# Brand Mention Inventories — Trailing Mean Series + Adjacent Row Changes

> Brand Mention Inventories — Trailing Mean Series + Adjacent Row Changes 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 trailing moving-average series and adjacent-row delta changes for brand mention inventory data (mention_count or source_count) across up to 200 rows, returning two analytical reports.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-company-18-146?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-trailing-mean-series-adjacent-row-changes-fd3f6f2a
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_ha_abI-BnZ3hjMWcS4mGU

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-trailing-mean-series-adjacent-row-changes-fd3f6f2a -d '<json body>'
```

Example prompt: Calculate the trailing mean series and adjacent row changes for my brand mention data — I have 50 rows with mention_count and source_count for company groups like 'acme-corp', using a window size of 5, and I want the report based on mention_count.

## When to prefer this

Choose this endpoint when you have brand mention inventory data already in hand and need fast, local computation of rolling averages and period-over-period deltas without any external data lookup, prediction, or enrichment. Ideal for agents that batch-process brand monitoring records and need two complementary analytical views (smoothed trend + raw delta) in a single low-cost call.

## Known failure modes

- Missing required row fields (row_id, date, company_group) returns a validation error
- Window size larger than number of rows may produce partial or empty trailing mean results
- Rows exceeding 200-item limit are rejected
- Malformed date strings not matching YYYY-MM-DD pattern cause validation failure
- Null values in the selected metric field may produce gaps in the mean series

## How this service works

Brand mention inventories — Trailing mean series + Adjacent row changes: Trailing mean series + Adjacent row changes 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: (1) a trailing mean series showing the rolling average of the selected field (mention_count or source_count) over the specified window size, and (2) an adjacent row changes report showing the difference between consecutive row values — both computed locally against the supplied dataset of up to 200 rows.

## 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"
  },
  "window": {
   "type": "integer",
   "default": 2,
   "maximum": 200,
   "minimum": 2
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/brand-mention-inventories-trailing-mean-series-adjacent-row-changes-fd3f6f2a/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)