# Loot Observations — String Normalisation + Adjacent Row Changes

> Loot Observations — String Normalisation + Adjacent Row Changes 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).

Normalises game_area strings and computes adjacent row changes for loot observation records (drop_count or attempt_count) across up to 200 rows, returning 2 analytical reports.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-game-05-029?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/loot-observations-string-normalisation-adjacent-row-changes-64908f1b
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap__lyheDgCbv48OmEO2JR68

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 loot-observations-string-normalisation-adjacent-row-changes-64908f1b -d '<json body>'
```

Example prompt: Can you normalise the game_area strings and calculate row-over-row changes in drop_count for these loot records? I have 4 rows: row-1 on 2026-10-01 in group-a with drop_count 10 and attempt_count 1, row-2 on 2026-10-02 in group-b with drop_count 20 and attempt_count 2, row-3 on 2026-10-03 in group-a with drop_count 15 and attempt_count 3, and row-4 on 2026-10-04 in group-b with drop_count 30 and attempt_count 4.

## When to prefer this

Choose this endpoint when you need both string normalisation of categorical game area labels and adjacent row change computation on loot metrics in a single low-cost call. It is ideal for game analytics pipelines processing sequential loot observation data without needing live lookups, external enrichment, or predictions. At $0.01 USDC for 2 reports on up to 200 rows, it is cost-effective for batch offline analysis of game session logs.

## Known failure modes

- Exceeding 200 rows returns a validation error
- Missing required fields (row_id, game_area, date, drop_count, attempt_count) cause rejection
- Invalid date format (not YYYY-MM-DD) triggers a pattern validation error
- Numeric values outside ±1,000,000,000,000 are rejected
- Invalid field enum value (anything other than drop_count or attempt_count) causes an error
- Payment failure or insufficient USDC balance prevents processing

## How this service works

Loot observations — String normalisation + Adjacent row changes: String normalisation + Adjacent row changes for supplied loot observations records (drop_count, attempt_count). 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 2 independent analytical reports: one covering string normalisation of the game_area field across all submitted rows, and one showing adjacent (row-to-row) changes in the selected numeric field (drop_count or attempt_count). No external lookups or predictions are included.

## Request schema (JSON Schema)

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/loot-observations-string-normalisation-adjacent-row-changes-64908f1b/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)