# Brand Mention Inventories — String Normalisation + Numeric Row Ordering

> Brand Mention Inventories — String Normalisation + Numeric Row Ordering 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).

Normalises company/group strings and orders rows numerically for brand mention inventory data (mention_count, source_count), producing 2 analytical reports for up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-company-18-025?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-string-normalisation-numeric-row-ordering-22eb3a10
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_xLxH4UAIDPdfW1SKrRB3V

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-string-normalisation-numeric-row-ordering-22eb3a10 -d '<json body>'
```

Example prompt: Take my brand mention inventory rows — including mention_count and source_count columns for groups like 'Acme Corp' and 'Beta Ltd' across dates in October 2026 — normalise the company_group strings and sort everything by mention_count, then give me the two standard analytical reports for up to 200 rows.

## When to prefer this

Choose this endpoint when you have brand mention inventory tabular data (up to 200 rows) that needs both string normalisation of company group names and numeric ordering of mention or source counts, and you want two bundled analytical reports at low cost ($0.01 USDC). It is a pure local computation — no live data fetching, prediction, or external side effects — making it ideal for deterministic, repeatable data-cleaning and sorting tasks on supplied brand monitoring datasets.

## Known failure modes

- More than 200 rows submitted — request will be rejected or truncated
- Missing required fields (row_id, company_group, date, mention_count, or source_count) — validation error
- Date field not matching YYYY-MM-DD format — schema validation failure
- Numeric values outside allowed range (±1,000,000,000,000) — rejection
- Invalid field enum value (not mention_count or source_count) — schema error
- Empty rows array — minimum 1 item required

## How this service works

Brand mention inventories — String normalisation + Numeric row ordering: String normalisation + Numeric row ordering 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

Two analytical reports covering: (1) string-normalised company_group values and (2) numerically ordered rows ranked by the selected field (mention_count or source_count), applied to up to 200 input rows using local analytical engines — no external lookups or predictions.

## 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-string-normalisation-numeric-row-ordering-22eb3a10/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)