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Multi Llm Advisor

Checked
svenja-dev·vlatest·ai-ml

Provides LLMs guidance and assistance for building AI and machine learning applications.

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 svenja-dev/claude-code-skills --skill multi-llm-advisor -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

svenja-dev

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 svenja-dev/claude-code-skills at 4771c8e872.

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

Commit
4771c8e872
Manifest
skills/multi-llm-advisor/SKILL.md
Scanned
1 file, 130 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 multi-LLM Advisor skill allows an AI agent to leverage multiple Large Language Models (LLMs) for more comprehensive and nuanced responses. It can compare outputs from different models, synthesize information, and provide a consolidated answer or recommendation based on the strengths of each LLM. This results in higher quality and more reliable outcomes than relying on a single model.

When to use it

  • Complex Problem Solving: When facing a multifaceted question requiring diverse perspectives or specialized knowledge that might be better handled by different models.
  • Fact Verification & Bias Mitigation: To cross-reference information from multiple LLMs, reducing the risk of inaccurate or biased responses.
  • Creative Content Generation: To combine creative writing styles or generate more varied and engaging content by drawing on different LLM capabilities.
  • Decision Support: When needing a balanced recommendation considering various factors and potential outcomes that can be assessed using different models.

Key capabilities

  • Comparison of LLM outputs
  • Synthesis of information from multiple sources
  • Consolidated response generation
  • Leveraging strengths of individual LLMs

Example prompts

  • "Compare the responses from GPT-4, Claude 3 Opus and Gemini 1.5 Pro regarding the ethical implications of AI art generation."
  • “Summarize the key arguments for and against universal basic income, using insights from both a legal LLM and an economic LLM.”
  • "Generate three different marketing slogans for a new coffee shop, one each in the style of Hemingway, Shakespeare, and a modern social media influencer. Then combine them into a single, compelling message."

Tips & gotchas

  • The effectiveness of this skill depends on having access to multiple LLMs through appropriate APIs or integrations.
  • Consider the cost implications of querying multiple models – it can be significantly higher than using just one.