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System Info

Checked
agno-agi·vlatest·other·Apache-2.0

This skill provides instant system details (OS, version, specs) for troubleshooting and understanding your environment 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 agno-agi/agno --skill system-info -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

agno-agi

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 agno-agi/agno at 8c3d8ec52b.

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

Commit
8c3d8ec52b
Manifest
cookbook/05_agent_os/23_skills/sample_skills/system-info/SKILL.md
Scanned
3 files, 157 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 system-info skill provides access to information about the underlying system running the AI agent. It can retrieve details like operating system version, available memory, and CPU usage. This allows agents to adapt their behavior based on resource constraints or report system status.

When to use it

  • Resource Monitoring: An agent needs to understand if it's running on a low-powered device and adjust its processing load accordingly.
  • Troubleshooting: A developer wants to gather diagnostic information about the environment where an AI agent is experiencing issues.
  • System Reporting: An agent is tasked with regularly reporting system health metrics to a central monitoring service.
  • Adaptive Behavior: The agent needs to adjust its actions based on available memory or CPU resources.

Key capabilities

  • Retrieve operating system version.
  • Report available memory.
  • Provide CPU usage statistics.

Example prompts

  • "What is the operating system version?"
  • "How much RAM is available?"
  • "Give me current CPU utilization."

Tips & gotchas

The accuracy of the information returned depends on the permissions granted to the AI agent and the underlying system's reporting capabilities. Results may vary across different operating systems and environments.