experiment-review

name	experiment-review
description	Use when reviewing experiment topics, run.py files, experiment registries, GPU/JAX environment ownership, notebook artifacts, or experiment README/report readiness.

Experiment Review

Tool Commands

Use the command packet before applying this skill's workflow:

python3 tools/agent_tools/skill_tool_commands.py show --skill experiment-review --format text

Execute the required and task-matching conditional commands that the packet prints.

1. Read agents/skills/experiment-review.md.
2. Review from the registered experiment entry before reading implementation detail: experiments/registry.toml -> topic README.md -> config.yaml -> run.py -> notebook.
3. Confirm the topic entrypoint is not confused with setup tooling: /usr/bin/python experiments/<topic>/run.py with no CLI options is the canonical run command.
4. Confirm the topic code and checked-in config do not set GPU visibility, JAX platform, allocator, preallocation, max_workers: 1, or equivalent serial throttles unless the user explicitly requested an environment-contract change.
5. Confirm caller-owned environment is preserved by topic-created subprocesses: notebook execution and workers should inherit os.environ.copy() or default inheritance instead of replacing GPU/JAX runtime settings.
6. Confirm registered commands, when present, call the topic run.py entrypoint directly. Confirm the direct run writes summary.json, cases.jsonl, config snapshot, case artifacts, and notebook output under experiments/<topic>/result/<run_name>/.
7. Confirm the notebook reads run artifacts and has a Japanese Markdown explanation immediately above each visualization cell.
8. Report findings first, grouped by severity. Treat registered commands that bypass topic run.py, environment hard-coding in topic code, or child subprocess environment reset as fix-now findings.