env-and-assets-bootstrap

作成者： lllllllama

README優先の深層学習リポジトリ再現のためのRigor Setupスキル。READMEにドキュメント化されたリポジトリで実行前に、保守的なconda優先環境、チェックポイントとデータセットのパス前提、キャッシュ場所のヒント、セットアップノートを準備するタスクに使用する。リポジトリスキャン、完全なオーケストレーション、論文解釈、最終実行レポート、特定の再現対象に紐づかない汎用的な環境セットアップには使用しない。

npx skills add https://github.com/lllllllama/rigorpilot-skills --skill env-and-assets-bootstrap

ZIPダウンロード GitHub

env-and-assets-bootstrap

Use this as the Rigor Setup skill. The installed slug remains env-and-assets-bootstrap for compatibility.

Use the shared operating principles in ../../references/agent-operating-principles.md; this skill should keep setup planning conservative while leaving environment-specific judgment to the model.

When to apply

After repo intake identifies a credible reproduction target.
When environment creation or asset path preparation is needed before running commands.
When the repo depends on checkpoints, datasets, or cache directories.
When the user explicitly wants setup help before any run attempt.

When not to apply

When the repository already ships a ready-to-run environment that does not need translation.
When the task is only to scan and plan.
When the task is only to report results from commands that already ran.
When the request is a generic conda or package-management question outside repo reproduction.

Clear boundaries

This skill prepares environment and asset assumptions.
It does not own target selection.
It does not own final reporting.
It does not perform paper lookup except by forwarding gaps to the optional paper resolver.

Input expectations

target repo path
selected reproduction goal
relevant README setup steps
any known OS or package constraints

Output expectations

conservative environment setup notes
candidate conda commands
asset path plan
checkpoint and dataset source hints
unresolved dependency or asset risks

Notes

Use references/env-policy.md, references/assets-policy.md, scripts/bootstrap_env.py, scripts/plan_setup.py, and scripts/prepare_assets.py. Use scripts/bootstrap_env.sh only as a POSIX wrapper around the Python bootstrapper when a shell entrypoint is more convenient.

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