# Commerce Intent Exact Normalised Duplicate Audit

> Commerce Intent Exact Normalised Duplicate Audit is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-12).

Audits up to 200 labelled commerce-intent text records to identify exact normalised duplicates across browse, purchase, return, and other categories.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-sector-ml-commerce-intent-duplicates?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-12
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/commerce-intent-exact-normalised-duplicate-audit-2c563c0f
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_LsneP6xgFPWZQc6hLkn2A

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 commerce-intent-exact-normalised-duplicate-audit-2c563c0f -d '<json body>'
```

Example prompt: Can you run an exact normalised duplicate audit on my commerce intent dataset? I have 150 labelled records with browse, purchase, return, and other categories — here they are — and I want to know which ones are exact duplicates after normalisation.

## When to prefer this

Choose this endpoint when you need a cheap, fast, and deterministic exact-match duplicate check on a small labelled commerce-intent dataset (up to 200 records) before training or benchmarking a classifier. It is not a semantic similarity tool or a hosted model — it uses local normalisation logic to find verbatim or near-verbatim duplicates. Prefer it over general deduplication tools when your data is specifically structured around browse, purchase, return, and other commerce intent labels and you want an audit deliverable rather than transformed data.

## Known failure modes

- Fewer than 2 records supplied — minimum input requirement not met
- More than 200 records supplied — exceeds maximum batch size
- Record ID missing or exceeds 80 characters — schema validation failure
- Text field exceeds 1000 characters per record — rejected
- Invalid intent label provided outside browse/purchase/return/other enum — validation error
- Payment of 0.01 USDC not completed — request blocked

## How this service works

Commerce intent - Exact normalised duplicate audit: Exact normalised duplicate audit for Commerce intent. 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 exact normalised duplicate audit deliverable.

## Output

A structured duplicate audit report identifying which of the supplied labelled text records are exact matches after normalisation, covering records labelled across browse, purchase, return, and other commerce intent categories. The deliverable is bounded to one audit per call for up to 200 records.

## 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": [
       "browse",
       "purchase",
       "return",
       "other"
      ],
      "type": "string"
     }
    },
    "additionalProperties": false
   },
   "default": [
    {
     "id": "example-0-0",
     "text": "browse sample document number 0 for this supplied dataset.",
     "actual": "browse"
    },
    {
     "id": "example-0-1",
     "text": "browse sample document number 1 for this supplied dataset.",
     "actual": "browse"
    },
    {
     "id": "example-0-2",
     "text": "browse sample document number 2 for this supplied dataset.",
     "actual": "browse"
    },
    {
     "id": "example-1-0",
     "text": "purchase sample document number 0 for this supplied dataset.",
     "actual": "purchase"
    },
    {
     "id": "example-1-1",
     "text": "purchase sample document number 1 for this supplied dataset.",
     "actual": "purchase"
    },
    {
     "id": "example-1-2",
     "text": "purchase sample document number 2 for this supplied dataset.",
     "actual": "purchase"
    },
    {
     "id": "example-2-0",
     "text": "return sample document number 0 for this supplied dataset.",
     "actual": "return"
    },
    {
     "id": "example-2-1",
     "text": "return sample document number 1 for this supplied dataset.",
     "actual": "return"
    },
    {
     "id": "example-2-2",
     "text": "return sample document number 2 for this supplied dataset.",
     "actual": "return"
    },
    {
     "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
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/commerce-intent-exact-normalised-duplicate-audit-2c563c0f/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)