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Ollama Stack

Listed
bagelhole·vlatest·ai-ml·MIT

Ollama Stack streamlines local LLM deployment & management, simplifying setup and enabling efficient experimentation for developers.

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 bagelhole/devops-security-agent-skills --skill ollama-stack -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

bagelhole

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 1 host that is neither well-known infrastructure nor declared in the skill's frontmatter: 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.comundeclared127.0.0.1local

    What it found

    • infrastructure/local-ai/ollama-stack/SKILL.md:34contacts ollama.com
      curl -fsSL https://ollama.com/install.sh | sh

  • No pipe-to-shell installers: failed

    Runs code fetched at install time in 2 places.

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

    What it found

    • infrastructure/local-ai/ollama-stack/SKILL.md:34remote script piped into a shell
      curl -fsSL https://ollama.com/install.sh | sh
    • infrastructure/local-ai/ollama-stack/SKILL.md:286remote script piped into an interpreter
      curl -s http://localhost:11434/api/ps | python3 -m json.tool

  • 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 bagelhole/devops-security-agent-skills at 0365f57a07.

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

Commit
0365f57a07
Manifest
infrastructure/local-ai/ollama-stack/SKILL.md
Scanned
1 file, 336 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-stack skill allows AI agents to run and interact with large language models (LLMs) locally using the Ollama framework. This enables offline operation, increased privacy through local data processing, and potentially faster response times compared to cloud-based LLM APIs. It simplifies the process of downloading, managing, and executing various open-source LLMs directly within an agent's environment.

When to use it

  • Offline environments: When internet connectivity is unreliable or unavailable, this skill allows agents to continue functioning with LLM capabilities.
  • Privacy-sensitive tasks: Processing sensitive data locally avoids sending information to external servers.
  • Rapid prototyping & experimentation: Quickly test and deploy different LLMs without complex setup procedures.
  • Resource constraints: Run smaller LLMs on devices with limited computational resources compared to cloud solutions.

Key capabilities

  • LLM downloading via Ollama
  • Local LLM execution
  • Simplified model management
  • Offline operation

Example prompts

  • "Download and run the 'llama2' model using ollama-stack."
  • "Summarize this document locally using the 'mistral' model through ollama-stack."
  • "List all available models managed by ollama-stack."

Tips & gotchas

  • Ensure Ollama is installed and configured correctly before utilizing this skill.
  • The performance of LLMs will depend on your local hardware capabilities.