# Texture Streaming Analytics — Numeric Row Ordering + Trailing Mean Series

> Texture Streaming Analytics — Numeric Row Ordering + Trailing Mean Series is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-11-02).

Computes numeric row ordering and a trailing mean series for supplied texture streaming records (loaded_mb and stream_ms) across up to 200 rows, returning two analytical reports.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-game-09-115?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-11-02
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/texture-streaming-analytics-numeric-row-ordering-trailing-mean-series-8bd14a8f
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_1D2ZtlCJj3upgS0tBOBRw

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 texture-streaming-analytics-numeric-row-ordering-trailing-mean-series-8bd14a8f -d '<json body>'
```

Example prompt: I have 50 rows of texture streaming data with loaded_mb and stream_ms fields — can you rank them numerically by loaded_mb and also compute a trailing mean series with a window of 5 for those rows?

## When to prefer this

Choose this endpoint when you have raw texture streaming records (with loaded_mb and stream_ms metrics) and need both a ranked numeric ordering of rows and a trailing/rolling mean series computed from your own supplied data — without any live data lookup, external enrichment, or predictive modeling. It is ideal for game developers or analysts wanting lightweight, local analytical summaries of texture performance logs at very low cost ($0.01 USDC for both reports).

## Known failure modes

- Fewer than 1 row supplied — request rejected
- More than 200 rows supplied — exceeds maximum item limit
- Invalid date format (not YYYY-MM-DD) — validation error
- Window size smaller than 2 or larger than 200 — rejected
- Field value not 'loaded_mb' or 'stream_ms' — enum validation error
- Numeric fields outside allowed range — schema rejection
- Missing required row fields (row_id, game_area, date) — validation error

## How this service works

Texture streaming — Numeric row ordering + Trailing mean series: Numeric row ordering + Trailing mean series for supplied texture streaming records (loaded_mb, stream_ms). 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 numeric row ordering (ranking) of the supplied texture streaming records by the chosen metric, and (2) a trailing mean series computed over the selected field (loaded_mb or stream_ms) using the specified window size. No external lookups or predictions are made — all computation is performed on the supplied data rows.

## Request schema (JSON Schema)

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/texture-streaming-analytics-numeric-row-ordering-trailing-mean-series-8bd14a8f/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)