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24K Labs Stats Toolkit
x402
24K Labs Stats Toolkit is a paid API for AI agents from api.24klabs.ai, paid per call via x402, $0.003/call, status unknown (last checked 2026-09-15).
Computes descriptive statistics (mean, median, mode, stddev, variance, quartiles, percentiles, z-scores, IQR), detects outliers, and optionally runs Pearson correlation and linear regression against a second data series.
Price / call$0.003
Success—
StatusUnknown
How this service works
One call for mean/median/mode, stddev/variance, quartiles/percentiles, z-scores, IQR and z-score outlier flags; optional Pearson correlation and linear regression against a second series.
Output
Returns a JSON object containing central tendency metrics (mean, median, mode), dispersion metrics (stddev, variance, IQR), quartile and percentile breakdowns, z-scores for each data point, IQR-based and z-score-based outlier flags per element, and optionally Pearson correlation coefficient and linear regression slope/intercept when a second series is provided.
Example use cases
Exploratory data analysis on sales figures
“I have monthly sales numbers for the past year: [4200, 3800, 5100, 4750, 6200, 5900, 4100, 3600, 7000, 5500, 4800, 6100]. Can you give me mean, median, stddev, quartiles, and flag any outlier months using z-scores?”
Correlation between ad spend and revenue
“I want to know how strongly correlated my ad spend is with my revenue. Here are the two series — ad spend: [1000, 1500, 2000, 1800, 2500, 3000] and revenue: [8000, 11000, 14500, 13000, 18000, 22000]. Run a Pearson correlation and linear regression on them.”
Detecting anomalies in sensor readings
“I have temperature readings from a sensor over 10 hours: [72, 71, 73, 70, 69, 95, 71, 72, 68, 70]. Can you compute the IQR and z-scores and tell me which readings are statistical outliers?”
Technical details
Endpoint
POSThttps://api.24klabs.ai/api/v1/stats-toolkitWhen to prefer
Choose this endpoint when you need a comprehensive, single-call statistical summary covering both descriptive stats and inferential metrics (correlation, regression) without setting up a local computation environment. Ideal for agents operating in lightweight or serverless contexts where importing a stats library is impractical. Prefer this over general-purpose code execution when you need a fast, deterministic, pay-per-call stats primitive with no setup overhead.
Side effects
- Non-numeric values in the input array return a 400 validation error
- Empty or single-element arrays may produce undefined results for stddev/variance
- Mismatched lengths between the two series for correlation/regression return an error
- Extremely large arrays may approach timeout limits
- Missing required array parameter returns a 400 error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| data | array |
Output
Schema · Response
{
"type": "json",
"example": {
"mean": 5,
"stdev": 2,
"median": 4.5,
"outliers": []
}
}Tags
x402
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