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Exploratory Data Analysis

Checked
braselog·vlatest·data

Helps with data, analysis as part of data analysis and analytics workflows 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 braselog/researchassistant --skill exploratory-data-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

braselog

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 braselog/researchassistant at 6e1e60a1d7.

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

Commit
6e1e60a1d7
Manifest
.github/skills/exploratory-data-analysis/SKILL.md
Scanned
1 file, 21 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

This skill performs exploratory data analysis (EDA) on datasets provided as CSV files. It automatically identifies and summarizes key statistical properties, including distributions, correlations, and potential outliers. The goal is to provide initial insights into the dataset's structure and characteristics before further modeling or analysis.

When to use it

  • You have a new dataset and want a quick overview of its contents.
  • Before building machine learning models, you need to understand data distributions and relationships.
  • To identify potential data quality issues like missing values or outliers.
  • When exploring the feasibility of using a dataset for a specific project.

Key capabilities

  • CSV file input
  • Statistical summary generation (e.g., mean, median, standard deviation)
  • Distribution visualization
  • Correlation analysis
  • Outlier detection

Example prompts

  • "Analyze this CSV file and tell me about the data."
  • "Perform exploratory data analysis on 'customer_data.csv' and highlight any potential outliers."
  • "What are the correlations between different columns in 'sales_data.csv'?"

Tips & gotchas

  • The skill requires a valid CSV file as input. Ensure the file is properly formatted before providing it to the agent.