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research-pipeline

Automate machine learning research from idea generation to submission-ready papers.

14.4k|1.3k|Updated Mar 10, 2026
Search Tags:#automation#research#machine learning#autonomous agent#experimentation#paper writing
One-click install
npx skills add https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep --skill research-pipeline-wanshuiyin
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: research-pipeline
Source: https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep/tree/main/skills/research-pipeline
Command: npx skills add https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep --skill research-pipeline-wanshuiyin

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill automates the entire research lifecycle, from initial idea generation and validation to experiment implementation, autonomous review, and preparation for submission.

Core Features & Use Cases

  • Full Research Lifecycle: Orchestrates idea discovery, implementation, experimentation, and iterative review.
  • Autonomous Operation: Can run complex research workflows overnight or while you focus on other tasks.
  • Cross-Model Collaboration: Leverages different AI models for execution and critical review to break self-play blind spots.
  • Use Case: Start a research project on a new machine learning technique by providing a broad research direction, and wake up to a submission-ready paper draft with experiments run and weaknesses addressed.

Quick Start

Use the research-pipeline skill to automate the full research process for the topic of "advances in reinforcement learning for robotics".

Frequently Asked Questions about research-pipeline

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

FAQPage Schema
How do I automate the machine learning research pipeline from idea generation to paper writing?▼

You can automate the full machine learning research pipeline by orchestrating literature review, novelty checking, experiment implementation, and autonomous critique to generate a submission-ready paper draft.

What is cross-model collaboration for autonomous experimentation and review?▼

Cross-model collaboration leverages different AI models for execution and critical review during experimentation, breaking self-play blind spots to refine hypotheses and improve final paper quality.

Can I run an autonomous agent for overnight research and experimentation?▼

Yes, you can configure an autonomous agent to run complex research workflows overnight, allowing you to wake up to a completed paper draft with experiments run and weaknesses addressed.

Does the automated research pipeline support configurable human checkpoints?▼

Yes, the automated research pipeline supports configurable human checkpoints, enabling you to pause the workflow for review and validation during idea generation, experimentation, or paper writing.

What environments are supported for executing automated machine learning experiments?▼

The experimentation pipeline supports various execution environments for running implemented machine learning experiments, allowing flexible configuration based on your specific research infrastructure needs.

How does automated novelty checking work for new research hypotheses?▼

Automated novelty checking evaluates generated hypotheses against existing literature during the review phase, identifying unique contributions before proceeding to experiment implementation and paper writing.

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