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-11).

Checks whether evaluation texts overlap with labeled training records used to classify product return reasons, detecting potential data leakage.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-sector-ml-return-reason-leakage?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-11
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/return-reason-training-evaluation-text-overlap-109ea506
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_LXfS3ET849IZeV0AuQRzO

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 return-reason-training-evaluation-text-overlap-109ea506 -d '<json body>'
```

Example prompt: Check whether any of my evaluation texts appear in or overlap with my labeled training records for return reason classification — I have 12 labeled records split across damaged, wrong_item, unwanted, and other categories, plus 5 evaluation texts I want to test for leakage.

## When to prefer this

Choose this endpoint when you need a fast, inexpensive ($0.01 USDC) check for text overlap between a labeled training set and evaluation texts specifically for return reason classification (damaged, wrong_item, unwanted, other). It is ideal for small datasets (up to 200 records) and local evaluation workflows where you want to detect data leakage without deploying a hosted model or using foundation model infrastructure.

## Known failure modes

- Fewer than 2 training records supplied — minimum items violation
- Evaluation texts array is empty or missing
- Individual text exceeds 1000 character limit
- Record ID missing or blank — required field violation
- Invalid actual label supplied outside of allowed enum values (damaged, wrong_item, unwanted, other)
- More than 200 records or evaluation texts supplied — exceeds maxItems limit
- Payment not included or insufficient — x402 payment required

## How this service works

Return reason - Training evaluation text overlap: Training evaluation text overlap for Return reason. Up to 200 supplied labelled text records. Local dataset tools, evaluation and small naive-Bayes baselines; no hosted model or foundation-model training. One of 25 profiles or calculations across 20 shared operations in this sector. 0.01 USDC includes one bounded training evaluation text overlap deliverable.

## Output

A bounded deliverable reporting the degree of text overlap between the supplied labeled training records and the evaluation texts, identifying which evaluation documents share content with training data and quantifying the extent of potential data leakage.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "records": {
   "type": "array",
   "items": {
    "type": "object",
    "required": [
     "id",
     "text",
     "actual"
    ],
    "properties": {
     "id": {
      "type": "string",
      "default": "",
      "maxLength": 80,
      "minLength": 1
     },
     "text": {
      "type": "string",
      "default": "",
      "maxLength": 1000
     },
     "actual": {
      "enum": [
       "damaged",
       "wrong_item",
       "unwanted",
       "other"
      ],
      "type": "string"
     }
    },
    "additionalProperties": false
   },
   "default": [
    {
     "id": "example-0-0",
     "text": "damaged sample document number 0 for this supplied dataset.",
     "actual": "damaged"
    },
    {
     "id": "example-0-1",
     "text": "damaged sample document number 1 for this supplied dataset.",
     "actual": "damaged"
    },
    {
     "id": "example-0-2",
     "text": "damaged sample document number 2 for this supplied dataset.",
     "actual": "damaged"
    },
    {
     "id": "example-1-0",
     "text": "wrong_item sample document number 0 for this supplied dataset.",
     "actual": "wrong_item"
    },
    {
     "id": "example-1-1",
     "text": "wrong_item sample document number 1 for this supplied dataset.",
     "actual": "wrong_item"
    },
    {
     "id": "example-1-2",
     "text": "wrong_item sample document number 2 for this supplied dataset.",
     "actual": "wrong_item"
    },
    {
     "id": "example-2-0",
     "text": "unwanted sample document number 0 for this supplied dataset.",
     "actual": "unwanted"
    },
    {
     "id": "example-2-1",
     "text": "unwanted sample document number 1 for this supplied dataset.",
     "actual": "unwanted"
    },
    {
     "id": "example-2-2",
     "text": "unwanted sample document number 2 for this supplied dataset.",
     "actual": "unwanted"
    },
    {
     "id": "example-3-0",
     "text": "other sample document number 0 for this supplied dataset.",
     "actual": "other"
    },
    {
     "id": "example-3-1",
     "text": "other sample document number 1 for this supplied dataset.",
     "actual": "other"
    },
    {
     "id": "example-3-2",
     "text": "other sample document number 2 for this supplied dataset.",
     "actual": "other"
    }
   ],
   "maxItems": 200,
   "minItems": 2
  },
  "evaluation_texts": {
   "type": "array",
   "items": {
    "type": "string",
    "default": "",
    "maxLength": 1000
   },
   "default": [
    "damaged sam
… (truncated)
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/return-reason-training-evaluation-text-overlap-109ea506/health.json
- [Zero catalog index](https://www.zero.xyz/llms.txt)
- [Other services from market.datapackvibe.com](https://www.zero.xyz/host/market.datapackvibe.com/llms.txt)