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Ollama

Listed
balloob·vlatest·ai-ml

Ollama simplifies running large language models locally, enabling experimentation and private use without relying on external APIs.

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 balloob/llm-skills --skill ollama -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

balloob

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 2 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 2 hosts that are neither well-known infrastructure nor declared in the skill's frontmatter: 192.168.1.100, ollama.com.

    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

    ollama.comundeclared192.168.1.100undeclared

    What it found (3 of 4)

    • ollama/SKILL.md:52contacts ollama.com
      curl -fsSL https://ollama.com/install.sh | sh
    • ollama/SKILL.md:96contacts 192.168.1.100
      python scripts/validate_connection.py http://192.168.1.100:11434
    • ollama/references/nodejs_api.md:70contacts 192.168.1.100
      // const ollama = new Ollama({ host: 'http://192.168.1.100:11434' });

  • No pipe-to-shell installers: failed

    Runs code fetched at install time in 1 place.

    No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.

    What it found

    • ollama/SKILL.md:52remote script piped into a shell
      curl -fsSL https://ollama.com/install.sh | sh

  • 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.

  • Pinned to a commit: passed

    Scanned balloob/llm-skills at a83dfdbf28.

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

Commit
a83dfdbf28
Manifest
ollama/SKILL.md
Scanned
3 files, 1,308 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 ollama skill allows your AI agent to run large language models locally. It simplifies the process of downloading, managing, and executing LLMs directly on your machine, eliminating reliance on external APIs. This enables offline operation and greater control over model versions and data privacy.

When to use it

  • Offline Reasoning: When internet connectivity is unreliable or unavailable, use ollama to perform tasks requiring language processing.
  • Data Privacy: For sensitive information that cannot be sent to external servers, run LLMs locally with ollama.
  • Experimentation: Quickly test and compare different LLM models without incurring API costs.
  • Custom Model Usage: Utilize specific or custom-trained language models not readily available through standard APIs.

Key capabilities

  • Local LLM execution
  • Model downloading and management
  • Offline operation
  • Support for various model formats

Example prompts

  • "Run the llama2 model and summarize this article."
  • "Download and use the mistral-7b model to answer questions about my documents."
  • “Generate a creative story using the codellama model.”

Tips & gotchas

  • Ensure you have sufficient system resources (RAM, disk space) to accommodate the selected LLM.
  • The first time you use a model, ollama will download it – this can take some time depending on the model size and your internet connection speed.