# Brand Mention Inventories — Category Frequencies + Two-Measure Correlation

> Brand Mention Inventories — Category Frequencies + Two-Measure Correlation is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-20).

Computes category frequencies and a two-measure correlation (mention_count vs source_count) for up to 200 rows of brand mention inventory data using local analytical engines.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-company-18-108?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-20
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/brand-mention-inventories-category-frequencies-two-measure-correlation-8e6f3d79
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_e9ntwEBM9Lry0wP0g4A6_

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 brand-mention-inventories-category-frequencies-two-measure-correlation-8e6f3d79 -d '<json body>'
```

Example prompt: I have brand mention data for two company groups — GroupA and GroupB — with mention counts and source counts across several dates. Can you run a category frequency breakdown by company group and also compute the correlation between mention_count and source_count across all the rows?

## When to prefer this

Choose this endpoint when you have structured brand mention records with numeric mention_count and source_count fields and need both a group-level frequency breakdown and a correlation between the two measures in a single low-cost call. It is ideal for offline or batch analytical tasks on pre-collected data where no live data fetching, prediction, or external enrichment is needed.

## Known failure modes

- Missing required fields (row_id, company_group, date, mention_count, source_count) cause validation errors
- More than 200 rows submitted exceeds the row limit and will be rejected
- Invalid date format (not YYYY-MM-DD) causes schema validation failure
- Null values in both measure columns may result in undefined or degenerate correlation output
- Payment not supplied or insufficient USDC causes x402 payment rejection

## How this service works

Brand mention inventories — Category frequencies + Two-measure correlation: Category frequencies + Two-measure correlation for supplied brand mention inventories records (mention_count, source_count). Up to 200 rows; 2 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 2 supplied-data reports for up to 200 rows.

## Output

Returns two analytical reports: (1) a category frequency table showing the distribution of records across company groups, and (2) a two-measure correlation analysis between mention_count and source_count across the supplied rows — all computed locally without external lookups.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "rows": {
   "type": "array",
   "items": {
    "type": "object",
    "required": [
     "row_id",
     "company_group",
     "date",
     "mention_count",
     "source_count"
    ],
    "properties": {
     "date": {
      "type": "string",
      "default": "",
      "pattern": "^\\d{4}-\\d{2}-\\d{2}$",
      "maxLength": 10
     },
     "row_id": {
      "type": "string",
      "default": "",
      "maxLength": 80,
      "minLength": 1
     },
     "source_count": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "company_group": {
      "type": "string",
      "default": "",
      "maxLength": 80
     },
     "mention_count": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     }
    },
    "additionalProperties": false
   },
   "default": [
    {
     "date": "2026-10-01",
     "row_id": "row-1",
     "source_count": 1,
     "company_group": "group-a",
     "mention_count": 10
    },
    {
     "date": "2026-10-02",
     "row_id": "row-2",
     "source_count": 2,
     "company_group": "group-b",
     "mention_count": 20
    },
    {
     "date": "2026-10-03",
     "row_id": "row-3",
     "source_count": 3,
     "company_group": "group-a",
     "mention_count": 15
    },
    {
     "date": "2026-10-04",
     "row_id": "row-4",
     "source_count": 4,
     "company_group": "group-b",
     "mention_count": 30
    }
   ],
   "maxItems": 200,
   "minItems": 1
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/brand-mention-inventories-category-frequencies-two-measure-correlation-8e6f3d79/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)