aiming-lab/AutoResearchClaw

**Repository**: https://github.com/aiming-lab/AutoResearchClaw **Stars**: 11,057 ⭐ **License**: MIT **Language**: Python **Archetype**: Autonomous Research Pipeline **Processing Date**: 2026-04-13

Overview

AutoResearchClaw is a fully autonomous 23-stage research pipeline that transforms a single research idea into a conference-ready paper with no human intervention required. It represents one of the most comprehensive end-to-end automated research systems, integrating literature review, experiment design, execution, analysis, and paper writing.

Repository Structure

AutoResearchClaw/
├── .claude/                 # Claude Code integration
├── researchclaw/           # Core pipeline implementation
├── docs/                   # Documentation and guides
│   ├── HITL_GUIDE.md      # Human-in-the-Loop guide
│   ├── showcase/          # Generated paper examples
│   └── integration-guide.md
├── scripts/               # Setup and utility scripts
├── prompts.default.yaml   # LLM prompts for all stages
└── config.researchclaw.example.yaml # Configuration template

23-Stage Research Pipeline

Literature & Foundation (Stages 1-6)

1. **Idea Refinement** - Topic clarification and scope definition 2. **Literature Search** - OpenAlex, Semantic Scholar, arXiv integration 3. **Literature Analysis** - Citation analysis and gap identification 4. **Research Question Formation** - Hypothesis generation 5. **Methodology Design** - Experimental approach planning 6. **Related Work Synthesis** - Background section creation

Experimentation & Development (Stages 7-13)

7. **Environment Setup** - Hardware-aware sandbox configuration 8. **Code Generation** - Implementation with external CLI agent delegation 9. **Experiment Design** - Statistical methodology planning 10. **Data Collection** - Automated data gathering 11. **Experiment Execution** - GPU/MPS/CPU auto-detection 12. **Results Analysis** - Statistical validation 13. **Visualization** - Figure and chart generation

Quality & Validation (Stages 14-19)

14. **Multi-Agent Peer Review** - CodeAgent, BenchmarkAgent, FigureAgent 15. **4-Round Quality Audit** - AI-slop detection, 7-dimension scoring 16. **NeurIPS Checklist Validation** - Conference standard compliance 17. **Citation Verification** - Anti-fabrication system 18. **Claim Validation** - Anti-hallucination verification 19. **Reproducibility Check** - Code and data validation

Paper Production (Stages 20-23)

20. **Draft Generation** - Section-by-section writing 21. **LaTeX Compilation** - Conference-ready formatting 22. **Final Review** - Human-AI collaborative editing 23. **Submission Package** - Complete paper with supplements

Key Features & Innovations

Human-in-the-Loop (HITL) System

• **6 Intervention Modes**: full-auto, gate-only, checkpoint, step-by-step, co-pilot, custom
• **SmartPause**: Confidence-driven dynamic intervention
• **Idea Workshop**: Hypothesis co-creation
• **Baseline Navigator**: Experiment design review
• **Paper Co-Writer**: Collaborative drafting
• **ALHF**: Intervention learning from human feedback

Multi-Agent Architecture

• **CodeAgent**: Code generation and validation
• **BenchmarkAgent**: Performance evaluation
• **FigureAgent**: Visualization creation
• **Multi-agent debate**: Consensus building across agents

Quality Assurance

• **Anti-fabrication system**: VerifiedRegistry + diagnosis loop
• **Citation verification**: Real literature from academic databases
• **7-dimension review scoring**: Comprehensive quality metrics
• **AI-slop detection**: Academic writing quality control

Cross-Platform Integration

• **ACP-compatible backends**: Claude Code, Codex CLI, Copilot CLI, Gemini CLI, Kimi CLI
• **OpenClaw bridge**: Discord, Telegram, Lark, WeChat support
• **Beast Mode**: Complex code generation routing to OpenCode
• **MetaClaw integration**: Cross-run learning and skill accumulation

Skills System (19+ Skills)

Pre-loaded skills covering:

• Scientific writing methodologies
• Experiment design patterns
• Chemistry and biology domain knowledge
• Statistical analysis techniques
• A-Evolve agentic evolution (community contributed)

Custom skills via:

researchclaw skills install
# or drop SKILL.md into .claude/skills/

Extractable Processes

Research Orchestration Patterns

1. **23-stage pipeline architecture** - Complete research lifecycle 2. **Multi-agent consensus building** - Collaborative validation 3. **Human-AI intervention points** - Strategic collaboration patterns 4. **Dynamic confidence assessment** - Automated quality gating

Quality Assurance Frameworks

1. **Multi-layer validation** - Technical, academic, and reproducibility checks 2. **Citation verification pipelines** - Anti-fabrication safeguards 3. **7-dimension quality scoring** - Comprehensive evaluation metrics 4. **Conference compliance checking** - Automated standard validation

Literature Integration Methods

1. **Multi-source literature aggregation** - OpenAlex, Semantic Scholar, arXiv 2. **Citation analysis workflows** - Gap identification and positioning 3. **Related work synthesis** - Automated background generation 4. **Real-time verification** - Anti-hallucination for references

Experiment Automation

1. **Hardware-aware execution** - GPU/MPS/CPU auto-detection 2. **Sandbox environment management** - Isolated experiment execution 3. **Statistical validation pipelines** - Automated analysis workflows 4. **Reproducibility frameworks** - Code and data validation

Technology Stack

• **Python 3.11+** with modern async/await patterns
• **Docker sandbox** with network-policy-aware execution
• **OpenAlex, Semantic Scholar, arXiv** for literature
• **LaTeX compilation** for paper generation
• **Multi-LLM support** with provider abstraction
• **CLI agent integration** for complex code generation

Value for Babysitter Marketplace

**Very High Value** - This repository contains one of the most sophisticated automated research pipelines available, with extensive orchestration patterns for:

• Multi-stage workflow coordination
• Human-AI collaboration frameworks
• Quality assurance and validation systems
• Literature integration and verification
• Academic standard compliance

Key Extractable Elements

• 23-stage pipeline orchestration patterns
• Multi-agent consensus building mechanisms
• Human-in-the-loop intervention strategies
• Quality evaluation and validation frameworks
• Literature integration and citation verification
• Academic writing and compliance automation

Classification

**Category**: Autonomous Research System **Subcategory**: Academic Paper Generation Pipeline **Complexity**: Research-grade **Maturity**: Production-ready (v0.4.0) **Adoption**: High (11K+ stars, active development)

Ethical Considerations

The repository includes comprehensive ethics guidelines covering:

• Academic integrity requirements
• Transparency in AI assistance
• Citation verification obligations
• Misuse prevention measures
• Human review requirements

Research Notes

This repository represents a significant advancement in automated research methodology, demonstrating:

• End-to-end academic workflow automation
• Sophisticated multi-agent coordination
• Real-world quality assurance mechanisms
• Human-AI collaborative patterns
• Academic standard compliance automation

The 23-stage pipeline architecture and quality validation systems provide substantial value for complex workflow orchestration in babysitter processes.

Library Mapping

Plugin Marketplace Mapping