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Install in OpenClaw
/install multi-model-response-comparator
Description
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...
Usage Guidance
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.
Capability Analysis
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.
Capability Assessment
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.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install multi-model-response-comparator - After installation, invoke the skill by name or use
/multi-model-response-comparator - Provide required inputs per the skill's parameter spec and get structured output
Version History
v0.2.0
Initial public pilot release
Metadata
Frequently Asked Questions
What is Multi-Model Response Comparator?
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... It is an AI Agent Skill for Claude Code / OpenClaw, with 234 downloads so far.
How do I install Multi-Model Response Comparator?
Run "/install multi-model-response-comparator" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Multi-Model Response Comparator free?
Yes, Multi-Model Response Comparator is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does Multi-Model Response Comparator support?
Multi-Model Response Comparator is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created Multi-Model Response Comparator?
It is built and maintained by xujfcn (@xujfcn); the current version is v0.2.0.
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