env-and-assets-bootstrap
Prepares the runtime environment and dependencies for AI paper reproduction, automatically detecting missing model checkpoints, datasets, and cache directories, supporting various cloud storage.
npx skills add lllllllama/ai-paper-reproduction-skill --skill env-and-assets-bootstrapBefore / After Comparison
1 组手动阅读README、识别依赖、安装Python包、下载检查点和数据集、配置路径,准备一个论文环境需要2-4小时,容易遗漏关键步骤
自动扫描仓库依赖、一键安装环境、自动下载缺失资源、智能配置路径,准备环境仅需10-20分钟,标准化可复现
description SKILL.md
env-and-assets-bootstrap
env-and-assets-bootstrap
When to apply
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After repo intake identifies a credible reproduction target.
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When environment creation or asset path preparation is needed before running commands.
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When the repo depends on checkpoints, datasets, or cache directories.
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When the user explicitly wants setup help before any run attempt.
When not to apply
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When the repository already ships a ready-to-run environment that does not need translation.
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When the task is only to scan and plan.
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When the task is only to report results from commands that already ran.
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When the request is a generic conda or package-management question outside repo reproduction.
Clear boundaries
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This skill prepares environment and asset assumptions.
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It does not own target selection.
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It does not own final reporting.
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It does not perform paper lookup except by forwarding gaps to the optional paper resolver.
Input expectations
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target repo path
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selected reproduction goal
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relevant README setup steps
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any known OS or package constraints
Output expectations
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conservative environment setup notes
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candidate conda commands
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asset path plan
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checkpoint and dataset source hints
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unresolved dependency or asset risks
Notes
Use references/env-policy.md, references/assets-policy.md, scripts/bootstrap_env.sh, and scripts/prepare_assets.py.
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