Mean, median, quantiles, and linear regression inside a Code node or CodeAct action, with simple-statistics running in the guest
Scanned 9/1/2026
Install to Claude Code
npx -y skills add nodetool-ai/nodetool --skill sandbox-stats --agent claude-codeInstalls into .claude/skills of the current project.
Are you the author of Sandbox Stats?
Add the live security badge to your README — it updates automatically with every re-scan.
[](https://www.skillsdirectory.com/skills/nodetool-ai-sandbox-stats)More formats (shields.io, HTML) on the badges page.
---
name: sandbox-stats
description: Mean, median, quantiles, and linear regression inside a Code node or CodeAct action, with simple-statistics running in the guest
---
# Statistics in the sandbox
Specifier: `@nodetool-ai/sandbox-stats`. One module, simple-statistics.
Import it at the top of the body.
## Column summaries
```js
import { mean, median, standardDeviation, quantile } from "@nodetool-ai/sandbox-stats";
const xs = inputs.values;
return {
mean: mean(xs),
median: median(xs),
sd: standardDeviation(xs),
p90: quantile(xs, 0.9)
};
```
## Linear regression
```js
import { linearRegression, linearRegressionLine } from "@nodetool-ai/sandbox-stats";
const fit = linearRegression(inputs.points);
const line = linearRegressionLine(fit);
return { m: fit.m, b: fit.b, at10: line(10) };
```
`inputs.points` is `[[x, y], ...]`.
## Gotchas
- **Named imports.** Import only the functions you use.
- **Empty arrays throw.** Guard before `mean([])`.
- **This is not TFJS.** Classification and embeddings stay on
`@nodetool-ai/sandbox-tfjs`.
Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.
No comments yet. Be the first to comment!
Adversarial multi-agent planning skill. Self-orchestrates 5 hostile category members (unspecified-low, unspecified-high, deep, ultrabrain, artistry) via team-mode for ruthless cross-critique debate, distills only the defensible insights, then MANDATORILY hands the distilled insight bundle to the `plan` agent for executable plan formalization. Use when planning needs maximum rigor and surfacing of weak assumptions, blind spots, and over-engineering. Triggers: 'hyperplan', 'hpp', '/hyperplan', ...