model-bakeoff
提供可复现且公平的多模型代码变更竞赛与评估流程
可能需大量计算资源并访问多个模型接口
让多模型在隔离工作树独立完成同一变更并对比评分合并最佳结果
把多款模型各自放到独立的 git worktree 上，让它们针对同一受限改动独立诊断→规划→实施，再在干净服务器上可复现地评分，最后把各模型的最佳改动合并到实验分支。适合想公平比对哪款模型在某类改动上更强并希望把胜出片段拼成最终结果时用。特点是端到端可复现、逐变更评估并能把不同模型的优点 graft 到一个分支。
▸ 展开 SKILL.md 英文原文
Use to run a controlled multi-model bake-off — have N models (e.g. Opus 4.8, Sonnet 5.0, GPT-5.5) each independently diagnose→plan→execute the SAME bounded change in isolated git worktrees, then deterministically re-score their committed code on a fresh server, merge the best-of (grafting distinct wins from the others), and repeat per change. Triggers on "bake-off", "compare models on this task", "which model is best at", "run the same change across models and score them". NOT for choosing a model tier/segment for one agent — use `model-tiering`.
帮我安装这个 skill：https://raw.githubusercontent.com/tyroneross/build-loop/main/skills/model-bakeoff/SKILL.mdcurl -fsSL "https://raw.githubusercontent.com/tyroneross/build-loop/main/skills/model-bakeoff/SKILL.md"# Model Bake-off Harness
Run a fair, evidence-based competition where several models each solve the *same* change end-to-end, then merge the best result. One orchestrator (this session) coordinates; contestants are single agents (measure the model, not a multi-agent loop). Repeat per change, accumulating merges on one experiment branch.
## Roster & dispatch (verified handles)
- Opus 4.8 → `Agent(model: "opus")`; Sonnet 5.0 → `Agent(model: "sonnet")` (`sonnet` = latest, NOT 4.x — older Sonnets have no clean subagent handle).
- GPT-5.5 → Codex MCP `mcp__codex__codex` with `model: "gpt-5.5"`, `config: {model_reasoning_effort: "xhigh", sandbox_workspace_write:{network_access:true}}`, `approval