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Llama Cpp

Checked
tdimino·vlatest·ai-ml·MIT

Llama Cpp translates Python code into optimized C++ for faster execution and reduced memory usage of Llama models.

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 tdimino/claude-code-minoan --skill llama-cpp -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

tdimino

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

    Only contacts known or declared hosts: github.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

    github.comsource host

  • 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 tdimino/claude-code-minoan at 9f4a84393d.

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

Commit
9f4a84393d
Manifest
skills/integration-automation/llama-cpp/SKILL.md
Scanned
12 files, 1,384 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.
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About this skill

What it does

The tdimino-llama-cpp skill allows AI agents to leverage Llama.cpp, a C++ port of the LLaMA language model. This enables efficient local inference and deployment of large language models on various hardware configurations. It provides capabilities for running LLaMA models directly within an agent's environment, reducing reliance on external APIs.

When to use it

  • Local LLM Inference: When you need to run a LLaMA model without relying on cloud-based API calls due to privacy or cost concerns.
  • Resource-Constrained Environments: Ideal for deploying AI agents on devices with limited resources, such as edge computing setups or embedded systems.
  • Offline Operation: Enables AI agent functionality even when internet connectivity is unavailable.
  • Custom Model Integration: Allows integration of specific LLaMA model variants and fine-tunes not readily available through standard APIs.

Key capabilities

  • Local LLaMA inference using C++ implementation
  • Support for various hardware configurations
  • Efficient resource utilization
  • Offline operation capability

Example prompts

  • "Run the Llama model to summarize this document."
  • "Generate a creative story using the Llama model, focusing on [topic]."
  • "Translate this text into French using the local LLaMA model."

Tips & gotchas

  • Requires a compatible LLaMA model file (GGUF format) to be present.
  • Performance is dependent on available system resources (CPU/GPU).