# Save Files Analytics — Category Frequencies + IQR Outlier Flags

> Save Files Analytics — Category Frequencies + IQR Outlier Flags 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) to produce category frequency distributions and IQR-based outlier flags for up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-game-13-107?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-category-frequencies-iqr-outlier-flags-3485d464
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_CCoXcv4jiJ15vmZFSLxOI

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-category-frequencies-iqr-outlier-flags-3485d464 -d '<json body>'
```

Example prompt: I have 4 game save records across group-a and group-b areas — can you analyze the save_kb field to show me how often each game area appears and flag any rows with outlier save sizes using IQR? Rows: row-1 (2026-10-01, group-a, 10 KB, 1 ms), row-2 (2026-10-02, group-b, 20 KB, 2 ms), row-3 (2026-10-03, group-a, 15 KB, 3 ms), row-4 (2026-10-04, group-b, 30 KB, 4 ms).

## When to prefer this

Choose this endpoint when you have game save file telemetry data (up to 200 rows) and need both a categorical frequency breakdown by game area AND IQR-based statistical outlier detection on numeric save metrics (save_kb or write_ms) in a single $0.01 call. Prefer this over generic analytics tools when you specifically need these two combined local reports without any external data enrichment or prediction.

## Known failure modes

- Fewer than 1 row supplied — minimum input requirement not met
- More than 200 rows submitted — exceeds maximum row limit
- Missing required fields (row_id, game_area, date, save_kb, write_ms) in any row
- Invalid date format (must match YYYY-MM-DD pattern)
- Numeric fields out of accepted range (±1 trillion)
- Field enum value not one of 'save_kb' or 'write_ms'
- Payment not completed via x402 protocol — endpoint requires 0.01 USDC per call

## How this service works

Save files — Category frequencies + IQR outlier flags: Category frequencies + IQR outlier flags 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 category frequency table showing how often each game_area value appears across the supplied rows, and (2) IQR-based outlier flags for the selected numeric field (save_kb or write_ms), identifying which rows fall outside the interquartile range bounds. Both reports are generated 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-category-frequencies-iqr-outlier-flags-3485d464/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)