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README.md

Contributor Analysis Framework

Tag Categories

Area Tags

  • core: Core framework and runtime
  • client: Client implementations (Discord, Twitter, Telegram, etc.)
  • plugin: Plugin development
  • docs: Documentation
  • infra: Infrastructure (CI/CD, Docker, etc.)
  • test: Testing implementation
  • security: Security-related work
  • ui: User interface work

Role Tags

  • architect: Major architectural contributions
  • maintainer: Regular maintenance and updates
  • feature-dev: New feature development
  • bug-fix: Bug fixing
  • docs-writer: Documentation focus
  • reviewer: Code review focus
  • devops: Infrastructure and deployment

Technology Tags

  • typescript: TypeScript development
  • blockchain: Blockchain integration
  • ai: AI/ML integration
  • db: Database work
  • api: API integration

Notable Contributors Analysis

Primary Contributors

  1. ponderingdemocritus

    • Tags: architect, core, client, typescript
    • Focus: Core architecture, client implementations, and system integration
    • Key Contributions:
      • Services architecture
      • Starknet plugin development
      • Runtime improvements
      • Client refactoring

  2. lalalune

    • Tags: architect, core, client, ai
    • Focus: AI integration, client development, and core system design
    • Key Contributions:
      • Model provider abstraction
      • Twitter client upgrades
      • Core refactoring
      • Service integration

  3. bmgalego

    • Tags: feature-dev, client, typescript
    • Focus: Client implementations and core functionality
    • Key Contributions:
      • Farcaster client
      • Cache manager implementation
      • Memory system improvements

Domain Specialists

  1. MarcoMandar

    • Tags: blockchain, feature-dev
    • Focus: Trust score system and token functionality
    • Key Contributions:
      • Trust integration
      • Token provider implementation
      • Simulation services

  2. o-on-x

    • Tags: ai, feature-dev
    • Focus: AI model integration and image generation
    • Key Contributions:
      • OpenRouter integration
      • Image generation improvements
      • Model configuration

Infrastructure Contributors

  1. HashWarlock

    • Tags: infra, devops
    • Focus: Docker and deployment
    • Key Contributions:
      • Docker support
      • TEE Plugin
      • Infrastructure improvements

  2. snobbee

    • Tags: test, devops
    • Focus: Testing infrastructure and CI/CD
    • Key Contributions:
      • Test coverage implementation
      • CI workflow improvements

Analysis Script Enhancement

def analyze_contributor(contributor_data):
    """Enhanced analysis function"""
    analysis = {
        'tags': set(),
        'focus_areas': [],
        'key_contributions': [],
        'stats': {
            'commits': 0,
            'files_changed': set(),
            'lines_changed': 0
        }
    }
    
    # Analyze files and commits
    for commit in contributor_data['commits']:
        analysis['stats']['commits'] += 1
        
        for file in commit['files']:
            analysis['stats']['files_changed'].add(file)
            
            # Determine tags based on file paths
            if 'core/' in file:
                analysis['tags'].add('core')
            elif 'client/' in file:
                analysis['tags'].add('client')
            elif 'plugin/' in file:
                analysis['tags'].add('plugin')
            # Add more path-based tag logic...
            
            # Analyze commit messages for additional context
            if 'fix' in commit['title'].lower():
                analysis['tags'].add('bug-fix')
            elif 'feat' in commit['title'].lower():
                analysis['tags'].add('feature-dev')
                
    # Generate focus areas based on most touched directories
    dir_counts = {}
    for file in analysis['stats']['files_changed']:
        dir_name = file.split('/')[0]
        dir_counts[dir_name] = dir_counts.get(dir_name, 0) + 1
    
    analysis['focus_areas'] = sorted(dir_counts.items(), 
                                   key=lambda x: x[1], 
                                   reverse=True)[:3]
    
    return analysis

Recommendations for Tracking

  1. Implement automatic tagging based on:

    • File paths touched
    • Commit message keywords
    • PR labels
    • Issue involvement

  2. Track contribution metrics:

    • Commit frequency
    • Lines of code changed
    • Files touched
    • PR reviews performed
    • Documentation added

  3. Generate periodic reports:

    • Active contributors by area
    • Emerging specialists
    • Cross-domain contributors
    • Documentation coverage