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 rep

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 ../ai research reproduction/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.

env-and-assets-bootstrap