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.

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Updated: 1 month ago
In the catalog since: 18 Sept 2026
From: lllllllama/rigorpilot-skills

Get it through your agent npx skills add lllllllama/rigorpilot-skills@env-and-assets-bootstrap

Skill instructions

Rendered from the published SKILL.md, 50 lines.

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.

Get it through your agent

Call the Graph-of-Skills MCP server's retrieve_skill_bundle tool and it returns this skill's text inside your budget.

{
  "tool": "retrieve_skill_bundle",
  "arguments": {
    "query": "env-and-assets-bootstrap"
  }
}

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Source

Source repository lllllllama/rigorpilot-skills
Listing on skills.sh

From lllllllama/rigorpilot-skills via skills.sh

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