ai-research-explore
Rigor Explore compatible skill slug for meaningful and potentially novel deep learning…
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
$ npx -y skills add lllllllama/rigorpilot-skills --skill env-and-assets-bootstrap --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/env-and-assets-bootstrapContext preview
The summary Claude sees to decide when to auto-load this skill.
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
name: env-and-assets-bootstrap description: 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.
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.
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.
Run research repositories from their README, with bounded execution and auditable evidence. RigorPilot adds section-level results without rewriting the original README. Trusted reproduction is the default; candidate exploration requires explicit authorization.
Repo: lllllllama/ai-paper-reproduction-skill
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Rigor Run skill for README-first deep learning repo reproduction. Use when the task is…