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Statistical Analysis

Official
anthropics·vlatest·data·Apache-2.0

Official anthropics skill for analysis — helps with agent workflows.

Repository

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

  1. 1

    Run this in your project

    terminal
    $ npx skills add anthropics/knowledge-work-plugins --skill statistical-analysis -a claude-code

  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

anthropics

Matched to the vendor's own GitHub organisation.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

No human has reviewed this code. The checks below are a static scan of the files at one commit — nobody has run this skill or judged whether it works. A skill runs with whatever access you give your agent, so read the source before you install it.

Automated safety checks

scanned

This skill passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.

  • Declares what it does: passed

    SKILL.md parses and declares a name and a description.

    SKILL.md exists, its frontmatter parses, and it declares a name and a description.

  • No undeclared network calls: passed

    Makes no network calls.

    Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.

  • No obfuscated payloads: passed

    No encoded or obfuscated payloads.

    No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.

  • No credential access: passed

    Reads no keys, tokens, keychains or credential files.

    Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.

  • No pipe-to-shell installers: passed

    No pipe-to-shell or download-and-run installers.

    No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.

  • Pinned to a commit: passed

    Scanned anthropics/knowledge-work-plugins at da38ec1ee8.

    The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.

Commit
da38ec1ee8
Manifest
data/skills/statistical-analysis/SKILL.md
Scanned
1 file, 234 lines
This is a static scan, not a review. It reads the skill's files; it does not run them, and it cannot tell you whether the skill is any good or whether the code does what its description says. A skill runs with whatever access you give your agent.
What each check looks for →

About this skill

What it does

The statistical-analysis skill enables AI agents to perform data analysis tasks such as calculating descriptive statistics, conducting hypothesis tests, and generating visualizations. It supports working with structured datasets and provides insights through summary metrics like mean, median, standard deviation, and correlation coefficients.

When to use it

  • To analyze survey results and identify trends or patterns in responses
  • For quality control processes where data needs to be validated statistically
  • When preparing reports that require visual summaries of numerical data

Key capabilities

  • Descriptive statistics calculation (mean, median, mode)
  • Hypothesis testing (t-tests, chi-square tests)
  • Data visualization (histograms, scatter plots, box plots)
  • Correlation and regression analysis

Example prompts

  • "Calculate the mean and standard deviation of this dataset."
  • "Generate a histogram for the 'age' column in the provided CSV file."
  • "Perform a t-test to compare the average scores between two groups."

Tips & gotchas

Ensure your data is clean and properly formatted before using this skill. Some advanced statistical methods may require additional libraries or preprocessing steps.