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Building Dashboards

Official
axiomhq·vlatest·data·MIT

AxiomHQ's building-dashboards skill generates interactive data visualizations from your information sources to track key metrics.

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 axiom-building-dashboards, 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 axiomhq/skills --skill axiom-building-dashboards -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

axiomhq

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 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: api.axiom.co.

    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

    api.axiom.coundeclared

    What it found

    • skills/building-dashboards/reference/chart-config.md:117contacts api.axiom.co
      curl -X POST 'https://api.axiom.co/v2/annotations' \

  • 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 axiomhq/skills at a3ea3f29a0.

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

Commit
a3ea3f29a0
Manifest
skills/building-dashboards/SKILL.md
Scanned
21 files, 4,054 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 enables AI agents to construct interactive dashboards, allowing them to visualize complex data sets and monitor system metrics dynamically. It transforms raw information into actionable insights through customizable graphical interfaces tailored to specific user needs.

When to use it

  • Real-time Monitoring: Track live server health metrics or application performance indicators during deployment cycles.
  • Executive Reporting: Generate visual summaries of quarterly sales data or project timelines for stakeholder reviews.
  • Operational Analysis: Create interactive charts to identify trends in customer support tickets or inventory levels.
  • Data Exploration: Allow users to drill down into specific dataset segments by configuring filterable dashboard views.

Key capabilities

  • Visualizes complex datasets into readable graphical formats
  • Enables dynamic interaction with data points for deeper analysis
  • Supports the creation of custom layouts tailored to specific monitoring goals
  • Facilitates real-time updates as underlying data sources change

Example prompts

  • "Build a dashboard showing our server CPU usage and memory consumption over the last 24 hours."
  • "Create an interactive view of our Q3 sales figures broken down by region and product line."
  • "Generate a monitoring panel that tracks daily active users and error rates for our mobile app."

Tips & gotchas

Ensure your AI agent has access to the necessary data sources or APIs before attempting to build a dashboard, as visualization requires underlying data streams. For best results, specify the desired chart types (e.g., line graphs, bar charts) and time ranges explicitly in your request to avoid generic outputs.