Knowledge Base

The knowledge base is the “brain” of the Mendix Expert server. It contains curated, structured information about Mendix development.

Structure

knowledge/
├── best-practices.json      # Coding patterns, guidelines
├── studio-pro.json          # Studio Pro features, UI
├── model-sdk.json           # Model SDK programming
├── platform-sdk.json        # Platform SDK operations
├── troubleshooting.json     # Common issues, solutions
├── advanced-patterns.json   # Complex techniques
├── performance-guide.json   # Optimization strategies
├── security-guide.json      # Security best practices
└── harvested-*.json         # Auto-crawled content

Entry Format

Every knowledge entry follows this structure:

{
  "title": "Loop Pattern for Microflows",
  "description": "How to iterate over lists in microflows",
  "content": "Detailed explanation...",
  "when_to_use": "When you need to process items one by one",
  "best_practices": ["Use IterableList on loopSource", "Avoid deprecated loopVariableName"],
  "examples": [
    {
      "description": "Basic loop",
      "code": "loopAction.loopSource = new microflows.IterableList(...);"
    }
  ],
  "related_topics": ["microflows", "lists", "iteration"],
  "mendix_version": "10.0+",
  "_metadata": {
    "id": "abc123",
    "added": "2024-01-15T10:30:00Z",
    "source": "docs.mendix.com",
    "quality_score": 0.95,
    "verified": true
  }
}

Content Categories

Best Practices (best-practices.json)

Coding patterns and guidelines:

• Microflow design patterns
• Error handling strategies
• Naming conventions
• Performance optimization
• Code organization

Studio Pro (studio-pro.json)

Studio Pro features and usage:

• UI element configuration
• Modeling techniques
• Version-specific features
• Keyboard shortcuts
• Pro tips

Model SDK (model-sdk.json)

SDK programming patterns:

• Creating/modifying elements
• Navigation patterns
• Working with transactions
• Common pitfalls
• Real-world examples

Platform SDK (platform-sdk.json)

Platform operations:

• Creating apps
• Working copies
• Branch management
• Deployment operations
• Team Server integration

Troubleshooting (troubleshooting.json)

Common issues and fixes:

• Error messages explained
• Known bugs/workarounds
• Migration issues
• Performance problems

Harvested Content (harvested-*.json)

Auto-crawled from official sources:

• Release notes (10.x, 11.x)
• Documentation updates
• New feature announcements
• API changes

Quality Scoring

Every entry is automatically scored on:

Factor	Weight	Description
Completeness	30%	Has all relevant fields
Source quality	25%	Official docs score higher
Verification	20%	Manually verified entries
Freshness	15%	Recent updates preferred
Usage	10%	Frequently accessed entries

Thresholds:

• >= 0.8 - High quality, trusted
• 0.5 - 0.8 - Good quality
• < 0.5 - May need review

Coverage Statistics

Current knowledge base metrics:

Category	Entries	Coverage
Best Practices	~50	Core patterns
Studio Pro	~40	Major features
Model SDK	~60	Common operations
Platform SDK	~30	Key operations
Troubleshooting	~25	Common issues
Harvested	~100+	Auto-updated

Total: 300+ curated entries + 318 vector embeddings

Knowledge Gaps

The system tracks “missed queries” - searches that returned no results. These indicate knowledge gaps to fill.

View gaps:

@mendix-expert hello
# Shows recent missed queries in analytics

Common gaps are automatically added to the harvest priority list.

Validation

The knowledge base is automatically validated:

• Syntax errors - Invalid JSON
• Missing required fields - No title or description
• Staleness - Not updated in 6+ months
• Duplicates - Similar entries detected
• Broken references - Invalid cross-references

Run manual validation:

@mendix-expert Check the knowledge validation report
# Returns mendix://validation/report

Adding Knowledge

Manual Addition

@mendix-expert add_to_knowledge_base
  knowledge_file="best-practices"
  category="microflows"
  content='{
    "title": "My Pattern",
    "description": "How to do X",
    "when_to_use": "When you need Y"
  }'
  source="discovered through research"

Auto-Learning

When Beast Mode research discovers new information, the AI is instructed to save it:

I found this pattern in the SDK demos:
[Pattern details]

Let me save this to the knowledge base...
@mendix-expert add_to_knowledge_base ...

Harvesting

Weekly automatic harvests add fresh content from:

• docs.mendix.com
• Release notes
• API documentation

Keeping It Current

Mechanism	Frequency	What It Does
Auto-Harvest	Weekly	Crawls official docs
Self-Learning	On-demand	Saves discoveries
Validation	Daily	Flags issues
Vector Re-index	After changes	Updates embeddings

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