experiment-queuelisted

> **本整合包适配**：涉及 `mcp__codex__codex` / `mcp__manual_review__*` 的评审调用，按 [`shared-references/reviewer-adapter.md`](../shared-references/reviewer-adapter.md) 的后端优先级适配（MCP → codex/gemini CLI → Devin 子会话 → 新对话人工中转 → 同模型降级并标注）。引用 `tools/experiment_queue/*` 的脚本位于本包 `tools/` 目录。未收录的 skill 引用见 `shared-references/pack-mapping.md`。 # Experiment Queue > ⏱ **External cadence: visibility only.** This skill already runs its own > detached server-side scheduler (60s poll + `depends_on` + wave transitions). > Use its status output for overnight visibility (N done / N running / N > pending); do **not** wrap it in a second `/loop` / `CronCreate` poll — that > duplicates the scheduler on an uncoordinated clock and races the > wave-transition logic it was built to prevent. See > [`shared-references/external-cadence.md`](../shared-references/external-cadence.md) > ("don't duplicate an existing scheduler"). Orchestrate large batches of ML experiments on SSH remote GPU servers with proper state tracking, OOM retry, stale cleanup, and wave transitions. ## When to Use This Skill Use when `/run-experiment` is insufficient: - **≥10 jobs** that need batching across GPUs - **Multi-seed sweeps** (e.g., 21 seeds × 12 cells) - **Wave transitions** (run wave 1, wait, run wave 2, wait, run wave 3...) - **Teacher+student chains** (train teacher then distill; auto-trigger student after teacher done) - **OOM-prone configs** where you need to retry with different GPU or wait - **Mixed seed grids** where faile