Agent skill

Env And Assets Bootstrap

by lllllllama in lllllllama/RigorPilot-Skills

Rigor Setup skill for README-first deep learning repo reproduction.

MITAuto-check passedDevelopment

Install Env And Assets Bootstrap

skills CLI
$ npx skills add lllllllama/RigorPilot-Skills --skill env-and-assets-bootstrap -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install lllllllama/RigorPilot-Skills env-and-assets-bootstrap --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/lllllllama/RigorPilot-Skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/env-and-assets-bootstrap .claude/skills/env-and-assets-bootstrap && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
env-and-assets-bootstrap
GitHub stars
497
Used in
1 other repo
Token cost
~592 tokens
SKILL.md length
234 words
Files
8 (incl. scripts, references)
Skills in repo
11
Repo updated
First seen
Licence
MIT

At a glance

Rigor Setup skill for README-first deep learning repo reproduction.

  • The task is specifically to prepare a conservative conda-first environment
  • SKILL.md covers When to apply, When not to apply, Clear boundaries and Input expectations, plus 2 more sections
  • Runs Python and Shell scripts from its folder
  • Checkpoint and dataset path assumptions

What it does

Env And Assets Bootstrap is an agent skill from lllllllama/RigorPilot-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.

Its SKILL.md is about 590 tokens, which your agent loads only when the skill is triggered. The skill folder holds 10 other files, including scripts and reference files (for example `agents/openai.yaml`, `references/assets-policy.md` and `references/env-policy.md`).

It sits in Development, covering Deep learning and Technical documentation. The repository describes itself as: README-first research reproduction skills with bounded execution, auditable evidence, and byte-preserving README annotations. The licence is MIT.

When your agent uses it

  • The task is specifically to prepare a conservative conda-first environment
  • Checkpoint and dataset path assumptions
  • Cache location hints
  • Setup notes before any run on a README-documented repository

Example prompts

  • “/env-and-assets-bootstrap”

Requirements

  • Python 3
  • A Bash shell

What it can do on your machine

Read from SKILL.md and the folder at commit fb3ccdf. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 4 files in scripts/ (Python and Shell), which the agent can run.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Env And Assets Bootstrap loads about 592 tokens when it runs, and up to ~1.1k if it reads all its reference files. Until then it costs about 120 tokens; SKILL.md has 234 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~120
When it runs · the whole SKILL.md, loaded when a task matches
~592
With references · SKILL.md plus every file in references/, read only if the agent opens them
~1.1k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from lllllllama/RigorPilot-Skills at commit fb3ccdf, republished under its MIT licence (© lllllllama). 234 words, ~592 tokens.

Download SKILL.mdSave it as .claude/skills/env-and-assets-bootstrap/SKILL.md (or your agent's skills folder). This skill also uses 7 other files; get the full folder from GitHub.
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.

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.

© lllllllama, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 7 other files (scripts, references) in skills/env-and-assets-bootstrap of lllllllama/RigorPilot-Skills.

  • SKILL.md
  • agents/openai.yaml
  • references/assets-policy.md
  • references/env-policy.md
  • scripts/bootstrap_env.py
  • scripts/bootstrap_env.sh
  • scripts/plan_setup.py
  • scripts/prepare_assets.py

Open the folder on GitHubat commit fb3ccdf

Used in 1 other repository

We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in lllllllama/RigorPilot-Skills, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Env And Assets Bootstrap next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Env And Assets Bootstrap compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Env And Assets Bootstrap this skilllllllllama/RigorPilot-Skills4971 repos~592Automated safety check: PassMIT
Ascendcascend-ai-coding/awesome-ascend-skills174—~3.5kAutomated safety check: PassNone
Docstringpytorch/pytorch104k2 repos~2.6kAutomated safety check: PassCustom licence
Document Public APIspytorch/pytorch104k—~4.2kAutomated safety check: PassCustom licence
Aoti Debugpytorch/pytorch104k1 repos~1.7kAutomated safety check: PassCustom licence
Get API Docs with chubandrewyng/context-hub14k1 repos~775Automated safety check: PassMIT

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Questions about Env And Assets Bootstrap

What does Env And Assets Bootstrap do?

Rigor Setup skill for README-first deep learning repo reproduction. Env And Assets Bootstrap is an agent skill from lllllllama/RigorPilot-Skills. Rigor Setup skill for README-first deep learning repo reproduction.

When should I use Env And Assets Bootstrap?

Env And Assets Bootstrap fits situations like: the task is specifically to prepare a conservative conda-first environment; checkpoint and dataset path assumptions; cache location hints; setup notes before any run on a README-documented repository.

How do I install Env And Assets Bootstrap in Claude Code?

Run `npx skills add lllllllama/RigorPilot-Skills --skill env-and-assets-bootstrap -a claude-code`. Or copy the skill folder (skills/env-and-assets-bootstrap in lllllllama/RigorPilot-Skills) into .claude/skills/env-and-assets-bootstrap in your project. Claude Code loads it when a task matches its description.

How do I install Env And Assets Bootstrap in Codex?

Run `npx skills add lllllllama/RigorPilot-Skills --skill env-and-assets-bootstrap -a codex`. Or copy the skill folder (skills/env-and-assets-bootstrap in lllllllama/RigorPilot-Skills) into .agents/skills/env-and-assets-bootstrap in your project. Codex loads it when a task matches its description.

Can I use Env And Assets Bootstrap in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add lllllllama/RigorPilot-Skills --skill env-and-assets-bootstrap -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/env-and-assets-bootstrap, .gemini/skills/env-and-assets-bootstrap, .github/skills/env-and-assets-bootstrap and .opencode/skills/env-and-assets-bootstrap in your project.

What does Env And Assets Bootstrap need to run?

Going by SKILL.md and its folder, Env And Assets Bootstrap needs Python and a shell for the scripts in its folder. Our summary lists: Python 3; A Bash shell.

Does Env And Assets Bootstrap access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Env And Assets Bootstrap safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Env And Assets Bootstrap use?

Env And Assets Bootstrap is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Env And Assets Bootstrap use?

About 592 tokens (SKILL.md is roughly 2.4k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 500 tokens, read only when the agent opens those files.

What are the alternatives to Env And Assets Bootstrap?

Skills that share tags, products or a category with Env And Assets Bootstrap: Ascendc (ascend-ai-coding/awesome-ascend-skills, 174 stars), Docstring (pytorch/pytorch, 104k stars), Document Public APIs (pytorch/pytorch, 104k stars) and Aoti Debug (pytorch/pytorch, 104k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Env And Assets Bootstrap?

lllllllama (a GitHub user) maintains it in lllllllama/RigorPilot-Skills, which has 497 GitHub stars. The repository holds 11 skills in this directory. The repository was last updated on September 23, 2026.

Source: lllllllama/RigorPilot-Skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.