voices

Query multiple LLMs in parallel via an OpenAI-compatible chat API.

6|1|Updated May 30, 2026
One-click install
npx skills add https://github.com/Wondermonger-daydreaming/claude-skills-library --skill voices
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: voices
Source: https://github.com/Wondermonger-daydreaming/claude-skills-library/tree/main/skills/voices
Command: npx skills add https://github.com/Wondermonger-daydreaming/claude-skills-library --skill voices

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

Query multiple LLMs in parallel to surface diverse perspectives and cross-check insights.

Core Features & Use Cases

  • Cross-model dialogue: send a prompt to several hosts and compare their responses side by side.
  • Council diagnostics: quickly identify consensus vs. disagreement across architectures to inform decisions.
  • Open-ended testing: test ideas across model families (OpenAI, Anthropic, DeepSeek, etc.) using a single client.

Quick Start

Run the voices client with a set of models and a prompt to see concurrent responses.

Frequently Asked Questions about voices

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I query multiple LLMs in parallel to compare model responses?

Query multiple LLMs in parallel by sending a prompt to several model hosts concurrently, which surfaces diverse perspectives and cross-checks insights side by side. This concurrent request handling quickly identifies consensus or disagreement across architectures.

What is a council-style LLM comparison and when do I need it?

A council-style LLM comparison queries multiple model architectures simultaneously to identify consensus versus disagreement. You need this cross-model dialogue when making decisions that benefit from diverse AI perspectives and cross-checked insights.

Can I use a single API client to test prompts across OpenAI and Anthropic model families?

Yes, you can test ideas across model families like OpenAI, Anthropic, and DeepSeek using a single vendor-agnostic client. It satisfies an OpenAI-compatible chat API workflow to manage these cross-model dialogues.

How do I manage API keys for concurrent requests to different LLM hosts?

Manage API keys for concurrent requests through environment-based API key management. This setup securely handles authentication for multiple hosts when running cross-model dialogues and council-style comparisons.

Does this parallel LLM querying approach support saving the chat exchanges?

Yes, this parallel LLM querying approach supports optional saving of exchanges. While handling concurrent requests to surface diverse perspectives, you can save the cross-model dialogues for later analysis.