# Env And Assets Bootstrap

> 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.

Source: https://skillsagentes.com/skills/lllllllama/rigorpilot-skills/env-and-assets-bootstrap
Repository: https://github.com/lllllllama/RigorPilot-Skills
Author: lllllllama
License: MIT
Updated: hace 19 días
Context cost: 114 tok installed, 586 tok once triggered, 4.8k tok with every bundled file
Bundle: 8 files, 19 KB
Permissions requested: none declared

## Install

```bash
npx -y skills add lllllllama/RigorPilot-Skills --skill env-and-assets-bootstrap --agent claude-code
```

## What it does

- Prepara notas conservadoras de configuración de entorno conda antes de ejecutar un repo README-first
- Genera comandos conda candidatos y un plan de rutas para assets
- Identifica hints de origen para checkpoints y datasets
- Señala riesgos de dependencias o assets sin resolver

## Use it when

- Tras la intake del repo cuando ya hay un objetivo de reproducción creíble
- Cuando se necesita crear el entorno o preparar rutas de assets antes de correr comandos
- Cuando el repo depende de checkpoints, datasets o directorios de caché
- Cuando el usuario quiere ayuda de setup antes de intentar cualquier ejecución

## Don't bother when

- El repo ya trae un entorno listo para usar que no necesita traducción
- La tarea es solo escanear y planificar, o solo reportar resultados ya ejecutados
- La petición es una pregunta genérica de conda fuera de la reproducción de un repo

## What triggers it

- "Prepara el entorno conda para este repo antes de correrlo"
- "Necesito el plan de rutas de datasets y checkpoints para este proyecto"
- "Configura las notas de setup conservadoras siguiendo el README antes de ejecutar nada"

## Before you install

- Requiere el path del repo objetivo, el objetivo de reproducción seleccionado y los pasos de setup relevantes del README.
- Environment: BASH_SOURCE, PYTHON, PYTHON_BIN, SCRIPT_DIR

## Files

- SKILL.md — 2 KB
- agents/openai.yaml — 314 B
- references/assets-policy.md — 826 B
- references/env-policy.md — 1 KB
- scripts/bootstrap_env.py — 5 KB
- scripts/bootstrap_env.sh — 270 B
- scripts/plan_setup.py — 5 KB
- scripts/prepare_assets.py — 4 KB

## SKILL.md

Reproduced verbatim from lllllllama/RigorPilot-Skills under MIT. This section is the upstream document and is in English.

# 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

- 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.

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Skills Agentes — https://skillsagentes.com/skills/lllllllama/rigorpilot-skills/env-and-assets-bootstrap