env-and-assets-bootstrap
bylllllllama· 44 skills
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.
How to install env-and-assets-bootstrap?
lllllllama/rigorpilot-skills/env-and-assets-bootstrap
$npx -y skills add lllllllama/rigorpilot-skills --skill env-and-assets-bootstrapInstalls into the current project.
›Prefer a prompt? Paste this to your agent
Run `npx skills use "https://github.com/lllllllama/rigorpilot-skills" --skill "lllllllama/rigorpilot-skills/env-and-assets-bootstrap"` and follow the generated skill instructions now. Read its complete output, redirecting it to a temporary file first if necessary. Resolve relative paths from the supporting-files directory it provides.
Use the skills in "https://github.com/lllllllama/rigorpilot-skills" that are relevant to the current task. Run `npx skills add "https://github.com/lllllllama/rigorpilot-skills"` and select the relevant skills, then follow their instructions.
SKILL.md
| 1 | # env-and-assets-bootstrap |
| 2 | |
| 3 | Use this as the Rigor Setup skill. The installed slug remains |
| 4 | `env-and-assets-bootstrap` for compatibility. |
| 5 | |
| 6 | Use the shared operating principles in |
| 7 | `../../references/agent-operating-principles.md`; this skill should keep setup |
| 8 | planning conservative while leaving environment-specific judgment to the model. |
| 9 | |
| 10 | ## When to apply |
| 11 | |
| 12 | - After repo intake identifies a credible reproduction target. |
| 13 | - When environment creation or asset path preparation is needed before running commands. |
| 14 | - When the repo depends on checkpoints, datasets, or cache directories. |
| 15 | - When the user explicitly wants setup help before any run attempt. |
| 16 | |
| 17 | ## When not to apply |
| 18 | |
| 19 | - When the repository already ships a ready-to-run environment that does not need translation. |
| 20 | - When the task is only to scan and plan. |
| 21 | - When the task is only to report results from commands that already ran. |
| 22 | - When the request is a generic conda or package-management question outside repo reproduction. |
| 23 | |
| 24 | ## Clear boundaries |
| 25 | |
| 26 | - This skill prepares environment and asset assumptions. |
| 27 | - It does not own target selection. |
| 28 | - It does not own final reporting. |
| 29 | - It does not perform paper lookup except by forwarding gaps to the optional paper resolver. |
| 30 | |
| 31 | ## Input expectations |
| 32 | |
| 33 | - target repo path |
| 34 | - selected reproduction goal |
| 35 | - relevant README setup steps |
| 36 | - any known OS or package constraints |
| 37 | |
| 38 | ## Output expectations |
| 39 | |
| 40 | - conservative environment setup notes |
| 41 | - candidate conda commands |
| 42 | - asset path plan |
| 43 | - checkpoint and dataset source hints |
| 44 | - unresolved dependency or asset risks |
| 45 | |
| 46 | ## Notes |
| 47 | |
| 48 | Use `references/env-policy.md`, `references/assets-policy.md`, `scripts/bootstrap_env.py`, `scripts/plan_setup.py`, and `scripts/prepare_assets.py`. |
| 49 | Use `scripts/bootstrap_env.sh` only as a POSIX wrapper around the Python bootstrapper when a shell entrypoint is more convenient. |
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