CaseStudies

MassGen Case Studies Summary

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This document provides a comprehensive overview of all MassGen case studies, organized by category and version.

Overview

MassGen is focused on case-driven development. Each case study demonstrates real-world multi-agent collaboration on complex tasks, with actual session logs and outcomes. All case studies follow the PLANNING → TESTING → EVALUATION cycle and include video demonstrations where available.

Release Features & Technical Capabilities

Title	Version	Short Description	Status	Link
Session Management & Computer Use Tools	v0.1.9	Complete session state tracking and restoration for multi-turn conversations, computer use automation tools (Claude/Gemini/OpenAI) for browser and desktop control, enhanced config builder with fuzzy model matching	✅ Ready	📄 Guide
Automation Mode Enables Meta Self-Analysis	v0.1.8	Automation infrastructure with --automation flag providing clean structured output, enabling agents to run nested MassGen experiments and analyze results for meta-level self-analysis	✅ Ready	📄 Case Study · 🎥 Video
Agent Task Planning & Background Execution	v0.1.7	MCP-based task management with dependency tracking, background shell execution for long-running commands, and preemption-based coordination for improved multi-agent workflows	✅ Ready	Documentation in v0.1.7 changelog
Persistent Memory with Semantic Retrieval	v0.1.5	Research-to-implementation workflow demonstrating memory system with automatic fact extraction, vector storage, and semantic retrieval across multi-turn sessions	✅ Ready	📄 Case Study · 🎥 Video
Multimodal Video Analysis	v0.1.3	Meta-level demonstration where agents autonomously download and analyze their own case study videos to identify improvements and automation opportunities	✅ Ready	📄 Case Study · 🎥 Video
Custom Tools with GitHub Issue Market Analysis	v0.1.1	Self-evolution through market analysis using custom Python tools combined with web search to analyze GitHub issues, research trends, and drive feature prioritization	✅ Ready	📄 Case Study
Universal Code Execution via MCP	v0.0.31	Universal code execution capabilities through MCP enabling agents across all backends to run commands, execute tests, and validate code (pytest, uv run, npm test)	✅ Ready	📄 Case Study
MCP Planning Mode for Safe Tool Coordination	v0.0.29	Strategic coordination approach allowing agents to plan MCP tool usage without execution during collaboration, preventing irreversible actions until consensus	✅ Ready	📄 Case Study
AG2 Framework Integration	v0.0.28	External agent adapter system enabling MassGen to orchestrate agents from AG2 framework with code execution capabilities while maintaining consensus architecture	✅ Ready	📄 Case Study · 🎥 Video
Multi-Turn Filesystem Support	v0.0.25	Multi-turn filesystem support with persistent context enabling agents to build websites iteratively (Bob Dylan tribute site example)	✅ Ready	📄 Case Study
Advanced Filesystem with User Context Path Support	v0.0.21-v0.0.22	Advanced filesystem permissions with user context paths, copy MCP integration, and selective path exposure for secure multi-agent workspace collaboration	✅ Ready	📄 Case Study · 🎥 Video
Unified Filesystem Support with MCP Integration	v0.0.16	Unified filesystem capabilities demonstrating cross-workspace coordination, conflict-free development with per-agent versioning, and final workspace snapshots	✅ Ready	📄 Case Study
Gemini MCP Notion Integration	v0.0.15	Integration with Notion via MCP demonstrating seamless third-party tool integration for knowledge management and documentation workflows	✅ Ready	📄 Case Study
Enhanced Logging and Workspace Management	v0.0.12-v0.0.14	Enhanced logging capabilities and workspace management for better debugging, session tracking, and coordination history analysis	✅ Ready	📄 Case Study

Research & Analysis

Title	Version	Short Description	Status	Link
Berkeley Agentic AI Summit Summary	v0.0.3	Agents handle specialized research queries with strict source constraints, demonstrating precise adherence to academic standards and framework-specific talk analysis	✅ Ready	📄 Case Study · 🎥 Video
AI News Synthesis	v0.0.3	Cross-verification and content aggregation excellence demonstrating how agents synthesize diverse AI news sources with fact-checking and consensus building	✅ Ready	📄 Case Study
Grok-4 HLE Benchmark Cost Analysis	v0.0.3	Unanimous expert consensus on complex pricing calculations through iterative refinement, demonstrating collaborative validation for technical analysis	✅ Ready	📄 Case Study

Travel & Recommendations

Title	Version	Short Description	Status	Link
Stockholm Travel Guide	v0.0.3	Extended intelligence sharing and comprehensive convergence where agents collaborate to create detailed travel recommendations with diverse perspectives	✅ Ready	📄 Case Study

Creative & Problem Solving

Title	Version	Short Description	Status	Link
Super Intelligence Approaches	v0.0.4	Complex philosophical and technical question exploration leveraging different reasoning capacities (minimal, medium, high) for comprehensive analysis	✅ Ready	📄 Case Study · 🎥 Video
Comprehensive Algorithm Enumeration	v0.0.4	Technical analysis demonstrating how agents collaboratively enumerate and compare different algorithmic approaches (Fibonacci algorithms)	✅ Ready	📄 Case Study
IMO 2025 AI Winners	v0.0.3	Agents tackle International Mathematical Olympiad problems demonstrating collaborative mathematical reasoning and problem-solving capabilities	✅ Ready	📄 Case Study
Collaborative Creative Writing	v0.0.3	Multi-agent creative writing collaboration showcasing diverse narrative perspectives and consensus-driven story development	✅ Ready	📄 Case Study

In Development

Title	Version	Short Description	Status	Link
Agent Adapter System	Future	Unified agent interface for easier backend integration, enabling seamless integration of new agent frameworks	🔄 In Progress	📄 Case Study · ROADMAP.md
Human-in-the-Loop Safety for Irreversible Actions	Future	Human approval mechanism for dangerous operations (file deletion, system commands, API calls), preventing accidental damage while maintaining agent autonomy	🔄 In Progress	📄 Case Study · ROADMAP.md
Automatic MCP Tool Selection & NLIP	v0.1.13	Automatic MCP tool selection based on task requirements, dynamic tool refinement during execution, NLIP integration for enhanced agent coordination with hierarchy initialization	📋 Planned	📄 Case Study · Target: Nov 17, 2025
Terminal Evaluation & Automated Case Study Generation	v0.1.14	MassGen terminal evaluation and self-improvement, terminal session recording using asciinema, automated case study generation from terminal recordings, video editing integration	📋 Planned	📄 Case Study · Target: Nov 19, 2025
Parallel File Operations & Docker Isolation	v0.1.15	Parallel file operations for improved performance, standard efficiency evaluation and benchmarking methodology, custom tools running in isolated Docker containers for enhanced security and portability	📋 Planned	📄 Case Study · Target: Nov 21, 2025
Web UI Development - Collaborative Design	v0.1.x	Three agents competitively build complete dashboard implementations with peer review and voting. Demonstrated production-ready output in 12 minutes with unanimous consensus	✅ Completed	📄 Draft PR · Session: log_20251025_222849
Interactive Course Generator	v0.1.x	5-agent sequential pipeline transforming PDFs/textbooks into interactive courses with Q&A, drag-and-match exercises, flowcharts, and code examples	📝 Planning	📄 Quick Reference
Codebase Architecture Analysis	v0.1.x	Multi-agent collaborative analysis of large codebases (FastAPI) creating comprehensive architecture documentation by reading 30+ files	🧪 In Testing	📄 Case Study · Config: tools/memory/gpt5mini_gemini_codebase_analysis_memory.yaml
Revert Feature After Final Agent Failure	v0.1.1	Automated rollback mechanism when final agent execution fails, ensuring safe multi-agent operations	⏸️ Blocked	📄 Issue #325
Twitter Integration Case Study	v0.x	Multi-agent Twitter posting and engagement with MCP integration	⏸️ Blocked	Blocked by Twitter rate limits, will revisit

Planned (Backlog)

Title	Version	Short Description	Status	Link
Advanced Orchestration Patterns	v0.2.0+	Task decomposition, parallel coordination, adaptive agent assignment for complex multi-agent workflows	📋 Planned	📄 Case Study · ROADMAP.md
Visual Workflow Designer	v0.2.0+	No-code multi-agent workflow creation with drag-and-drop interface for building complex agent interactions	📋 Planned	📄 Case Study · ROADMAP.md
Enterprise Features	v0.2.0+	RBAC, audit logs, compliance tracking, multi-user collaboration for enterprise deployments	📋 Planned	📄 Case Study · ROADMAP.md
Framework Integrations	v0.2.0+	Seamless integration with LangChain, CrewAI, and custom framework adapters for ecosystem compatibility	📋 Planned	📄 Case Study · ROADMAP.md
Complete Multimodal Pipeline	v0.2.0+	End-to-end audio and video understanding with generation capabilities for full multimodal workflows	📋 Planned	📄 Case Study · ROADMAP.md
Multi-Agent Marketing Automation	Future	Parallel analysis and engagement: Find 200 Twitter accounts (VCs, customers), analyze historical data per account, automated replies to followers. Competitor activity analysis across Twitter, Discord, GitHub with key datapoint extraction. One agent per data point for parallel processing	📋 Planned	📄 Case Study
Web Agent Browsing	Future	Agents autonomously browse and interact with web applications using Gemini 2.5 Computer Use and OpenAI Operator for complex web tasks	📋 Planned	📄 Case Study · Target: Mind2Web Leaderboard
Map-Reduce Document Processing	Future	Assign one document per agent to process, vote on which documents require manager attention. Applications: meeting notes prioritization, paper selection, email triage	📋 Planned	📄 Case Study
Website Creation from Scratch	Future	Produce high-quality website better than existing tools (e.g., Manus.im) with multi-agent collaboration	📋 Planned	📄 Case Study
MassGen Video Recording and Editing	Future	Auto-generate case study videos: run command, record, edit (speed up, captions, log highlights), produce 1-min demo videos automatically	📋 Planned	📄 Case Study
Paper Reviewing	Future	Provide detailed academic paper feedback competing with tools like Refine.ink	📋 Planned	📄 Case Study
Priority-Based Document Ranking	Future	Vote on document importance for busy managers/researchers: meeting notes, conference papers, stock news, emails	📋 Planned	📄 Case Study

Case Study Template

For contributors who want to create their own case studies:

Title	Description	Status	Link
Case Study Template	Comprehensive template with PLANNING → TESTING → EVALUATION structure, including baseline analysis, success criteria, and status tracking	📝 Template	📄 Template

Statistics

• Total Case Studies: 47
  • ✅ Ready: 22 (completed with documentation)
  • ✅ Completed: 1 (Web UI Development)
  • 📝 Planning: 1 (Interactive Course Generator)
  • 🧪 In Testing: 1 (Codebase Analysis)
  • 🔄 In Progress: 2 (Agent Adapter, Irreversible Actions Safety)
  • ⏸️ Blocked: 2 (Revert Feature, Twitter Integration)
  • 📋 Planned: 17 (future backlog: 3 upcoming releases + 5 v0.2.0+ features + 7 existing planned + 2 in development tracks)
  • 📝 Template: 1
• With Video Demonstrations: 9
• Release Versions Covered: v0.0.3 to v0.1.15 (planned)
• Categories: 6 (Release Features, Research, Travel, Creative, In Development, Planned)

Key Features Demonstrated

Technical Capabilities

• ✅ Session state tracking and restoration (v0.1.9)
• ✅ Computer use automation (browser & desktop control) (v0.1.9)
• ✅ Fuzzy model name matching and discovery (v0.1.9)
• ✅ Automation mode for meta-analysis (v0.1.8)
• ✅ DSPy question paraphrasing for diversity (v0.1.8)
• ✅ Agent task planning with dependencies (v0.1.7)
• ✅ Background shell execution (v0.1.7)
• ✅ Preemption coordination (v0.1.7)
• ✅ Multi-turn conversations with persistent memory
• ✅ Multimodal understanding (images, audio, video, PDFs)
• ✅ Custom Python tools integration
• ✅ MCP (Model Context Protocol) integration
• ✅ External framework adapters (AG2)
• ✅ Universal code execution across all backends
• ✅ Planning mode for safe tool coordination
• ✅ Advanced filesystem operations with permissions
• ✅ Cross-workspace coordination
• ✅ Semantic fact extraction and retrieval

Collaboration Patterns

• ✅ Multi-agent consensus building
• ✅ Voting and refinement cycles
• ✅ Representative agent selection
• ✅ Diverse reasoning capacities
• ✅ Cross-verification and validation
• ✅ Iterative improvement workflows

Real-World Applications

• ✅ Research and analysis
• ✅ Code development and testing
• ✅ Content creation and documentation
• ✅ Market analysis and feature prioritization
• ✅ Self-evolution and meta-analysis (v0.1.8)
• ✅ Multi-turn conversation continuation (v0.1.9)
• ✅ Browser and desktop automation (v0.1.9)
• ✅ External system integration (Discord, Notion, GitHub)
• 🔄 Web UI design and competitive development
• 🔄 Educational content generation (interactive courses)
• 📋 Web browsing and automation
• 📋 Document processing at scale
• 📋 Video creation and editing
• 📋 Academic paper reviewing

Development Workflow

Case Study Creation Process

1. Issues First: Submit a GitHub issue for case studies, add label case study
   • Use template: https://github.com/massgen/MassGen/blob/main/docs/case_studies/case-study-template.md
2. Planning Phase:
   • Write prompt
   • Define config file (agents, hyperparameters)
   • Specify command
   • Document current vs. expected behavior
   • Explain how it ties to self-improvement goals
3. Development Phase:
   • Feature created by dev team
   • Iterate with development team
   • Test early to address issues revealed by case study
4. Evaluation Phase:
   • Improve the prompt (ideally in same domain as planning)
   • Run prompt with provided cmd and config
   • Record video demonstration
   • Write report using Claude Code
   • Push to GitHub repo by release

Release Schedule

Goal: Have case study planned the day after releasing previous feature

• Release n-1 feature: Morning
• Plan case study for feature n: Night sync (Tuesday, Thursday, Monday)

Community Contributions

We want this to be a community document:

• Submit your own case studies
• Share interesting use cases
• Contribute to backlog of goals

How to Use This Document

1. Browse by Category: Find case studies relevant to your use case
   • Release Features: Production-ready capabilities and upcoming releases (17 total: 14 ready + 3 planned)
   • In Development: Active development with PRs/testing (7 case studies)
   • Planned: Future roadmap items (12 in backlog)
2. Check Status Icons:
   • ✅ Ready: Complete with documentation and session logs
   • ✅ Completed: Executed successfully, documentation in progress
   • 📝 Planning: Design complete, ready for execution
   • 🧪 In Testing: Active testing and iteration
   • ⏸️ Blocked: Waiting on external dependencies
   • 📋 Planned: In backlog, not yet started

3. Watch Videos: Click video links (🎥) to see live demonstrations

4. Read Documentation: Click “📄 Case Study” links for detailed technical documentation

5. Track Progress: Use GitHub issues and PRs to follow development

6. Create Your Own: Use the template to contribute your own case studies

Technical Requirements by Case Study Type

Completed Features

• Session management with restoration (v0.1.9) ✅
• Computer use automation tools (v0.1.9) ✅
• Fuzzy model matching (v0.1.9) ✅
• Automation mode for LLM agents (v0.1.8) ✅
• DSPy question paraphrasing (v0.1.8) ✅
• Agent task planning (v0.1.7) ✅
• Background shell execution (v0.1.7) ✅
• Multi-turn conversations with persistent memory ✅
• Multimodal understanding (images, audio, video, PDFs) ✅
• Custom Python tools integration ✅
• MCP integration ✅
• Universal code execution ✅

In Development

• Web UI competitive development ✅
• Sequential agent pipelines (course generation) 📝
• Large codebase analysis with memory 🧪

Planned Requirements

• Automatic MCP tool selection (v0.1.13) 📋
• Terminal evaluation and automated case studies (v0.1.14) 📋
• Parallel file operations and Docker isolation (v0.1.15) 📋
• Advanced video understanding and editing 📋
• Map-reduce document processing 📋
• User-defined voting criteria 📋
• Scalable multi-agent backends 📋
• Advanced orchestration patterns (v0.2.0+) 📋
• Visual workflow designer (v0.2.0+) 📋
• Enterprise features (v0.2.0+) �

Long-Term Vision

Website Creation from Scratch

• Goal: Produce websites better than existing tools (e.g., Manus.im)
• Requirements: Playwright/Computer Use, image understanding, filesystem memory, multi-turn memory
• Timeline: After Computer Use integration complete

MassGen Video Recording and Editing

• Goal: Auto-generate case study videos (1-min demos with editing)
• Requirements: Video understanding, cmd execution, video editing MCP, planning mode
• Timeline: Could start soon, needs efficient handling of >10min videos

Paper Reviewing

• Goal: Compete with tools like Refine.ink for detailed paper feedback
• Requirements: Multi-agent review, quality assessment, research knowledge
• Timeline: Research-focused development phase

Interactive Course Generation

• Goal: Transform PDFs/textbooks into interactive courses automatically
• Requirements: 5-agent pipeline, component generation, quality review
• Status: Planning complete, ready for execution

Contributing

We welcome community contributions! To create your own case study:

1. Submit GitHub Issue: Use the case study label
   • Template: https://github.com/massgen/MassGen/blob/main/docs/case_studies/case-study-template.md
2. Planning Phase:
   • Define prompt and expected behavior
   • Create config file
   • Explain connection to self-improvement goals

3. Run MassGen: Save session logs and outputs

4. Record Demo: Use OBS Studio or similar tools

5. Write Documentation: Follow the case study template

6. Submit PR: Include case study doc and video (Claude Code can help)

See the Contributing Guidelines for submission instructions.

TODO & Improvements

• Make it easier to share MassGen sessions online
• Auto-logging for users who opt in (currently just contributors)
• Better community organization for user-submitted case studies
• Automated case study video generation pipeline (see v0.1.14 in Release Features)
• Case study quality metrics and benchmarking

For detailed development roadmap and upcoming features, see ROADMAP.md.

Resources

• Documentation: https://docs.massgen.ai
• Case Studies Online: https://docs.massgen.ai/en/latest/examples/case_studies.html
• GitHub Repository: https://github.com/massgen/MassGen
• Website: https://massgen.ai
• Case Studies Portal: https://case.massgen.ai

Version History

This summary covers case studies from MassGen v0.0.3 (initial release) through v0.1.12 (latest), with planned releases through v0.1.15 and long-term vision for v0.2.0+. For detailed development roadmap, see ROADMAP.md.

Recent Releases (Post v0.1.5)

v0.1.12 (November 14, 2025) - System Prompt Architecture & Multi-Agent Computer Use

• Complete system prompt refactoring with hierarchical structure
• Semtools (semantic search) and Serena (LSP symbol understanding) skills
• Enhanced Gemini computer use with Docker integration
• Multi-agent computer use coordination with VNC visualization

v0.1.11 (November 12, 2025) - Rate Limiting & Bug Fixes

• Multi-dimensional rate limiting for Gemini models
• Model-specific limits with sliding window tracking
• Various bug fixes and stability improvements

v0.1.10 (November 10, 2025) - Framework Streaming & Handbook

• Real-time streaming for LangGraph and SmoLAgent
• MassGen Handbook at https://massgen.github.io/Handbook/
• Enhanced debugging for external framework tools

v0.1.9 (November 7, 2025) - Session Management & Computer Use Tools

• Complete session state tracking and restoration for multi-turn conversations
• Computer use automation tools (Claude, Gemini, OpenAI) for browser and desktop control
• Enhanced config builder with fuzzy model matching
• Expanded backend support (Cerebras, Together, Fireworks, Groq, OpenRouter, Moonshot)

v0.1.8 (November 5, 2025) - Automation Mode & DSPy Integration

• Automation infrastructure with --automation flag for LLM agents
• Real-time status.json monitoring for programmatic workflows
• DSPy-powered question paraphrasing for multi-agent diversity
• Meta-coordination capabilities (MassGen running MassGen)

v0.1.7 (November 3, 2025) - Agent Task Planning & Background Execution

• MCP-based task management with dependency tracking
• Background shell execution for long-running commands
• Preemption coordination for multi-agent workflows

v0.1.6 (November 1, 2025) - Additional improvements and bug fixes

Detailed Case Study Notes

Web UI Development - Collaborative Design

• Status: ✅ Completed October 25, 2025
• Duration: 12 minutes, 25 seconds
• Session: log_20251025_222849
• Agents: GPT-5 (architecture), Claude 3.5 Haiku (technical), Gemini 2.5 Flash (visual)
• Outcome: Gemini won with unanimous 3/3 votes, 97KB production-ready code
• Key Achievement: Zero bugs, zero post-processing, professional dashboard in <15 minutes
• Draft PR: https://github.com/Leezekun/MassGen/pull/375

Interactive Course Generator

• Status: 📝 Planning Complete, Ready for Execution
• Pipeline: 5-agent sequential (parser → structurer → builder → reviewer → publisher)
• Expected Duration: ~30 minutes from PDF to course
• Components: Q&A, drag-and-match, flowcharts, info bubbles, code examples
• Quick Reference: docs/case_studies/interactive-course-generator-QUICKREF.md

Codebase Architecture Analysis

• Status: 🧪 In Testing
• Target: FastAPI repository analysis
• Goal: Read 30+ files, create comprehensive architecture documentation
• Config: tools/memory/gpt5mini_gemini_codebase_analysis_memory.yaml
• Command: Clone FastAPI, analyze components, interactions, design patterns, request flows

Revert Feature After Final Agent Failure

• Status: ⏸️ Blocked
• Issue: https://github.com/Leezekun/MassGen/issues/325
• Goal: Automated rollback when final agent execution fails
• Use Case: Safe multi-agent operations with failure recovery

Twitter Integration

• Status: ⏸️ Blocked by Twitter API rate limits
• Goal: Multi-agent Twitter posting and engagement
• Will Revisit: After API access issues resolved

Multi-Agent Marketing Automation

• Status: 📋 Planned
• Goal: Scalable social media marketing and competitor intelligence
• Key Features:
  • Account Discovery: Find 200+ target Twitter accounts (VCs, potential customers)
  • Parallel Analysis: One agent per account for historical data analysis
  • Automated Engagement: Intelligent automated replies to followers
  • Competitor Monitoring: Track competitor activity across Twitter, Discord, GitHub
  • Key Datapoint Extraction: Each agent focuses on specific metrics
  • Parallel Processing: Simultaneous analysis across all platforms
• Technical Requirements:
  • Twitter MCP for API access
  • Discord MCP for server monitoring
  • GitHub MCP for repository analysis
  • Parallel agent execution framework
  • Data aggregation and reporting tools
  • Rate limiting and API quota management
• Use Cases:
  • VC outreach campaigns
  • Customer engagement at scale
  • Competitive intelligence gathering
  • Market sentiment analysis
  • Lead generation and qualification
• Architecture: Map-reduce pattern with one agent per data point, coordinator agent for aggregation

Web Agent Browsing

• Status: 📋 Planned
• Goal: Compete on Online Mind2Web Leaderboard
• Requirements: Gemini 2.5 Computer Use, OpenAI Operator support
• Use Case: Autonomous web navigation and interaction
• Target: https://huggingface.co/spaces/osunlp/Online_Mind2Web_Leaderboard

Map-Reduce Document Processing

• Status: 📋 Planned
• Goal: Information-to-attention prediction for busy managers
• Applications:
  • Meeting notes prioritization
  • Conference paper selection (100+ papers)
  • Stock news analysis for traders
  • Email triage (top 10 important from past 10 days)
• Requirements:
  • Separate document processing per agent
  • Scalable multi-agent backend
  • User-defined voting criteria
• Key Innovation: Vote on which document requires attention, not which answer is better

Website Creation from Scratch

• Status: 📋 Planned
• Goal: Produce websites better than Manus.im
• Example: https://manus.im/share/lFvPbN1H9dtI1zXIbuYAiF?replay=1
• Technical Requirements:
  • Playwright/Computer Use for browser automation
  • Image understanding (v0.1.3) for visual design
  • Filesystem memory to reduce re-reading
  • Multi-turn memory for follow-up queries
  • OpenAI Operator and Gemini 2.5 Computer Use

MassGen Video Recording and Editing

• Status: 📋 Planned (could start soon)
• Goal: Auto-generate 1-min case study videos
• Workflow:
  1. Run command with full args
  2. Record entire session
  3. Edit: speed up, add captions, highlight logs
  4. Cut unnecessary parts
  5. Produce final demo video
• Technical Requirements:
  • Video understanding (v0.1.3+)
  • Command execution (v0.0.31)
  • Video editing MCP (need to find existing tool)
• Challenge: Handle >10min command execution + video watching/editing time
• Approach: May need planning mode, coordination power of MassGen

Paper Reviewing

• Status: 📋 Planned
• Goal: Compete with Refine.ink for detailed paper feedback
• Target: https://www.refine.ink/
• Requirements: Multi-agent review, academic quality assessment
• Use Case: Provide constructive, thorough academic paper reviews

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Last Updated: November 2, 2025