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Mixture of Agents
作者
John Scianna
· GitHub ↗
· v1.2.0
671
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当前安装
1
版本数
在 OpenClaw 中安装
/install moa
功能描述
Mixture of Agents: Make 3 frontier models argue, then synthesize their best insights into one superior answer. ~$0.03/query.
安全使用建议
This skill is coherent and appears to be what it claims: it needs an OpenRouter API key and will send your prompts (and the model responses) to openrouter.ai. Before installing, (1) confirm you are comfortable sending query text and any sensitive context to OpenRouter, (2) set OPENROUTER_API_KEY only with a key scoped/rotatable for this use, (3) inspect scripts/moa-paid.js (it contains a hard-coded demo prompt and runs immediately if executed), and (4) avoid using this skill with secrets or highly sensitive data because prompts and responses are logged to stdout and sent to external models. Also correct or be aware of the metadata mismatch (some metadata claims no env vars while the manifest and SKILL.md require OPENROUTER_API_KEY). If you need stronger assurance, ask the author for a canonical repository URL and a checksumed release, and test the code in an isolated environment first.
功能分析
Type: OpenClaw Skill
Name: moa
Version: 1.2.0
The OpenClaw skill 'moa' is designed to orchestrate multiple LLM calls via OpenRouter. Its code (scripts/moa.js, scripts/moa-paid.js) and documentation (SKILL.md, manifest.json) consistently show its purpose: taking a user prompt, sending it to various LLMs on openrouter.ai using a user-provided OPENROUTER_API_KEY, and then synthesizing the results. There is no evidence of malicious intent, such as unauthorized data exfiltration, arbitrary code execution, persistence mechanisms, or prompt injection attempts against the OpenClaw agent itself. All network calls are directed to the expected OpenRouter API endpoint, and the API key is used for legitimate authentication.
能力评估
Purpose & Capability
The skill's stated purpose (mixing multiple LLMs and synthesizing their outputs) matches the code and instructions. However, registry metadata at the top of the provided package summary lists no required environment variables, while both SKILL.md and manifest.json require OPENROUTER_API_KEY — an inconsistency that should be corrected but is not evidence of malicious behavior.
Instruction Scope
SKILL.md and the code instruct the agent to call OpenRouter's chat completions API with the user's prompt, aggregate model responses, and synthesize them. The instructions do not ask for unrelated files or credentials. One minor operational note: scripts/moa-paid.js contains a hard-coded example prompt and calls runMoA(prompt) immediately (it runs when executed), which is a benign demo but may be surprising if someone runs that file expecting only a library. The scripts also print prompt snippets and model responses to stdout (logging), which may expose sensitive prompts/responses in logs.
Install Mechanism
There is no install spec (instruction-only skill with Node.js files). No remote downloads or archive extraction are used. The package relies on axios (a normal dependency) and runtime Node >=18 as declared in manifest.json.
Credentials
The only required secret is OPENROUTER_API_KEY, which is appropriate for a skill that calls OpenRouter. The earlier top-level summary incorrectly claimed 'no required env vars', which conflicts with the manifest/SKILL.md — the environment requirement itself is proportionate, but the metadata mismatch should be fixed.
Persistence & Privilege
The skill does not request always: true and does not modify other skills or global agent configuration. It behaves as a normal user-invocable skill that makes outbound API calls; autonomous invocation is allowed by default but not unusually privileged here.
如何使用
- 确保已安装 OpenClaw（本地或 Docker 部署）
- 在对话框中输入安装命令：
/install moa - 安装完成后，直接呼叫该 Skill 的名称或使用
/moa触发 - 根据 Skill 的参数说明提供必要输入，即可获得结构化输出
版本历史
v1.2.0
V1.2: Better docs, API reference, failure modes. Dogfooded with MoA itself.
元数据
常见问题
Mixture of Agents 是什么？
Mixture of Agents: Make 3 frontier models argue, then synthesize their best insights into one superior answer. ~$0.03/query. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 671 次。
如何安装 Mixture of Agents？
在 OpenClaw 或 Claude Code 对话框中运行命令「/install moa」即可一键安装，无需额外配置。
Mixture of Agents 是免费的吗？
是的，Mixture of Agents 完全免费（开源免费），可自由下载、安装和使用。
Mixture of Agents 支持哪些平台？
Mixture of Agents 跨平台运行，可在任意部署了 OpenClaw / Claude Code 的环境中使用（cross-platform）。
谁开发了 Mixture of Agents？
由 John Scianna（@jscianna）开发并维护，当前版本 v1.2.0。
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