# Save Files Analytics — Numeric Row Ordering + Date by Category Pivot

> Save Files Analytics — Numeric Row Ordering + Date by Category Pivot 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).

Analyzes save-file records (save_kb, write_ms) by producing two reports: a numeric row ordering and a date-by-category pivot table, for up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-game-13-122?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/save-files-analytics-numeric-row-ordering-date-by-category-pivot-978c3793
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_VZt4rKUgoyfUYpCVvKQ-L

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 save-files-analytics-numeric-row-ordering-date-by-category-pivot-978c3793 -d '<json body>'
```

Example prompt: Can you run the numeric row ordering and date-by-category pivot reports on these save file records — the field I want analyzed is save_kb, and here are my rows: row-1, 2026-10-01, game_area group-a, save_kb 10, write_ms 1; row-2, 2026-10-02, group-b, 20, 2; row-3, 2026-10-03, group-a, 15, 3?

## When to prefer this

Choose this endpoint when you have tabular game save-file data (with row IDs, game areas, dates, save sizes in KB, and write times in ms) and need both a ranked ordering by a numeric metric AND a cross-tabulated date-by-category pivot in a single call. Best for offline/local analytical reporting on supplied data up to 200 rows, with no need for live lookups or predictions.

## Known failure modes

- Input rows array is empty or missing — validation error returned
- row_id or game_area exceeds 80-character limit — schema validation failure
- date field does not match YYYY-MM-DD pattern — rejected with format error
- More than 200 rows submitted — request rejected due to row limit
- field value is not 'save_kb' or 'write_ms' — enum validation failure
- save_kb or write_ms values outside allowed numeric range — validation error
- Payment not included or insufficient — x402 payment required response

## How this service works

Save files — Numeric row ordering + Date by category pivot: Numeric row ordering + Date by category pivot for supplied save files records (save_kb, write_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 that ranks the supplied save-file records by the chosen metric (save_kb or write_ms), and (2) a date-by-category pivot table that cross-tabulates save file metrics by game_area and date. Both reports are computed locally from the supplied data with no external lookups.

## Request schema (JSON Schema)

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/save-files-analytics-numeric-row-ordering-date-by-category-pivot-978c3793/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)