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ai-research-reproduction

Coordinate auditable reproduction workflows for AI research repositories.

515|11|Updated Mar 30, 2026
Search Tags:#audit#traceability#reproduction#orchestrate#research-workflow#readme-first
One-click install
npx skills add https://github.com/lllllllama/ai-research-workflow-skills --skill ai-research-reproduction
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: ai-research-reproduction
Source: https://github.com/lllllllama/ai-research-workflow-skills/tree/main/skills/ai-research-reproduction
Command: npx skills add https://github.com/lllllllama/ai-research-workflow-skills --skill ai-research-reproduction

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Automates end-to-end reproducibility of AI research repositories by coordinating a README-first workflow that yields auditable, minimal reproduction bundles.

Core Features & Use Cases

  • Orchestrates repository intake, planning, and target selection using documented commands.
  • Bootstraps environment and assets, runs the smallest credible target, and records evidence for auditability.
  • Generates a standardized repro bundle in repro_outputs/ (SUMMARY.md, COMMANDS.md, LOG.md, status.json), enabling reproducibility and review across teams.

Quick Start

Provide the path to the target repository and run the orchestrator to generate the standardized repro bundle in repro_outputs/.

Frequently Asked Questions about ai-research-reproduction

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

FAQPage Schema
How do I reproduce an AI research repository from its README?▼

You can reproduce an AI research repository by running an orchestration workflow that reads its README, selects the smallest credible target, bootstraps the environment, and generates an auditable bundle with machine-readable logs.

What is a README-first reproduction workflow for AI research?▼

A README-first reproduction workflow coordinates repository intake and target selection using documented commands, bootstraps assets, runs the smallest credible target, and records evidence for auditability across teams.

Can I generate machine-readable reproducibility logs for AI research code?▼

Yes, you can generate machine-readable reproducibility logs by running the workflow to emit a standardized repro_outputs structure containing SUMMARY.md, COMMANDS.md, LOG.md, and status.json files for auditability.

Does this reproduction workflow work with repositories that lack documentation?▼

No, this reproduction workflow requires repositories that expose a README-first pathway with documentation, scripts, configs, or commands to select the smallest credible target and produce a reproducible bundle.

What files are included in a standardized AI research reproduction bundle?▼

A standardized AI research reproduction bundle includes SUMMARY.md, COMMANDS.md, LOG.md, status.json, and an optional train_outputs directory, enabling reproducibility and review across teams.

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