AutoResearchClaw: Idea to Paper, Automated

"Research X" — That's All You Type

AutoResearchClaw is the most ambitious paper-writing agent in the OpenClaw ecosystem. You give it a one-line idea. It gives you a conference-level paper — with literature review, experiments, analysis, and LaTeX formatting. No human in the loop.

9,400+ stars. 8 showcase papers across math, biology, NLP, RL, and computer vision. Compatible with OpenClaw and MetaClaw.

How It Works: 23 Stages

AutoResearchClaw runs a 23-stage pipeline that mirrors how a human researcher works — but autonomously:

1. Idea parsing → 2. Literature discovery → 3. Gap identification
→ 4. Hypothesis formulation → 5. Multi-agent debate (challenge the hypothesis)
→ 6. Experiment design → 7. Code generation → 8. Self-debugging
→ 9. Experiment execution → 10. Result analysis → 11. Statistical testing
→ 12. Figure generation → 13. LaTeX writing → 14. Citation verification
→ 15. Anti-hallucination check → 16. Peer review simulation
→ 17. Revision → 18. Hardware-adaptive execution (GPU/CPU)
→ 19. Abstract generation → 20. Title optimization
→ 21. Final compilation → 22. PDF output → 23. Discord/Slack notification

The key innovations:

• Multi-agent debate — One agent proposes, another challenges, a third mediates
• Citation verification — Every reference is checked against real databases
• Self-healing error correction — If code fails, it diagnoses and fixes automatically
• Hardware-adaptive — Detects GPU/CPU and adjusts experiments accordingly

Quick Start

Option 1: Via OpenClaw (Recommended)

If you already have OpenClaw installed:

# Just chat with your OpenClaw
Research the impact of transformer attention mechanisms on protein folding prediction

That's it. AutoResearchClaw integrates directly with OpenClaw — one message starts the entire pipeline.

Option 2: Standalone

git clone https://github.com/aiming-lab/AutoResearchClaw.git
cd AutoResearchClaw
pip install -r requirements.txt
researchclaw run --topic "your research idea here"

Option 3: With MetaClaw (Cross-task Learning)

# AutoResearchClaw can optionally integrate with MetaClaw
# for cross-task learning across multiple research sessions
researchclaw run --topic "your idea" --metaclaw-enabled

The Paper Showcase: 8 Autonomous Papers

AutoResearchClaw has generated 8 complete papers across diverse domains, all without human intervention:

You can view all 8 papers in the official showcase.

Video Resources

YouTube Demo

Bilibili Demo

Key Features at a Glance

Limitations to Keep in Mind

• Generated papers are starting points, not finished publications. Human review is essential.
• Citation verification catches fabricated references but can't guarantee every cited paper says what the agent claims it says.
• Experiment quality depends on the underlying LLM — using Claude or GPT-4 produces better results than smaller models.
• The "conference-level" claim refers to structure and formatting, not guaranteed acceptance.

How It Compares

Related Resources

• AutoResearchClaw on GitHub →
• Paper Showcase →
• Testing Guide →
• All Research Agents on Claw4Science →
• OpenClaw Ecosystem Guide →

Last updated: March 29, 2026. AutoResearchClaw is actively maintained with daily updates.