# M2M Trust Descriptive Statistics API

> M2M Trust Descriptive Statistics API is a paid API for AI agents from energybilltoolkit.co.uk, paid per call via x402, $0.01/call, status unknown (last checked 2026-09-15).

Computes deterministic descriptive statistics (mean, median, std dev, min, max, etc.) for a bounded finite numeric array

## Facts

- Endpoint: POST https://energybilltoolkit.co.uk/m2m-trust/api/tools/descriptive-stats
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-09-15
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/energybilltoolkit-co-uk-bb31e54b
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_tgnft4O9XUF4uS-QHZcYm

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 energybilltoolkit-co-uk-bb31e54b -d '<json body>'
```

Example prompt: Can you run deterministic descriptive statistics on this array of sensor readings: [12.4, 15.1, 9.8, 14.2, 11.7, 13.5, 10.9, 16.0, 12.8, 14.5]? I need mean, median, standard deviation, min, max, and variance.

## When to prefer this

Choose this endpoint when you need fully deterministic, reproducible descriptive statistics on a finite numeric array — especially in quality-control, audit, or M2M trust contexts where consistent outputs for identical inputs are required. Prefer over probabilistic or ML-based analytics tools when auditability and repeatability matter.

## Known failure modes

- Non-numeric values in array cause validation error
- Empty array returns error or undefined statistics
- Array exceeds bounded size limit returning a payload-too-large error
- Malformed JSON body returns 400 bad request
- Infinite or NaN values in array may cause computation failure

## How this service works

M2M Trust deterministic analysis tool: Deterministic descriptive statistics for bounded finite numeric arrays.

## Output

Returns deterministic descriptive statistics for the submitted numeric array, including measures such as count, mean, median, mode, variance, standard deviation, min, max, and percentiles — all computed deterministically with no randomness or ML inference.

## Example request

```json
{
 "samples": [
  12.4,
  15.1,
  9.8,
  14.2,
  11.7,
  13.5,
  10.9,
  16,
  12.8,
  14.5
 ],
 "statistics": [
  "mean",
  "median",
  "std_dev",
  "min",
  "max",
  "variance"
 ]
}
```

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "context": {
   "type": "string",
   "description": "Short domain context for interpretation."
  },
  "samples": {
   "type": "array",
   "items": {
    "type": "number"
   },
   "maxItems": 10000,
   "minItems": 1,
   "description": "Finite numeric sample values; NaN, infinities and non-numeric strings are rejected."
  },
  "percentiles": {
   "type": "array",
   "items": {
    "type": "number",
    "maximum": 100,
    "minimum": 0
   },
   "maxItems": 25,
   "description": "Optional percentile requests from 0 to 100 inclusive."
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/energybilltoolkit-co-uk-bb31e54b/health.json
- [Zero catalog index](https://www.zero.xyz/llms.txt)
- [Other services from energybilltoolkit.co.uk](https://www.zero.xyz/host/energybilltoolkit.co.uk/llms.txt)