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OpenVerbs Statistics Summary
x402
OpenVerbs Statistics Summary is a paid API for AI agents from stats.openverbs.com, paid per call via x402, $0.004/call, status unknown (last checked 2026-09-14).
Computes descriptive statistics (mean, variance, standard deviation, etc.) for a numeric array using population or sample formulas
Price / call$0.004
Success—
StatusUnknown
How this service works
Full descriptive summary of a numeric sample: count, sum, min/max/range, mean, median, mode(s), variance, standard deviation and the quartiles (q1/q3/iqr). Set sample=true for the sample variance/stdev (÷ n-1) instead of the population form (÷ n).
Output
A statistical summary object containing computed metrics for the provided numeric array, including mean, count, variance, and standard deviation. Results reflect either population (÷n) or sample (÷n-1) formulas depending on the 'sample' flag.
Example use cases
Analyzing student test score spread
“I have a list of student exam scores: [55, 62, 70, 74, 81, 85, 88, 91, 95, 100]. Can you compute the sample mean and standard deviation for me so I can see how spread out the grades are?”
Quality control variance check
“We measured the diameter of 20 widgets from the production line: [10.01, 9.98, 10.02, 10.00, 9.97, 10.03, 10.01, 9.99, 10.00, 10.02, 9.98, 10.01, 10.00, 9.99, 10.03, 10.01, 10.02, 9.97, 10.00, 10.01]. Run a population statistics summary on these numbers so we can check our process consistency.”
Financial return distribution summary
“Here are 12 monthly portfolio returns as percentages: [2.1, -0.8, 3.4, 1.2, -1.5, 4.0, 0.5, 2.7, -0.3, 1.8, 3.1, 0.9]. Give me the sample mean and standard deviation so I can evaluate the volatility.”
Technical details
Endpoint
POSThttps://stats.openverbs.com/v1/summaryWhen to prefer
Choose this endpoint when you need a quick, pay-per-use statistical summary of a numeric dataset without setting up your own computation infrastructure. Ideal for agents that need on-demand descriptive statistics for up to 100,000 numbers with explicit control over population vs. sample formulas. Prefer this over general-purpose code execution when you want a single deterministic API call rather than running custom scripts.
Side effects
- Empty data array (minItems:1 violated) returns validation error
- Array exceeds 100,000 items (maxItems:100000 violated) returns rejection
- Non-numeric values in the array cause schema validation failure
- Missing required 'data' property returns 400-level error
- Insufficient USDC balance or x402 payment failure prevents execution
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| inputrequired | object |
Tags
x402
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