# Simulation Caches — String Normalisation + Base-100 Series

> Simulation Caches — String Normalisation + Base-100 Series is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-21).

Performs string normalisation and base-100 index series analysis on user-supplied simulation cache records (cache_gb, simulation_seconds) for up to 200 rows, returning two analytical reports.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-creative-08-030?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-21
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/simulation-caches-string-normalisation-base-100-series-20c79dc4
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_xGyj7eEm6HmxHWr3r2wXw

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 simulation-caches-string-normalisation-base-100-series-20c79dc4 -d '<json body>'
```

Example prompt: Can you run string normalisation and base-100 indexing on my simulation cache data? I have 4 rows with cache_gb values [10, 20, 15, 30] for groups A and B from October 2026, and I want to index on cache_gb starting from row 0.

## When to prefer this

Choose this endpoint when you have tabular simulation cache records with cache_gb and simulation_seconds fields and need both string normalisation and base-100 index series in a single low-cost call ($0.01 USDC for two reports). It is ideal for offline/batch analytical tasks on supplied data — no external data sources, predictions, or live lookups are involved. Prefer it over general-purpose analytics tools when you want deterministic, reproducible indexing anchored to a specific base row within a compact dataset of up to 200 rows.

## Known failure modes

- Empty or missing rows array returns a validation error
- More than 200 rows submitted causes a rejection due to maxItems constraint
- Invalid date format (not YYYY-MM-DD) triggers a pattern validation failure
- Missing required fields (row_id, asset_group, date, cache_gb, simulation_seconds) in any row causes an error
- base_index value exceeding the number of submitted rows may yield undefined indexing behaviour
- Non-numeric cache_gb or simulation_seconds values outside allowed range cause schema rejection

## How this service works

Simulation caches — String normalisation + Base-100 series: String normalisation + Base-100 series for supplied simulation caches records (cache_gb, simulation_seconds). 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 structured analytical reports for the submitted simulation cache rows: (1) string-normalised representations of the selected field values, and (2) a base-100 index series anchored at the specified base_index row — covering up to 200 rows per call, computed entirely on supplied data with no external lookups.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "rows": {
   "type": "array",
   "items": {
    "type": "object",
    "required": [
     "row_id",
     "asset_group",
     "date",
     "cache_gb",
     "simulation_seconds"
    ],
    "properties": {
     "date": {
      "type": "string",
      "default": "",
      "pattern": "^\\d{4}-\\d{2}-\\d{2}$",
      "maxLength": 10
     },
     "row_id": {
      "type": "string",
      "default": "",
      "maxLength": 80,
      "minLength": 1
     },
     "cache_gb": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "asset_group": {
      "type": "string",
      "default": "",
      "maxLength": 80
     },
     "simulation_seconds": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     }
    },
    "additionalProperties": false
   },
   "default": [
    {
     "date": "2026-10-01",
     "row_id": "row-1",
     "cache_gb": 10,
     "asset_group": "group-a",
     "simulation_seconds": 1
    },
    {
     "date": "2026-10-02",
     "row_id": "row-2",
     "cache_gb": 20,
     "asset_group": "group-b",
     "simulation_seconds": 2
    },
    {
     "date": "2026-10-03",
     "row_id": "row-3",
     "cache_gb": 15,
     "asset_group": "group-a",
     "simulation_seconds": 3
    },
    {
     "date": "2026-10-04",
     "row_id": "row-4",
     "cache_gb": 30,
     "asset_group": "group-b",
     "simulation_seconds": 4
    }
   ],
   "maxItems": 200,
   "minItems": 1
  },
  "field": {
   "enum": [
    "cache_gb",
    "simulation_seconds"
   ],
   "type": "string",
   "default": "cache_gb"
  },
  "base_index": {
   "type": "integer",
   "default": 0,
   "maximum": 199,
   "minimum": 0
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/simulation-caches-string-normalisation-base-100-series-20c79dc4/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)