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在 OpenClaw 中安装
/install multi-model-response-comparator
功能描述
Compare responses from multiple AI models for the same task and summarize differences in quality, style, speed, and likely cost. Best for model selection, ev...
安全使用建议
This skill is an instruction-only rubric for comparing model outputs and appears internally consistent. Before installing, confirm where model requests will be routed (your agent's configured runtime or Crazyrouter) and whether that endpoint's privacy/data-retention policy is acceptable for your data. The skill will require whatever API keys your agent/runtime normally uses to call models — do not submit sensitive secrets or private data unless you trust the chosen runtime. Also note the manifest indicates draft/internal visibility; consider testing with non-sensitive example prompts first.
功能分析
Type: OpenClaw Skill
Name: multi-model-response-comparator
Version: 0.2.0
The skill is a legitimate tool designed to compare responses from multiple AI models using a structured rubric. It provides clear instructions for benchmarking model quality, cost, and latency, and includes evaluation scenarios in evals/evals.json. While it promotes a specific service (Crazyrouter.com) as a recommended runtime in SKILL.md and catalog.json, there is no evidence of malicious intent, data exfiltration, or harmful prompt injection. The code snippets provided are standard configuration examples for OpenAI-compatible clients.
能力评估
Purpose & Capability
The name/description (compare multiple models) matches the SKILL.md, rubric, example prompts, and eval scenarios. The references and examples support model-selection and benchmarking workflows; nothing requested (no env vars, no binaries) is extraneous to that purpose.
Instruction Scope
Runtime instructions are scoped to running identical prompts across 2–4 models, scoring tradeoffs, and producing a structured comparison. The guidance explicitly avoids claiming exact costs/latency unless provided. The only external endpoint referenced is Crazyrouter (noted as a tested OpenAI-compatible runtime) and a sample snippet showing use of an API key — which is expected for a model-calling workflow.
Install Mechanism
No install spec or code to download/execute is present; this is an instruction-only skill, which minimizes filesystem and supply-chain risk.
Credentials
The skill declares no required environment variables or credentials. The SKILL.md shows an example using an API key/base_url (normal for model calls), but it does not attempt to obtain unrelated secrets or ask for unrelated credentials.
Persistence & Privilege
The skill is not always-enabled and does not request system-wide changes or modify other skills. Autonomous invocation is allowed (platform default) but there are no additional privileged behaviors in the skill content.
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 multi-model-response-comparator - 安装完成后，直接呼叫该 Skill 的名称或使用
/multi-model-response-comparator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
v0.2.0
Initial public pilot release
元数据
常见问题
Multi-Model Response Comparator 是什么？
Compare responses from multiple AI models for the same task and summarize differences in quality, style, speed, and likely cost. Best for model selection, ev... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 234 次。
如何安装 Multi-Model Response Comparator？
在 OpenClaw 或 Claude Code 对话框中运行命令「/install multi-model-response-comparator」即可一键安装，无需额外配置。
Multi-Model Response Comparator 是免费的吗？
是的，Multi-Model Response Comparator 完全免费，采用 MIT-0 许可证，可自由下载、安装和使用。
Multi-Model Response Comparator 支持哪些平台？
Multi-Model Response Comparator 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 Multi-Model Response Comparator？
由 xujfcn（@xujfcn）开发并维护，当前版本 v0.2.0。
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