version: "1.0.0" name: env-and-assets-bootstrap description: 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.

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.