Automatically evaluate and compare multiple AI models or agents without pre-existing test data. Generates test queries from a task description, collects responses from all target endpoints, auto-generates evaluation rubrics, runs pairwise comparisons via a judge model, and produces win-rate rankings with reports and charts. Supports checkpoint resume, incremental endpoint addition, and judge model hot-swap. Use when the user asks to compare, benchmark, or rank multiple models or agents on a custom task, or run an arena-style evaluation.
How to install auto-arena?
agentscope-ai/openjudge/auto-arena
$npx -y skills add agentscope-ai/openjudge --skill auto-arenaInstalls into the current project.
›Prefer a prompt? Paste this to your agent
Run `npx skills use "https://github.com/agentscope-ai/openjudge" --skill "agentscope-ai/openjudge/auto-arena"` and follow the generated skill instructions now. Read its complete output, redirecting it to a temporary file first if necessary. Resolve relative paths from the supporting-files directory it provides.
Use the skills in "https://github.com/agentscope-ai/openjudge" that are relevant to the current task. Run `npx skills add "https://github.com/agentscope-ai/openjudge"` and select the relevant skills, then follow their instructions.
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