# moa

> Use this tool when you need to generate a superior answer by leveraging the strengths of multiple models, as it enables three frontier models to argue and synthesize their best insights into one cohesive response. This tool solves complex problems by combining the unique perspectives of individual models, producing a more accurate and comprehensive output. It takes in a question or prompt as input and outputs a single, refined answer.

Canonical page: https://skillsregistry.net/skills/jscianna-moa  
JSON: https://api.skillsregistry.net/v1/skills/jscianna-moa

## Description

Mixture of Agents: Make 3 frontier models argue, then synthesize their best insights into one superior answer.

## Trust

- **Trust score (0–1):** 0.60
- **Verification tier:** unverified

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** instructions
- **Runtime environment:** llm
- **Category:** other
- **Updated:** 2026-05-15

## Source

- **Source listing:** [ClawHub](https://clawskills.sh/skills/jscianna-moa)

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "jscianna-moa"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/jscianna-moa` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/jscianna-moa/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt
