ai-research-explore
Rigor Explore compatible skill slug for meaningful and potentially novel deep learning research candidates. Use when the researcher has chosen the task family,…
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/rigorpilot-skills
Rigor Explore compatible skill slug for meaningful and potentially novel deep learning research candidates. Use when the researcher has chosen the task family,…
Rigor Reproduce compatible skill slug for README-first deep learning repository reproduction. Use when the user wants an end-to-end, minimal-trustworthy flow…
Rigor Analyze / Rigor Audit read-only skill for deep learning research repositories. Use when the user wants to read and understand a repository, inspect model…
Rigor Improve implementation leaf skill for auditable candidate implementation in deep learning research repositories. Use when the researcher explicitly…
Rigor Improve / Rigor Explore run leaf skill for bounded exploratory evidence in deep learning research repositories. Use when the researcher explicitly…
Rigor Run skill for README-first deep learning repo reproduction. Use when the task is specifically to capture or normalize evidence from the selected smoke…