Research AI Agents

A comprehensive collection of specialized AI agents designed to accelerate and enhance every aspect of academic research. Each agent is an expert in their research domain, ready to be invoked when their expertise is needed throughout the complete research workflow.

🔬 Overview

Transform your research process with 22 specialized AI agents that provide expert guidance from initial brainstorming to final publication. This system replaces the traditional scattered approach to research support with an integrated ecosystem that understands the unique challenges and requirements of academic research.

✨ What Makes This Special

• 🎯 Research-Focused: Built specifically for academic research, not adapted from business tools
• 🔄 Complete Workflow: Covers every stage from ideation to publication
• 🤝 Collaboration-Ready: Designed for team research and multi-institutional projects
• 📊 Evidence-Based: Incorporates best practices from research methodology and science
• 🔓 Open Science: Promotes reproducibility, transparency, and knowledge sharing
• 🌍 Interdisciplinary: Works across all research domains and methodologies

🏗️ System Architecture

research-ai-agents/
├── research-planning/      # Research ideation and planning
├── literature-review/      # Academic literature management
├── experimental-design/    # Methodology and statistical design
├── research-development/   # Research software and tools
├── data-analysis/         # Statistical analysis and visualization
├── paper-writing/         # Academic writing and documentation
└── research-operations/   # Research project management

🚀 Quick Start

Transform your research workflow in minutes. Simply describe your research challenge and the appropriate expert agent will provide specialized guidance.

💡 Example Research Scenarios

🔬 Starting a New Project:

"I want to research the impact of AI on healthcare but need help focusing my ideas"
→ research-ideator generates specific, testable research questions
→ gap-analyzer identifies unexplored areas in AI healthcare research
→ hypothesis-generator creates testable predictions

📚 Literature Review:

"I need to find and synthesize all research on remote work productivity"
→ paper-finder searches across academic databases systematically
→ literature-synthesizer organizes findings into coherent themes
→ citation-analyzer maps the research landscape and key contributors

🧪 Experimental Research:

"I want to test whether music affects coding performance"
→ methodology-designer creates robust experimental design
→ statistical-consultant calculates sample sizes and analysis plans
→ experiment-planner develops detailed protocols

📊 Data Analysis & Publication:

"I have complex longitudinal data that needs analysis and publication"
→ statistical-analyst handles advanced modeling techniques
→ data-visualizer creates publication-quality figures
→ academic-writer crafts compelling manuscripts

📋 Complete Agent Directory

🎯 Research Planning & Ideation (4 agents)

• research-ideator - Generate innovative research ideas and identify novel directions
• gap-analyzer - Systematically identify research gaps through literature analysis
• hypothesis-generator - Formulate testable hypotheses and theoretical predictions
• proposal-writer - Craft compelling research proposals and grant applications

📖 Literature Review (4 agents)

• paper-finder - Search and discover relevant academic literature across databases
• citation-analyzer - Analyze citation patterns and research impact networks
• literature-synthesizer - Synthesize findings from multiple papers into coherent narratives
• reference-manager - Organize and format citations with precision and consistency

🔬 Experimental Design (3 agents)

• methodology-designer - Design robust research methodologies and study approaches
• experiment-planner - Create detailed experimental procedures and protocols
• statistical-consultant - Provide statistical guidance and analysis planning

💻 Research Development (1 agent)

• research-coder - Develop reproducible research software and analysis tools

📊 Data Analysis & Visualization (4 agents)

• statistical-analyst - Conduct advanced statistical analyses and modeling
• data-visualizer - Create publication-quality figures and interactive visualizations
• ml-researcher - Apply machine learning methods to research problems
• results-interpreter - Interpret complex results and draw meaningful conclusions

✍️ Paper Writing & Documentation (4 agents)

• academic-writer - Craft clear, compelling academic manuscripts and papers
• figure-creator - Design scientific figures and publication graphics
• citation-formatter - Format citations and ensure bibliographic accuracy
• research-documenter - Create comprehensive research documentation and reports

🤝 Research Operations (3 agents)

• research-project-manager - Manage complex research projects and timelines
• ethics-advisor - Provide research ethics guidance and compliance support
• collaboration-coordinator - Facilitate research collaboration and team coordination

🌟 Key Features

🔬 Research-First Design

• Built specifically for academic research workflows, not adapted from business tools
• Incorporates best practices from research methodology and scientific practice
• Understands the unique challenges of academic environments

🤖 Intelligent Agent Coordination

• Agents work together seamlessly across research phases
• Automatic handoffs between related research tasks
• Consistent knowledge and context sharing

📈 Evidence-Based Approach

• All recommendations based on established research best practices
• Statistical rigor and methodological soundness built-in
• Quality assurance and validation at every step

🌍 Open Science Ready

• Promotes reproducibility and transparency
• Supports data sharing and collaborative research
• Integrates with open science platforms and standards

🎯 Interdisciplinary Support

• Works across all research domains and methodologies
• Bridges different research cultures and approaches
• Adapts to field-specific requirements and standards

💪 Benefits for Researchers

For Individual Researchers

• ⚡ Accelerated Workflow: Complete research tasks 3-5x faster
• 📚 Expert Guidance: Access to specialized knowledge across all research areas
• 🔄 Consistent Quality: Standardized best practices ensure high-quality outputs
• 🎓 Continuous Learning: Learn research best practices through guided assistance

For Research Teams

• 🤝 Better Collaboration: Structured coordination and communication tools
• 📊 Standardized Processes: Consistent approaches across team members
• 📈 Improved Productivity: Reduced administrative burden and streamlined workflows
• 🎯 Focused Effort: More time for discovery and innovation

For Institutions

• 🏆 Research Excellence: Higher quality research outputs and publications
• 💰 Resource Efficiency: Better utilization of research funding and resources
• 🌐 Collaboration Networks: Enhanced multi-institutional partnerships
• 📋 Compliance Assurance: Built-in ethics and regulatory guidance

🛠️ Getting Started

Prerequisites

• Access to Claude Code or compatible AI agent platform
• Basic understanding of research workflows
• Institutional access to academic databases (recommended)

First Steps

1. Identify your research stage - Where are you in your research journey?
2. Choose your starting agent - Select the most relevant agent for your current needs
3. Describe your challenge - Provide context about your specific research situation
4. Follow the guidance - Implement the agent's recommendations and suggestions
5. Chain agents together - Use multiple agents for complex, multi-stage research tasks

Best Practices

• Be specific - Provide detailed context about your research domain and constraints
• Iterate and refine - Use agent feedback to improve your research approach
• Document everything - Maintain records of agent interactions and recommendations
• Validate outputs - Always verify agent suggestions against domain expertise
• Share and collaborate - Use agents to facilitate team research and knowledge sharing

🔧 Advanced Usage

Multi-Agent Workflows

Combine multiple agents for comprehensive research support:

Research Project Pipeline:
research-ideator → gap-analyzer → hypothesis-generator → proposal-writer
↓
paper-finder → literature-synthesizer → reference-manager
↓
methodology-designer → experiment-planner → statistical-consultant
↓
research-coder → statistical-analyst → data-visualizer → results-interpreter
↓
academic-writer → figure-creator → citation-formatter → research-documenter

Collaboration Patterns

• Team Research: Use collaboration-coordinator for multi-researcher projects
• Multi-Institutional: Leverage research-project-manager for complex partnerships
• Ethics Compliance: Consult ethics-advisor throughout the research process
• Quality Assurance: Regular check-ins with relevant agents for validation

🌐 Integration Ecosystem

Academic Databases

• PubMed, Scopus, Web of Science
• arXiv, bioRxiv, SSRN
• Institutional repositories
• Disciplinary databases

Research Tools

• Reference managers (Zotero, Mendeley, EndNote)
• Statistical software (R, Python, SPSS, SAS)
• Collaboration platforms (GitHub, GitLab, OSF)
• Writing tools (LaTeX, Jupyter, R Markdown)

Publishing Platforms

• Journal submission systems
• Preprint servers
• Conference management systems
• Open access repositories
• Researcher training on agent capabilities
• Integration with existing research workflows
• Change management for research teams
• Continuous improvement based on user feedback

Quality Assurance

📊 Success Metrics

Research Productivity

• 3-5x faster literature reviews and synthesis
• 50% reduction in time spent on administrative tasks
• 2x improvement in research methodology rigor
• Consistent quality across all research outputs

Collaboration Enhancement

• Seamless coordination across multi-institutional projects
• Standardized processes for team research
• Improved communication between diverse research groups
• Enhanced knowledge sharing and transfer

Quality Improvements

• Higher publication acceptance rates through better methodology
• Increased citation impact through improved writing and presentation
• Better reproducibility through standardized documentation
• Enhanced research integrity through built-in quality checks

🤝 Contributing

We welcome contributions to improve and extend the research agent ecosystem:

How to Contribute

1. Report Issues - Identify bugs, inconsistencies, or missing features
2. Suggest Improvements - Propose enhancements to existing agents
3. Add New Agents - Develop agents for specialized research domains
4. Share Use Cases - Document successful applications and workflows
5. Improve Documentation - Help make the system more accessible

Development Guidelines

• Follow the established agent format and structure
• Include comprehensive examples and use cases
• Ensure research-specific focus and expertise
• Maintain consistency with existing quality standards
• Test agents with real research scenarios

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

🙏 Acknowledgments

• Built on the foundation of Claude Code's agent architecture
• Inspired by the needs of the global research community
• Informed by best practices from research methodology and science
• Designed with input from researchers across multiple disciplines

📞 Support

For questions, issues, or collaboration opportunities:

• GitHub Issues - Technical problems and feature requests
• Discussions - General questions and community support
• Email - Direct contact for institutional partnerships

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Transform your research workflow today. Start with any agent that matches your current research challenge and experience the power of AI-assisted academic research.

"Accelerating discovery through intelligent research assistance."