reproducibility-report

Collect experiment details from code, configs, logs, and environment files into a structured reproducibility report.

11|2|Updated May 29, 2025
One-click install
npx skills add https://github.com/yulonglin/dotfiles --skill reproducibility-report
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: reproducibility-report
Source: https://github.com/yulonglin/dotfiles/tree/main/claude/local-marketplace/plugins/research-toolkit/skills/reproducibility-report
Command: npx skills add https://github.com/yulonglin/dotfiles --skill reproducibility-report

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Reproducibility is critical for ML research; this Skill automates gathering experiment details into a structured reproducibility report to ensure you can replicate results.

Core Features & Use Cases

  • Auto-extract from code, configs, and logs to populate a complete reproducibility.md
  • Template-driven output exports to out/{experiment_dir}/reproducibility.md using the provided references/template.md
  • Wide applicability suitable after completing experiments, for collaboration, or for publication preparation

Quick Start

After you finish an experiment, run the reproducibility reporter to auto-generate a complete reproducibility.md in out/{experiment_dir}.

Frequently Asked Questions about reproducibility-report

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I generate a reproducibility report for completed ML experiments?▼

To generate a reproducibility report for ML experiments, run the reporter to auto-extract details from code, configs, logs, and environment files, exporting a structured reproducibility.md to out/{experiment_dir}.

What should a machine learning reproducibility report include for publication preparation?▼

A machine learning reproducibility report for publication should include model identity, prompts, data, compute, and provenance, which this template-driven process auto-collects into a structured markdown file.

Can I use Hydra configs and environment files to document experiment provenance automatically?▼

Yes, you can document experiment provenance automatically by extracting configuration and environment details from Hydra configs and environment files, populating a fixed reproducibility template.

What is the best way to automate collecting experiment details into a structured markdown file?▼

The best way to automate collecting experiment details into a structured markdown file is using a template-driven approach that pulls data from code, configs, and logs to export reproducibility.md.

Does the reproducibility report template support fixed output paths for experiment directories?▼

Yes, the reproducibility report template supports fixed output paths, automatically exporting the generated markdown to out/{experiment_dir}/reproducibility.md for consistent file organization.