env-and-assets-bootstrap

Conservative conda-first environment and asset preparation for deep learning repository reproduction.

- Prepares environment setup notes, candidate conda commands, and asset path plans based on README documentation and repo constraints

- Identifies checkpoint and dataset sources, cache location hints, and unresolved dependency or asset risks before execution

- Applies only after repo intake identifies a credible reproduction target; does not handle repo scanning, orchestration, or final reporting

- Expects target repo path, reproduction goal, README setup steps, and OS/package constraints as input

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