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Correlation Analysis

Checked
aj-geddes·vlatest·data·MIT

Identifies hidden relationships between datasets to reveal patterns and inform strategic decision-making.

Repository

Install on your platform

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

Installs under a different name. Its SKILL.md names it Correlation Analysis, not the name it is listed under, so the command below uses that name.
  1. 1

    Run this in your project

    terminal
    $ npx skills add aj-geddes/useful-ai-prompts --skill "Correlation 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

aj-geddes

Taken from the source listing. We haven't verified who controls this account.

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 aj-geddes/useful-ai-prompts at 3f5182cfd7.

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

Commit
3f5182cfd7
Manifest
skills/correlation-analysis/SKILL.md
Scanned
3 files, 265 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

The Correlation Analysis skill enables AI agents to identify and quantify relationships between variables within datasets. It processes numerical inputs to calculate correlation coefficients, revealing how changes in one metric influence another. This capability transforms raw data into actionable insights by highlighting patterns that might otherwise remain hidden.

When to use it

  • Analyzing sales data to determine if marketing spend directly impacts revenue growth.
  • Evaluating weather conditions against crop yield statistics for agricultural planning.
  • Investigating the relationship between study hours and exam scores in educational research.
  • Assessing how temperature fluctuations correlate with energy consumption levels.

Key capabilities

  • Calculates Pearson correlation coefficients to measure linear relationships.
  • Processes structured numerical datasets provided by the user.
  • Identifies positive, negative, or neutral associations between paired variables.
  • Outputs clear interpretations of statistical strength and direction.

Example prompts

  • "Analyze this dataset of monthly temperatures and ice cream sales to find the correlation coefficient."
  • "Calculate the relationship between hours spent studying and final exam grades provided in the CSV below."
  • "Determine if there is a strong positive or negative correlation between stock market indices and interest rates."

Tips & gotchas

Ensure your input data is clean, numerical, and properly paired before analysis, as missing values can skew results. This skill focuses on linear relationships; it may not detect complex non-linear patterns without additional configuration.