# Brand Mention Inventories — Record Quality Audit, String Normalisation & Weighted Mean

> Brand Mention Inventories — Record Quality Audit, String Normalisation & Weighted Mean 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).

Audits record quality, normalises strings, and computes secondary-measure weighted means for brand mention inventory data (mention_count, source_count) across up to 200 rows in three bundled analytical reports.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-company-18-205?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-record-quality-audit-string-normalisation-86a60a78
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_OTk5YAF5EIFNV5SzImvEz

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-record-quality-audit-string-normalisation-86a60a78 -d '<json body>'
```

Example prompt: Can you audit and clean my brand mention inventory data — check record quality, normalise the company_group strings, and compute a source_count-weighted mean of mention_count? Here are my rows: [{"row_id":"r1","company_group":"Acme Corp","date":"2025-01-15","mention_count":120,"source_count":5},{"row_id":"r2","company_group":"acme corp","date":"2025-01-16","mention_count":95,"source_count":3}].

## When to prefer this

Choose this endpoint when you have up to 200 rows of brand mention inventory data and need three bundled offline analytical operations — record quality auditing, string normalisation, and weighted mean computation — in a single low-cost call ($0.01 USDC). It is ideal when you do not need live data lookup, predictions, or external enrichment, and want fast, deterministic local analysis of existing mention_count and source_count data.

## Known failure modes

- Fewer than 1 row or more than 200 rows submitted — request rejected
- Row missing required fields (row_id, company_group, date, mention_count, source_count) — validation error
- date field does not match YYYY-MM-DD pattern — schema validation failure
- field enum value not 'mention_count' or 'source_count' — rejected
- All values for the selected numeric field are null — weighted mean cannot be computed
- Payment not included or insufficient USDC — x402 payment required error

## How this service works

Brand mention inventories — Record quality audit + String normalisation + Secondary-measure weighted mean: Record quality audit + String normalisation + Secondary-measure weighted mean for supplied brand mention inventories records (mention_count, source_count). Up to 200 rows; 3 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 3 supplied-data reports for up to 200 rows.

## Output

Three analytical reports covering: (1) a record quality audit flagging issues such as nulls, out-of-range values, and duplicate row IDs; (2) string normalisation results for company_group and other string fields; and (3) a secondary-measure weighted mean of the selected numeric field (mention_count or source_count) weighted by the other measure. All computed locally from supplied data, no 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
  },
  "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-record-quality-audit-string-normalisation-86a60a78/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)