env-and-assets-bootstrap
Rigor Setup skill for README-first deep learning repo reproduction. Use when the task is specifically to prepare a conservative conda-first environment, checkpoint and dataset path assumptions, cache location hints, and setup notes before any run on a README-documented repository. Do not use for repo scanning, full orchestration, paper interpretation, final run reporting, or generic environment setup that is not tied to a specific reproduction target.
适合你，如果需要在本地复现深度学习项目并快速搭建运行环境。
npx oh-my-skill add lllllllama/ai-paper-reproduction-skill/env-and-assets-bootstrapcurl -fsSL https://oh-my-skill.com/install.sh | bash -s -- lllllllama/ai-paper-reproduction-skill/env-and-assets-bootstrapnpx oh-my-skill verify lllllllama/ai-paper-reproduction-skill/env-and-assets-bootstrap怎么用
商店整理自技能原文 · 版本 56bc41c · 表述以原文为准装上后，Claude 会帮你准备深度学习项目的运行环境：创建 conda 环境、规划模型和数据集路径、提示缓存位置，并给出安装前的注意事项。
当你要求复现一个 GitHub 上的深度学习项目，且需要先搭建环境、准备模型文件或数据集时触发。
技能原文 SKILL.md
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.