# Save Files Numeric Distribution and Adjacent Row Changes Analyzer

> Save Files Numeric Distribution and Adjacent Row Changes Analyzer 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 two local analytical reports: a numeric distribution summary and an adjacent row change report, for up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-game-13-077?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-numeric-distribution-and-adjacent-row-changes-analyzer-5f8cae10
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_vxKxNYP3iJ_KNMrQj0OL9

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-numeric-distribution-and-adjacent-row-changes-analyzer-5f8cae10 -d '<json body>'
```

Example prompt: Can you analyze the distribution of save_kb values and show me how they change between adjacent rows for my save file records? Here's my data: row-1 on 2026-10-01 in group-a had save_kb=10 and write_ms=1, row-2 on 2026-10-02 in group-b had save_kb=20 and write_ms=2, row-3 on 2026-10-03 in group-a had save_kb=15 and write_ms=3 — run the numeric distribution and adjacent row changes reports on the save_kb field.

## When to prefer this

Choose this endpoint when you have tabular game save file records with save_kb and write_ms fields and need both a distributional overview and sequential row-to-row change detection in a single low-cost call. It is best suited for offline batch analysis of up to 200 rows without needing external lookups, predictions, or real-time data. Prefer alternatives if you need trailing averages, IQR outlier flagging, grouped summaries, or analyses of non-save-file datasets.

## Known failure modes

- Missing required fields (row_id, game_area, date, save_kb, write_ms) causes validation error
- More than 200 rows submitted exceeds the maxItems limit and is rejected
- Invalid date format (not YYYY-MM-DD) fails schema validation
- Field value outside numeric bounds causes rejection
- Empty rows array returns an error
- Non-numeric values in save_kb or write_ms (when not null) cause computation failure

## How this service works

Save files — Numeric distribution + Adjacent row changes: Numeric distribution + Adjacent row changes 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 analytical reports: (1) a numeric distribution breakdown of the selected field (save_kb or write_ms) across up to 200 rows, showing spread, frequency, and distributional characteristics; and (2) an adjacent row changes report showing differences between consecutive row values, highlighting sequential variation in the save file metric.

## 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-numeric-distribution-and-adjacent-row-changes-analyzer-5f8cae10/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)