القائمة
Run multi-model battle with rotating writer and judge models via OpenAI-compatible endpoints. Use when users ask to battle or compare models, run multi-LLM critique, or iteratively improve an answer across models.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
修复, 等待 AI 代码审查评论并处理它们并不断迭代直到可以合并
Combine recursive outer-loop refinement with multi-model arena generation each round. Use when users request recursive arena, multi-LLM consensus with iterative refinement, or recursive plus model-battle workflows.
Recursive master-orchestration for complex multi-step tasks. Decompose work, delegate execution to sub-agents, and iterate until verified. Use when users request recursive reasoning, multi-pass refinement, or explicit plan-execute-verify loops.
This skill should be used when the user asks to "analyze a large log", "summarize a big file", "read the whole repository", "process long tool output", "avoid context window overflow", "use sub-agents for preprocessing", "add evidence with line numbers", "verify claims with locators", or mentions "TaskSpec", "SubResult", "Evidence Contract", "Context Firewall", "Map-Reduce", "FileWorker", "Aggregator", "Critic".
| name | multi-model |
| description | Run multi-model battle with rotating writer and judge models via OpenAI-compatible endpoints. Use when users ask to battle or compare models, run multi-LLM critique, or iteratively improve an answer across models. |
| allowed-tools | Read, Bash(python:*) |
Use the bundled runner:
python3 "${CLAUDE_PLUGIN_ROOT}/skills/multi-model/scripts/multi_model.py".
The script searches upward from the current working directory for .env.
Required variables:
ARENA_MODELSARENA_OPENAI_BASE_URL (single endpoint) or ARENA_PROVIDER_<NAME>_BASE_URL (multi-provider)ARENA_OPENAI_API_KEY, ARENA_PROVIDER_<NAME>_API_KEYSingle-endpoint example:
ARENA_MODELS=qwen3:8b,deepseek-r1:14b
python3 "${CLAUDE_PLUGIN_ROOT}/skills/multi-model/scripts/multi_model.py" \
--prompt "<task>" --iters 5 --max-judges 3 --json
Useful flags: --out, --temperature, --max-tokens, --timeout.
--json..env.Model 0, Model 1, ...).