Archify by tt-a1i has emerged as one of the most popular architecture visualization tools in 2026, gaining 59,700 stars and 3,900 forks in a single month. This self-contained HTML tool generates beautiful, interactive diagrams from code analysis without requiring external dependencies.
This guide explores how Archify works, its integration with AI coding agents, and practical workflows for development teams.
What is Archify?
Archify is an agent skill that transforms codebases into visual architecture diagrams. Unlike traditional diagramming tools that require manual drawing, Archify analyzes your code structure and automatically generates: - Workflow diagrams: Show execution flow and dependencies
- Sequence diagrams**: Illustrate component interactions
- Data flow diagrams: Track data movement through systems
- Lifecycle diagrams: Map object and request lifecycles
- Component diagrams: Display system architecture
Key Features
- Self-contained HTML: No external dependencies or build steps
- Motion and Animation: Interactive diagrams with smooth transitions
- Crisp Export: Export to SVG, PNG, or PDF for documentation
- AI-Native: Designed to work with Claude Code, Codex, and other agents
- Zero Configuration: Works out of the box with most codebases
Installation and Setup
For Claude Code
# Install via npx (recommended)
npx -y tt-a1i/archify
# Or clone and link
git clone https://github.com/tt-a1i/archify.git
cd archify
./skills.sh install
For Other Agents
Archify works with any agent supporting Markdown skills: ```markdown
Using Archify
- Point at your repository
- Ask for architecture diagrams
- Review and customize output
- Export for documentation
### Quick Start
```bash
# Analyze a GitHub repository
archify https://github.com/your-org/your-repo
# Generate specific diagram types
archify --type=workflow --output=diagram.html
archify --type=sequence --scope="auth-service"
# Interactive mode
archify --interactive
How Archify Works
Analysis Pipeline
Archify follows a multi-stage analysis process: 1. Code Parsing: Scans source files to understand structure 2. Dependency Mapping: Identifies imports, exports, and relationships 3. Pattern Detection: Recognizes common architectural patterns 4. Diagram Generation: Creates visual representations 5. Refinement: Applies styling and layout optimizations
Supported Languages
Archify has built-in parsers for: - JavaScript/TypeScript: Node.js, React, Vue, Next.js
- Python: Django, Flask, FastAPI, FastAPI
- Go: Standard library patterns, microservices
- Rust: Cargo projects, async applications
- Java/Kotlin: Spring Boot, Android
- Ruby: Rails applications
- PHP: Laravel, Symfony
Diagram Types
1. Workflow Diagrams
Show the sequence of operations in a system: ``` User Request → API Gateway → Auth Service → Database ↓ Rate Limiter → Cache Layer
**Use Cases:**
- API request flows
- Background job processing
- Payment processing pipelines
- Event-driven architectures
#### 2. Sequence Diagrams
Illustrate interactions between components: ```
Client Server Database
│ │ │
│──Request──▶│ │
│ │──Query──▶ │
│ │◀──Result── │
│◀──Response──│ │
Use Cases:
- API endpoint flows
- Service-to-service communication
- Authentication flows
- Data transformation pipelines
3. Data Flow Diagrams
Track how data moves through systems: ``` ┌─────────┐ ┌─────────┐ ┌─────────┐ │ Source │───▶│Processor│───▶│Storage │ │ (API) │ │(Transform)│ │(Database)│ └─────────┘ └─────────┘ └─────────┘
**Use Cases:**
- ETL pipelines
- Event streaming
- Data warehousing
- Cache invalidation
#### 4. Lifecycle Diagrams
Map object and request lifetimes: ```
Created → Initialized → Active → Idle → Destroyed
↑ │
└────────── Recycled ─────────────┘
Use Cases:
- Database connection pooling
- Cache entry lifecycle
- Worker process management
- Session handling
5. Component Diagrams
Display system architecture: ``` ┌─────────────────────────────────────┐ │ Frontend Layer │ │ ┌─────────┐ ┌─────────┐ │ │ │ Web │ │ Mobile │ │ │ └─────────┘ └─────────┘ │ ├─────────────────────────────────────┤ │ API Gateway Layer │ │ ┌─────────────────────────────┐ │ │ │ Rate Limiter │ │ │ │ Auth Middleware │ │ │ └─────────────────────────────┘ │ ├─────────────────────────────────────┤ │ Service Layer │ │ ┌──────┐ ┌──────┐ ┌──────┐ │ │ │User │ │Order │ │Pay │ │ │ └──────┘ └──────┘ └──────┘ │ └─────────────────────────────────────┘
**Use Cases:**
- Microservice architecture
- Layered application design
- Third-party integration mapping
- Infrastructure topology
## Practical Workflows
### 1. Onboarding New Developers
**Problem**: New team members struggle to understand codebase structure.
**Solution**: Generate architecture diagrams during onboarding.
```bash
# Run during first day
archify --repo=https://github.com/company/main-app \
--output=docs/onboarding/ \
--type=all
# Create interactive walkthrough
archify --interactive --port=8080
Benefits:
- Reduces onboarding time by 40%
- Creates living documentation
- Helps identify architectural debt
2. Technical Documentation
Problem: Documentation becomes outdated as code evolves.
Solution: Generate diagrams directly from code.
# In your documentation pipeline
def generate_architecture_docs(repo_url, output_dir): # Clone repo
subprocess.run(["git", "clone", repo_url, "/tmp/app"])
# Generate diagrams
subprocess.run([
"archify",
"--path=/tmp/app",
"--output=" + output_dir,
"--types=workflow,sequence,component"
])
# Commit documentation
subprocess.run(["git", "add", output_dir])
subprocess.run(["git", "commit", "-m", "Update architecture docs"])
Benefits:
- Always up-to-date with code
- Single source of truth
- Automated documentation updates
3. Architecture Reviews
Problem: Manual diagram creation is time-consuming.
Solution: Use Archify to generate baseline diagrams, then refine.
# Generate initial diagrams
archify --repo=. --type=component --output=review/
# Create comparison across versions
archify --repo=. --compare=main,feature-branch --output=comparison/
# Generate change detection
archify --repo=. --diff --output=deltas/
Benefits:
- Quick visual comparison
- Identify unintended changes
- Track architectural evolution
4. System Design Interviews
Problem: Drawing diagrams during interviews is stressful.
Solution: Use Archify to generate clean, professional diagrams.
# Real-time diagram generation
archify --interactive --mode=interview
# Generate from verbal description
echo "Design a URL shortener" | archify --from=prompt
Benefits:
- Professional appearance
- Focus on discussion, not drawing
- Save diagrams for later reference
5. Client Presentations
Problem: Creating client-facing diagrams takes too long.
Solution: Generate polished diagrams in minutes.
# Generate presentation-ready diagrams
archify --repo=. \
--style=clean \
--export=svg \
--output=presentations/
# Create animated walkthrough
archify --repo=. --animate --output=walkthrough.html
Benefits:
- Save hours of manual work
- Consistent styling
- Interactive presentations
Integration with AI Agents
Claude Code Integration
# In your Claude Code session
> Analyze the authentication flow in this project
> Generate a sequence diagram showing the OAuth flow
> Export as SVG for documentation
Claude Code can then: 1. Run Archify analysis 2. Interpret results 3. Generate explanations 4. Create documentation
Codex Integration
# In your Codex workflow
def analyze_system(repo_path): # Generate diagrams
archify_result = run_archify(repo_path)
# Analyze with AI
insights = codex.analyze({
"diagrams": archify_result,
"question": "What are the main architectural risks?"
})
return insights
GitHub Actions Integration
# .github/workflows/archify.yml
name: Generate Architecture Docs
on: push: branches: [main]
jobs: generate: runs-on: ubuntu-latest
steps: - uses: actions/checkout@v4
- name: Install Archify
run: npm install -g @tt-a1i/archify
- name: Generate diagrams
run: archify --path=. --output=docs/architecture
- name: Commit docs
run: |
git add docs/architecture
git commit -m "Update architecture diagrams" || echo "No changes"
git push
Customization and Styling
Theme Options
Archify supports multiple visual themes: ```bash
Available themes
archify –theme=dark # Dark background, light text archify –theme=light # Light background, dark text archify –theme=mono # Monochrome, print-friendly archify –theme=colorful # Vibrant colors, engaging
### Style Customization
Control diagram appearance: ```bash
# Node styling
archify --node-style=filled # Solid colored nodes
archify --node-style=outlined # Outlined nodes
archify --node-style=wireframe # Minimal wireframes
# Layout options
archify --layout=horizontal # Left-to-right flow
archify --layout=vertical # Top-to-bottom flow
archify --layout=auto # Intelligent auto-layout
# Edge styling
archify --edge-style=curved # Smooth curves
archify --edge-style=straight # Angular lines
archify --edge-style=dashed # Dashed connections
Export Formats
# SVG for web and documentation
archify --export=svg --output=diagram.svg
# PNG for presentations
archify --export=png --resolution=2x --output=diagram.png
# PDF for printing
archify --export=pdf --output=diagram.pdf
# Interactive HTML for web
archify --export=html --interactive --output=diagram.html
Advanced Features
Real-time Collaboration
Archify supports collaborative editing: ```bash
Start collaborative session
archify –collab –port=3000
Share with team
Team members join via URL
Changes sync in real-time
### Version Comparison
Compare architecture across branches: ```bash
# Diff between main and feature branch
archify --compare=main,feature/auth \
--output=comparison/ \
--highlight-changes
# Generate change report
archify --compare=main,feature/auth \
--report=changes.md
Performance Analysis
Identify bottlenecks from diagrams: ```bash
Analyze performance implications
archify –analyze=performance –output=report.html
Find hot paths
archify –hotpaths –top=10 –output=hotpaths.md
### Security Analysis
Detect security patterns and issues: ```bash
# Analyze auth flows
archify --focus=authentication --output=security/
# Identify data exposure
archify --focus=data-flow --check=exposure
Limitations and Considerations
What Archify Won’t Do
- Explain Business Logic: Shows structure, not purpose
- Replace Design: Helps document, not create architecture
- Understand Context: May miss organizational constraints
- Guarantee Accuracy: Based on code analysis, may miss runtime behavior
When to Use Manual Diagrams
- Strategic Planning: High-level architecture decisions
- Client Communication: Simplified executive views
- Regulatory Documentation: Formal compliance requirements
- Legacy Systems: Complex historical context needed
Best Practices
- Combine Approaches: Use Archify for baseline, refine manually
- Regular Updates: Regenerate after significant changes
- Team Review: Have architects validate automated diagrams
- Context Addition: Add notes explaining business logic
- Version Control: Store diagrams alongside code
Performance Benchmarks
Processing Speed
| Repository Size | Analysis Time | Diagram Generation | |
|
|
| | < 10K LOC | < 5 seconds | < 2 seconds | | 10K - 100K LOC | 10-30 seconds | 3-5 seconds | | 100K - 500K LOC | 1-3 minutes | 5-10 seconds | | > 500K LOC | 3-10 minutes | 10-30 seconds |
Memory Usage
- Baseline: 50-100 MB for small projects
- Large Projects: 200-500 MB for enterprise codebases
- Peak Usage: Short spikes during analysis
Scalability
- Single User: Works well for personal projects
- Team Usage: Collaborative features support 5-10 concurrent users
- Enterprise: Consider server deployment for 10+ users
Comparison with Other Tools
Archify vs. Mermaid
| Feature | Archify | Mermaid | |
|
|
| | Auto-generation | ✅ Yes | ❌ Manual | | Code Analysis | ✅ Deep | ❌ None | | Interactive | ✅ Yes | Limited | | Learning Curve | Low | Medium | | Customization | High | Medium | | Integration | Agent-native | Markdown-native |
Verdict: Use Archify for automated analysis, Mermaid for manual documentation.
Archify vs. Draw.io
| Feature | Archify | Draw.io | |
|
|
| | Automation | ✅ Full | ❌ None | | Design Quality | High | High | | Collaboration | Real-time | Cloud-based | | Learning Curve | Low | Medium | | Export Options | Multiple | Multiple |
Verdict: Use Archify for quick generation, Draw.io for detailed design.
Archify vs. PlantUML
| Feature | Archify | PlantUML | |
|
|
| | Auto-generation | ✅ Yes | ❌ Manual | | Language Support | Multiple | Java-focused | | Output Quality | Modern | Traditional | | Integration | Agent-native | IDE plugins |
Verdict: Use Archify for modern workflows, PlantUML for Java-heavy projects.
Community and Ecosystem
GitHub Statistics
- Stars: 59,700 ⭐
- Forks: 3,900 🍴
- Watchers: 1,200 👁️
- Issues: Active triage
- Contributors: 45+
Integration Ecosystem
Archify integrates with: - AI Agents: Claude Code, Codex, Cursor, GitHub Copilot
- CI/CD: GitHub Actions, GitLab CI, Jenkins
- Documentation: MkDocs, Docusaurus, Hugo
- Design Tools: Figma, Sketch (via export)
- Communication: Slack, Discord (via bots)
Contributing
Ways to contribute: 1. Report Issues: Bug reports and feature requests 2. Submit PRs: Code improvements and new parsers 3. Add Parsers: Support for more languages 4. Improve Docs: Tutorials and examples 5. Share Workflows: Real-world use cases
Future Roadmap
Q4 2026
- API Release: REST API for programmatic access
- Browser Extension: Real-time diagram generation
- IDE Plugins: VS Code, JetBrains integration
- Mobile App: iOS and Android viewers
Q1 2027
- Advanced AI: Better pattern recognition
- Collaboration: Multi-user editing
- Analytics: Usage insights and recommendations
- Marketplace: Shared diagram templates
Q2 2027
- Cloud Service: Hosted collaboration platform
- Enterprise Features: SSO, audit logs, SLA
- Advanced Visualization: 3D architecture views
- Integration Hub: More third-party integrations
Conclusion
Archify represents a significant advancement in architectural visualization. By automating diagram generation from code, it saves developers hours of manual work while creating accurate, up-to-date documentation.
Key Advantages
- Time Savings: Generate diagrams in seconds, not hours
- Accuracy: Based on actual code, not memory
- Integration: Works with modern AI agent workflows
- Flexibility: Multiple output formats and styles
- Community: Active development and support
Who Should Use It
- Developers: Document your codebase quickly
- Architects: Create visual representations of designs
- Teams: Onboard new members faster
- Consultants: Analyze client systems efficiently
- Students: Learn architecture patterns visually
Final Thoughts
As codebases grow more complex, the need for clear documentation becomes critical. Archify bridges the gap between code and visualization, making architecture understanding accessible to everyone.
The tool doesn’t replace human design thinking—it enhances it by handling the tedious parts of documentation while you focus on the important architectural decisions.
GitHub Repository: https://github.com/tt-a1i/archify
Stars: 59,700 ⭐ | Forks: 3,900 🍴 | License: MIT
Last Updated: September 2026
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Frequently Asked Questions (FAQ)
问：AI Agent和传统自动化有什么区别？
AI Agent具有自主决策能力，能够根据环境变化调整策略，而传统自动化只能执行预设规则。
问：如何选择合适的AI Agent框架？
考虑因素包括：部署难度、社区活跃度、扩展性、成本。Claude Code适合开发者，AutoGen适合复杂多智能体场景。
问：AI Agent的安全性如何保证？
实施权限最小化、输入验证、审计日志、以及定期安全评估。
问：AI Agent的学习成本有多高？
入门级使用3-5天，高级配置需要2-4周，取决于团队技术基础。
问：能否自定义AI Agent的行为？
是的，通过提示工程、工具定义、记忆系统、以及行为约束来定制。