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Env and assets bootstrap

Skill bg-szy/TOP-SKILLS/skills/marketplace/env-and-assets-bootstrap

Environment and assets sub-skill for README-first AI 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.From its SKILL.md

Install
npx -y skills add bg-szy/TOP-SKILLS --skill env-and-assets-bootstrap

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

2 things to look at

  • no licenseNo license file was found in the repository. Code published without one is not open source by default, so using it at work is a question for whoever answers licensing questions where you are.
  • 5 stars5 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

SKILL.md

2.0 KB, 302 tokens by cl100k_base, as published. Nobody here has run it

env-and-assets-bootstrap

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.

What ships with it: 1 file

19.2 KB alongside SKILL.md

Keep looking

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