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Data Exploration Visualization

Listed
liangdabiao·vlatest·data

Visualize datasets with interactive charts and graphs to uncover patterns and insights quickly.

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 liangdabiao/claude-data-analysis-ultra-main --skill data-exploration-visualization -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

liangdabiao

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 failed 1 of 6 checks. A failure is not proof of bad intent; it means something in the code needs a human to look at it before you run it.

  • No undeclared network calls: failed

    Contacts 1 host that is neither well-known infrastructure nor declared in the skill's frontmatter: cdn.plot.ly.

    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.

    Hosts contacted

    cdn.plot.lyundeclared

    What it found

    • .claude/skills/data-exploration-visualization/examples/report_generator.py:86contacts cdn.plot.ly
      <script src="https://cdn.plot.ly/plotly-latest.min.js"></script>

  • 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 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 liangdabiao/claude-data-analysis-ultra-main at 6b52856848.

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

Commit
6b52856848
Manifest
.claude/skills/data-exploration-visualization/SKILL.md
Scanned
13 files, 7,147 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 data-exploration-visualization skill enables AI agents to perform deep statistical analysis, generate interactive charts, and produce comprehensive data reports directly from raw datasets. It transforms complex numerical inputs into clear visual insights without requiring manual coding or external tools.

When to use it

  • Analyzing sales trends to identify seasonal patterns and forecast future demand.
  • Visualizing customer demographics to segment audiences for targeted marketing campaigns.
  • Generating interactive dashboards that allow stakeholders to drill down into specific data points.
  • Creating summary reports that highlight key performance indicators (KPIs) with supporting charts.

Key capabilities

  • Performs advanced statistical analysis on uploaded datasets.
  • Generates a wide variety of interactive visualizations and charts.
  • Produces structured, comprehensive data reports summarizing findings.
  • Handles raw data ingestion and preprocessing automatically.

Example prompts

  • "Analyze this CSV file containing monthly sales figures and create a line chart showing year-over-year growth."
  • "Generate an interactive scatter plot to visualize the correlation between customer age and purchase frequency."
  • "Produce a summary report with key statistics and bar charts comparing product performance across different regions."

Tips & gotchas

Ensure your data files are in standard formats like CSV, JSON, or Excel before uploading for optimal parsing. For best results, specify the desired chart type (e.g., line, bar, scatter) explicitly when requesting visualizations to match your analytical needs.