Add comprehensive integration guides for 4 AI coding assistants: ## New Integration Guides (98KB total) - docs/integrations/WINDSURF.md (20KB) - Windsurf IDE with .windsurfrules - docs/integrations/CLINE.md (25KB) - Cline VS Code extension with MCP - docs/integrations/CONTINUE_DEV.md (28KB) - Continue.dev for any IDE - docs/integrations/INTEGRATIONS.md (25KB) - Comprehensive hub with decision tree ## Working Examples (3 directories, 11 files) - examples/windsurf-fastapi-context/ - FastAPI + Windsurf automation - examples/cline-django-assistant/ - Django + Cline with MCP server - examples/continue-dev-universal/ - HTTP context server for all IDEs ## README.md Updates - Updated tagline: Universal preprocessor for 10+ AI systems - Expanded Supported Integrations table (7 → 10 platforms) - Added 'AI Coding Assistant Integrations' section (60+ lines) - Cross-links to all new guides and examples ## Impact - Week 2 of ACTION_PLAN.md: 4/4 tasks complete (100%) ✅ - Total new documentation: ~3,000 lines - Total new code: ~1,000 lines (automation scripts, servers) - Integration coverage: LangChain, LlamaIndex, Pinecone, Cursor, Windsurf, Cline, Continue.dev, Claude, Gemini, ChatGPT ## Key Features - All guides follow proven 11-section pattern from CURSOR.md - Real-world examples with automation scripts - Multi-IDE consistency (Continue.dev works in VS Code, JetBrains, Vim) - MCP integration for dynamic documentation access - Complete troubleshooting sections with solutions Positions Skill Seekers as universal preprocessor for ANY AI system. Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
364 lines
8.3 KiB
Markdown
364 lines
8.3 KiB
Markdown
# Cline + Django Assistant Example
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Complete example showing how to use Skill Seekers to generate Cline rules for Django development with MCP integration.
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## What This Example Does
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- ✅ Generates Django documentation skill
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- ✅ Creates .clinerules for Cline agent
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- ✅ Sets up MCP server for dynamic documentation access
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- ✅ Shows autonomous Django code generation
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## Quick Start
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### 1. Generate Django Skill
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```bash
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# Install Skill Seekers with MCP support
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pip install skill-seekers[mcp]
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# Generate Django documentation skill
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skill-seekers scrape --config configs/django.json
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# Package for Cline (markdown format)
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skill-seekers package output/django --target markdown
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```
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### 2. Copy to Django Project
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```bash
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# Copy rules to project root
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cp output/django-markdown/SKILL.md my-django-project/.clinerules
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# Or use the automation script
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python generate_clinerules.py --project my-django-project
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```
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### 3. Configure MCP Server
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```bash
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# In VS Code Cline panel:
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# Settings → MCP Servers → Add Server
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# Add this configuration:
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{
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"skill-seekers": {
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"command": "python",
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"args": ["-m", "skill_seekers.mcp.server_fastmcp", "--transport", "stdio"],
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"env": {}
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}
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}
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# Reload VS Code
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```
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### 4. Test in Cline
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```bash
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# Open project in VS Code
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code my-django-project/
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# Open Cline panel (sidebar icon)
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# Start autonomous task:
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"Create a Django blog app with:
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- Post model with author, title, content, created_at
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- Comment model with post foreign key
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- Admin registration
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- REST API with DRF
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- Full test suite with pytest"
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# Cline will autonomously generate code following Django best practices
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```
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## Expected Results
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### Before (Without .clinerules)
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**Cline Task:** "Create a Django user model"
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**Output:**
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```python
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from django.db import models
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class User(models.Model):
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username = models.CharField(max_length=100)
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email = models.EmailField()
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```
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❌ Missing timestamps
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❌ No __str__ method
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❌ No Meta class
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❌ Not using AbstractUser
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### After (With .clinerules)
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**Cline Task:** "Create a Django user model"
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**Output:**
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```python
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from django.contrib.auth.models import AbstractUser
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from django.db import models
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class User(AbstractUser):
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email = models.EmailField(unique=True)
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bio = models.TextField(blank=True)
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created_at = models.DateTimeField(auto_now_add=True)
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updated_at = models.DateTimeField(auto_now=True)
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class Meta:
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ordering = ['-created_at']
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verbose_name = 'User'
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verbose_name_plural = 'Users'
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def __str__(self):
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return self.username
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```
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✅ Uses AbstractUser
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✅ Includes timestamps
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✅ Has __str__ method
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✅ Proper Meta class
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✅ Email uniqueness
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## Files in This Example
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- `generate_clinerules.py` - Automation script
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- `mcp_config.json` - MCP server configuration
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- `requirements.txt` - Python dependencies
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- `example-project/` - Minimal Django project
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- `manage.py`
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- `app/models.py`
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- `app/views.py`
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- `tests/`
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## MCP Integration Benefits
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With MCP server configured, Cline can:
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1. **Search documentation dynamically**
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```
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Cline task: "Use skill-seekers MCP to search Django async views"
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```
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2. **Generate fresh rules**
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```
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Cline task: "Use skill-seekers MCP to scrape latest Django 5.0 docs"
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```
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3. **Package skills on-demand**
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```
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Cline task: "Use skill-seekers MCP to package React docs for this project"
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```
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## Rule Files Structure
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After setup, your project has:
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```
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my-django-project/
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├── .clinerules # Core Django patterns (auto-loaded)
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├── .clinerules.models # Model-specific patterns (optional)
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├── .clinerules.views # View-specific patterns (optional)
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├── .clinerules.testing # Testing patterns (optional)
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├── .clinerules.project # Project conventions (highest priority)
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└── .cline/
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└── memory-bank/ # Persistent project knowledge
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└── README.md
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```
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Cline automatically loads all `.clinerules*` files.
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## Customization
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### Add Project-Specific Patterns
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Create `.clinerules.project`:
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```markdown
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# Project-Specific Conventions
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## Database Queries
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ALWAYS use select_related/prefetch_related:
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\```python
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# BAD
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posts = Post.objects.all() # N+1 queries!
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# GOOD
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posts = Post.objects.select_related('author').prefetch_related('comments').all()
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\```
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## API Responses
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NEVER expose sensitive fields:
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\```python
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class UserSerializer(serializers.ModelSerializer):
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class Meta:
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model = User
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fields = ['id', 'username', 'email', 'bio']
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# NEVER include: password, is_staff, is_superuser
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\```
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```
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### Memory Bank Setup
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```bash
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# Initialize memory bank
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mkdir -p .cline/memory-bank
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# Add project context
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cat > .cline/memory-bank/README.md << 'EOF'
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# Project Memory Bank
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## Tech Stack
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- Django 5.0
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- PostgreSQL 16
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- Redis for caching
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- Celery for background tasks
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## Architecture
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- Modular apps (users, posts, comments)
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- API-first with Django REST Framework
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- Async views for I/O-bound operations
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## Conventions
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- All models inherit from BaseModel (timestamps)
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- Use pytest for testing
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- API versioning: /api/v1/
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EOF
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# Ask Cline to initialize
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# In Cline: "Initialize memory bank from README"
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```
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## Troubleshooting
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### Issue: .clinerules not loading
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**Solution:** Check file location
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```bash
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# Must be at project root
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ls -la .clinerules
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# Reload VS Code
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# Cmd+Shift+P → "Developer: Reload Window"
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```
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### Issue: MCP server not connecting
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**Solution 1:** Verify installation
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```bash
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pip show skill-seekers
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# Should show: [mcp] extra installed
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```
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**Solution 2:** Test MCP server directly
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```bash
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python -m skill_seekers.mcp.server_fastmcp --transport stdio
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# Should start without errors
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```
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**Solution 3:** Use absolute Python path
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```json
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{
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"skill-seekers": {
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"command": "/usr/local/bin/python3",
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"args": ["-m", "skill_seekers.mcp.server_fastmcp", "--transport", "stdio"]
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}
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}
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```
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### Issue: Cline not using rules
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**Solution:** Add explicit instructions
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```markdown
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# Django Expert
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You MUST follow these patterns in ALL Django code:
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- Include timestamps in models
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- Use select_related for queries
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- Write tests with pytest
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NEVER deviate from these patterns.
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```
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## Advanced Usage
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### Multi-Framework Project (Django + React)
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```bash
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# Backend rules
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skill-seekers package output/django --target markdown
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cp output/django-markdown/SKILL.md .clinerules.backend
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# Frontend rules
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skill-seekers package output/react --target markdown
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cp output/react-markdown/SKILL.md .clinerules.frontend
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# Now Cline knows BOTH Django AND React patterns
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```
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### Cline + RAG Pipeline
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```python
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# Create both .clinerules and RAG pipeline
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from skill_seekers.cli.doc_scraper import main as scrape
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from skill_seekers.cli.package_skill import main as package
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# Scrape
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scrape(["--config", "configs/django.json"])
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# For Cline
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package(["output/django", "--target", "markdown"])
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# For RAG search
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package(["output/django", "--target", "langchain", "--chunk-for-rag"])
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# Now you have:
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# 1. .clinerules (for Cline context)
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# 2. LangChain docs (for deep search)
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```
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## Real-World Workflow
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### Complete Blog API with Cline
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**Task:** "Create production-ready blog API"
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**Cline Autonomous Steps:**
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1. ✅ Creates models (Post, Comment) with timestamps, __str__, Meta
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2. ✅ Adds select_related to querysets (from .clinerules)
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3. ✅ Creates serializers with nested data (from .clinerules)
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4. ✅ Implements ViewSets with filtering (from .clinerules)
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5. ✅ Sets up URL routing (from .clinerules)
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6. ✅ Writes pytest tests (from .clinerules.testing)
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7. ✅ Adds admin registration (from .clinerules)
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**Result:** Production-ready API in minutes, following all best practices!
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## Related Examples
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- [Cursor Example](../cursor-react-skill/) - Similar IDE approach
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- [Windsurf Example](../windsurf-fastapi-context/) - Windsurf IDE
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- [Continue.dev Example](../continue-dev-universal/) - IDE-agnostic
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- [LangChain RAG Example](../langchain-rag-pipeline/) - RAG integration
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## Next Steps
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1. Add more frameworks (React, Vue) for full-stack
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2. Create memory bank for project knowledge
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3. Build RAG pipeline with `--target langchain`
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4. Share your .clinerules patterns with community
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5. Integrate custom MCP tools for project-specific needs
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## Support
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- **Skill Seekers Issues:** [GitHub](https://github.com/yusufkaraaslan/Skill_Seekers/issues)
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- **Cline Docs:** [docs.cline.bot](https://docs.cline.bot/)
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- **Integration Guide:** [CLINE.md](../../docs/integrations/CLINE.md)
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