x402-toolbox Descriptive Statistics

x402

x402-toolbox Descriptive Statistics is a paid API for AI agents from x402-toolbox.shablony-pro.workers.dev, paid per call via x402, $0.002/call, status unknown (last checked 2026-09-29).

Computes descriptive statistics (mean, median, variance, etc.) for a given dataset via a pay-per-call x402 API requiring no signup or API key.

Price / call$0.002

Seller volume →—

Success—

StatusUnknown

How this service works

309 deterministic pay-per-call tools for AI agents over x402 (USDC, Base). No signup, no API key: the payment is the identity.

Output

Returns a JSON object with computed descriptive statistics for the provided dataset, including measures of central tendency (mean, median, mode), dispersion (variance, standard deviation, range), and shape (skewness, kurtosis), along with confirmation fields ok:true and paid:true.

Example use cases

Summarize student test score distribution

“I have these exam scores from my class: [55, 72, 68, 90, 83, 45, 77, 88, 61, 74] — can you calculate the descriptive statistics so I can see the average, spread, and any skew?”

Analyze sales data spread

“Here are last month's daily sales figures: [1200, 980, 1450, 870, 1100, 1350, 990] — give me the full descriptive stats including mean, median, variance, and standard deviation.”

Check sensor reading variability

“I have these temperature sensor readings in Celsius: [22.1, 21.8, 23.4, 22.9, 21.5, 23.1, 22.6] — compute descriptive statistics so I can see how stable the readings are.”

Technical details

Endpoint

GEThttps://x402-toolbox.shablony-pro.workers.dev/math/statistics-descriptive?utm_source=zero.xyz

When to prefer

Choose this endpoint when you need quick, pay-per-call descriptive statistics computation with no API key or account setup required — ideal for AI agents operating autonomously with a USDC wallet on Base. Best when you want a deterministic, cheap ($0.001) stats computation without integrating a full data science library or managing credentials.

Side effects

Missing or malformed schema/dataset input returns an error
Non-numeric data in dataset causes computation failure
Payment failure via x402 prevents access to results
Empty dataset returns error or undefined statistics
Malformed JSON schema string causes parsing error

Input

Schema · Request body

Field	Type	Description
schema	string

Output

Schema · Response

{
  "type": "json",
  "example": {
    "ok": true,
    "paid": true
  }
}

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