# Save Files Analytics: Weighted Mean + Keyed Dataset Comparison

> Save Files Analytics: Weighted Mean + Keyed Dataset Comparison is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-30).

Computes a secondary-measure weighted mean and compares two keyed save-file datasets (save_kb, write_ms) across game areas, returning two analytical reports for up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-game-13-186?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-30
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/save-files-analytics-weighted-mean-keyed-dataset-comparison-59034884
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_HiXScZpePddpohDhyF3yJ

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-weighted-mean-keyed-dataset-comparison-59034884 -d '<json body>'
```

Example prompt: I have two sets of game save file records (up to 200 rows each, with save_kb and write_ms per game_area and date) — can you compute the weighted mean of save_kb using write_ms as the secondary measure, and also run a keyed comparison between the two datasets to see where they differ?

## When to prefer this

Choose this endpoint when you need both a weighted mean computation and a keyed row-level comparison between two save file datasets in a single call, specifically for game save performance data (save_kb and write_ms). It is purpose-built for game analytics workflows where you want to compare two snapshots or builds without external lookups or predictions — ideal for lightweight, offline analytical reporting at low cost.

## Known failure modes

- Fewer than 1 row provided — validation error
- More than 200 rows supplied — request rejected
- Missing required fields (row_id, game_area, date, save_kb, write_ms) — schema validation error
- Invalid date format (not YYYY-MM-DD) — pattern validation failure
- Null values in both save_kb and write_ms for a row may produce undefined weighted mean
- Duplicate row_ids may produce ambiguous keyed comparison results

## How this service works

Save files — Secondary-measure weighted mean + Keyed dataset comparison: Secondary-measure weighted mean + Keyed dataset comparison 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

Returns two reports: (1) a secondary-measure weighted mean of the selected field (save_kb or write_ms) across all supplied rows, weighted by the other measure, and (2) a keyed dataset comparison highlighting matching, differing, and unmatched rows between the primary and secondary input datasets, segmented by game_area.

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/save-files-analytics-weighted-mean-keyed-dataset-comparison-59034884/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)