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reproducibility-check

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Atualizado16 de março de 2026 às 19:56

Apply the reproducibility checklist to assess whether experiments can be re-run reliably.

Instalação

Instalar com Codex ou Claude Copie este prompt, cole no Codex, Claude ou outro assistente e deixe que ele revise a página da skill e instale para você.

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Fonte

Xmaster6y

Xmaster6y/chess-experiments

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Ocupações relacionadasSOC

Baseado na classificação ocupacional SOC

Bioquímicos e biofísicosCiências da Vida, Físicas e Sociais·SOC 19-1021

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2 arquivos

SKILL.md

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name	reproducibility-check
description	Apply the reproducibility checklist to assess whether experiments can be re-run reliably.

Reproducibility Check Skill

When to Use

You are reviewing the project for reproducibility (e.g. review-paper command with experiments in scope).
The user wants to know if main results can be reproduced from the repo.

Instructions

Use references/checklist.md for the checklist items.
For each main result or experiment claimed in the paper, run through the checklist: entry point, configs, data, metrics, logging, randomness.
For each item, record: satisfied (with pointer, e.g. "configs/run_experiment.yaml", "scripts/run_experiment.py") or gap (what is missing).
Output: A short reproducibility report per result (or one table): checklist item → status + pointer or gap. Suggest concrete fixes for gaps (e.g. "add seed to config X").

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name	reproducibility-check
description	Apply the reproducibility checklist to assess whether experiments can be re-run reliably.

Reproducibility Check Skill

When to Use

You are reviewing the project for reproducibility (e.g. review-paper command with experiments in scope).
The user wants to know if main results can be reproduced from the repo.

Instructions

Use references/checklist.md for the checklist items.
For each main result or experiment claimed in the paper, run through the checklist: entry point, configs, data, metrics, logging, randomness.
For each item, record: satisfied (with pointer, e.g. "configs/run_experiment.yaml", "scripts/run_experiment.py") or gap (what is missing).
Output: A short reproducibility report per result (or one table): checklist item → status + pointer or gap. Suggest concrete fixes for gaps (e.g. "add seed to config X").