# Brand Mention Inventories — Category Frequencies & Daily Sum Series

> Brand Mention Inventories — Category Frequencies & Daily Sum Series is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-16).

Computes category-level frequency breakdowns and daily sum time series for supplied brand mention inventory data (mention_count, source_count) across company groups.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-company-18-102?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-16
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/brand-mention-inventories-category-frequencies-daily-sum-series-6acb4303
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_jnn8q9U1WAaxJox_CEP6c

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-daily-sum-series-6acb4303 -d '<json body>'
```

Example prompt: I have a list of daily brand mention records for group-a and group-b spanning October 2026 — can you run category frequency and daily sum series reports on the mention_count field for these rows and show me the breakdown?

## When to prefer this

Choose this endpoint when you have already collected brand mention inventory data (with date, company_group, mention_count, source_count fields) and need both a category-level frequency breakdown and a daily aggregated time series in one call. It is ideal for offline/batch analytical summarization of up to 200 rows without requiring any external data lookup or live data feed. Prefer this over live brand monitoring APIs when your data is already gathered and you simply need structured aggregation reports.

## Known failure modes

- Rows array is empty or missing — returns validation error
- More than 200 rows submitted — exceeds maximum input limit
- Invalid date format (not YYYY-MM-DD) — row rejected or error returned
- Field enum value not recognized — defaults or errors depending on implementation
- Null numeric values in mention_count/source_count may be excluded from sums
- row_id missing or too long — schema validation failure

## How this service works

Brand mention inventories — Category frequencies + Daily sum series: Category frequencies + Daily sum series 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 independent analytical reports: (1) category frequencies showing how mention_count or source_count values are distributed across company_group categories, and (2) a daily sum time series aggregating the selected metric by date — both computed locally against the supplied rows (up to 200).

## 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
  },
  "field": {
   "enum": [
    "mention_count",
    "source_count"
   ],
   "type": "string",
   "default": "mention_count"
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/brand-mention-inventories-category-frequencies-daily-sum-series-6acb4303/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)