LinkDB is an advanced SEO link planning and analysis system designed to automate and optimize backlink strategies using semantic SEO principles and topical authority concepts. The system helps plan, track, and analyze link building campaigns with AI-powered insights.
- Automatic Monthly Planning: Generate complete monthly link plans automatically
- Semantic Link Coordination: Plan links that work together to strengthen topical authority
- Customer Database Management: Track all links for each customer with history
- Monthly History Viewer: View and analyze links grouped by publication month
- Semantic Analysis: AI agents analyze link patterns and suggest optimal anchor texts
- Target URL Optimization: Smart selection of target pages based on site structure
- Preflight Validation: Self-correcting system validates plans before execution
- Customer-Specific Agents: AI agents created per customer for personalized planning
- Link History Analysis: Track performance and patterns over time
- Temporal Pattern Analysis: Identify trends in link building strategies
- Anchor Quality Analysis: Evaluate anchor text diversity and quality
- Domain Quality Analysis: Assess the quality of publication domains
- Competitive Comparison: Compare strategies across customers
- Google Sheets Integration: Import/export data directly from Google Sheets
- Airtable CSV Export: Export customer data for Airtable workflows
- Customer Database Builder: Automatically generate per-customer databases
linkdb/
├── app/ # Core application modules
│ ├── analyzers/ # Analysis tools
│ │ ├── anchor_quality_analyzer.py
│ │ ├── domain_quality_analyzer.py
│ │ ├── temporal_pattern_analyzer.py
│ │ ├── link_history_analyzer.py
│ │ └── monthly_link_viewer.py
│ ├── planning/ # Planning system
│ │ ├── basic_plan_generator.py
│ │ ├── customer_grouper.py
│ │ ├── db_manager.py
│ │ └── volume_detector.py
│ ├── validators/ # Validation tools
│ │ └── target_url_validator.py
│ ├── build_all_customer_dbs.py
│ ├── build_history_db.py
│ └── schema.sql
├── gui/ # GUI application
│ ├── backend/
│ │ └── app.py
│ └── gui_app.py
├── data/ # Data files
│ ├── input/
│ └── output/
├── docs/ # Documentation
│ ├── PRODUCT_VISION_2025.md
│ ├── SEMANTIC_SYSTEM_ARCHITECTURE.md
│ └── GUI_SPECIFICATION_FOR_GEMINI.md
└── templates/ # Web templates
- Python 3.8+
- SQLite3
- Google Sheets API credentials (optional, for integration)
- Clone the repository:
git clone https://github.com/robwestz/LinkDB.git
cd LinkDB- Create virtual environment:
python -m venv .venv
.venv\Scripts\activate # On Windows- Install dependencies:
pip install -r requirements_planning.txtpython init_planning_system.pypython app/build_all_customer_dbs.pystart_gui.bat
# Or: python gui_app.pypython export_customer_by_id.py- Planning System Spec - Complete planning system documentation
- Planning Quickstart - Quick start guide
- GUI Documentation - GUI usage guide
- Export Guide - Data export documentation
- Google Sheets Setup - Integration setup
- AI Planning Guide - AI features documentation
- Load monthly data from Google Sheets
- System detects link volume per customer
- AI analyzes semantic opportunities
- Generate coordinated link plan
- Preflight validation and self-correction
- Export to production format
- View customer link history by month
- Analyze anchor text patterns
- Evaluate domain quality
- Compare performance metrics
- Generate insights report
The GUI application provides:
- Main Sheet Viewer: View and manage the main planning sheet
- Planning Tab: Create and manage monthly plans
- Customer Management: Add/edit customer links
- Preflight Analysis: Validate plans before execution
- Export Tools: Export to various formats
- All database files (*.db) are excluded from version control
- Credentials and API keys should be stored in
.envfiles - Customer data is stored locally and not transmitted
This is a private project. For questions or issues, contact the project maintainer.
Private/Proprietary - All rights reserved
robwestz
- Repository: https://github.com/robwestz/LinkDB
- Planning Document: Google Sheets
Active development - Advanced semantic planning features in progress
Built with Python, SQLite, and AI-powered semantic analysis