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env-and-assets-bootstrap

Prix non confirmé★ 484 Stars GitHubRegistre mis à jour · 23 sept. 2026agent-skill

Vue d’ensemble

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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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.

Voir la source ↗

Métadonnées du fichier

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.

Voir le texte original

---
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.

Examiner la source

Prix et coûts d’utilisation

Obtenir le skill: Prix non confirmé
L’utiliser: Prérequis non confirmés. Consultez les frais d’agent, d’API et de services à la source.
Licence: MIT
Prix non confirmé: Le prix n’est pas confirmé. Les liens existants vers les sources et l’installation restent disponibles.

Gratuit à obtenir ne signifie pas gratuit à utiliser. Le prix ne constitue pas une évaluation de sécurité. Soumettre un prix →

Source à réexaminer

La source a changé ou sa synchronisation a échoué. Vérifiez-la avant installation.

Réviser avant installation: Éviter l’installation automatique

Licence: MIT

Dependency or permission surface needs review
Permission surface may require sandboxing
The skill references an external shared operating principles file (`../ai-research-reproduction/references/agent-operating-principles.md`) that is not included in the skill directory; this could break if the parent repository structure changes.
The `bootstrap_env.py` script imports from `plan_setup` without ensuring that module is available in the same directory; this is fine within the skill but could be fragile if the skill is copied standalone.
Quality score needs review
Permission surface needs review: secrets or environment access, shell or command execution
Stars/forks activity: 484 stars, 16 forks; issue activity unavailable in current metadata
Dependency/runtime risk: command execution surface, credential or environment access
Permission surface: secrets or environment access, shell or command execution

Ouvrir l’audit complet

Les outils sont des indications de métadonnées, pas une compatibilité testée. Les prompts sont des suggestions.

Commencer par une petite tâche

1Lisez la source et confirmez entrées, résultats, dépendances et permissions.
2Demandez un plan à l’agent. Approuvez la configuration et les coûts avant un test isolé.
3Vérifiez résultats et fichiers modifiés. Signalez uniquement ce qui a été exécuté et conservez la révision source.

Vérifiez les dépendances, clés API et frais externes dans la source. Un dépôt public ne rend pas tous les services gratuits.

Source et conseils d’utilisation

Répertorié

Métadonnées et examens sont indicatifs. Popularité, découverte et exécution réussie sont des faits distincts.

Dépôt source: lllllllama/RigorPilot-Skills
Licence: MIT
Version: 1.0.0
Dernier push GitHub: 6 sept. 2026
Registre mis à jour: 23 sept. 2026
Chemin des instructions: skills/env-and-assets-bootstrap/SKILL.md @ 20b8c3ef2652

Version déclarée dans le registre ; vérifiez les versions de la source.

Qualité

70/100

Solide

Confiance

58/100

Do not auto-install

Audit

74/100

Revue nécessaire

Ouvrir l’audit complet Voir le rapport d’évaluation

Dependency or permission surface needs review
Permission surface may require sandboxing
The skill references an external shared operating principles file (`../ai-research-reproduction/references/agent-operating-principles.md`) that is not included in the skill directory; this could break if the parent repository structure changes.
The `bootstrap_env.py` script imports from `plan_setup` without ensuring that module is available in the same directory; this is fine within the skill but could be fragile if the skill is copied standalone.
Quality score needs review
Permission surface needs review: secrets or environment access, shell or command execution
Stars/forks activity: 484 stars, 16 forks; issue activity unavailable in current metadata
Dependency/runtime risk: command execution surface, credential or environment access
Permission surface: secrets or environment access, shell or command execution

Verified installs: —
Résultats: —

Copier ne signifie pas installer. Les compteurs nécessitent un rapport de réussite et ne garantissent pas la qualité globale.

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Ouvrir l’API d’installation Format texte LLM Ouvrir Manifest Plan de résolution auto

Plus de détails

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Créateur: lllllllama
Source: lllllllama/RigorPilot-Skills
Indexé par: Index communautaire OpenAgentSkill

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env-and-assets-bootstrap

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