daffy0208-ai-dev-standards

AI Development Standards

Version 3.1.0 | Last Updated: 2025-11-24

A comprehensive framework of specialized AI skills, MCP servers, and development tools for AI-assisted software development. Features automated validation, agent evaluation, and quality assurance.

📊 Current Resources

Total: 199 Resources

Category	Count	Description
Skills	64	Specialized AI methodologies and workflows
MCPs	51	Model Context Protocol servers (executable tools)
Tools	4	Core utility scripts
Components	75	Reusable UI and system components
Integrations	5	Third-party service connectors

MCP Coverage: 79.7% (51 MCPs supporting 64 Skills)

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✨ What's New in 3.1.0

🎯 Agent Evaluation System (Phase 5.12)

Implement Eval-Driven Development (EDD) for continuous agent quality assurance:

• Automated testing against golden datasets
• Multiple grading strategies (exact, regex, LLM-based)
• Performance metrics and regression tracking
• 100% test pass rate in validation suite

# Run agent evaluations
node scripts/run-agent-evals.js --dataset tests/fixtures/golden-dataset-example.json --mock

⚡ Two-Tier Validation System

• Quick Validation (10-30s): Registry consistency, documentation
• Full Validation (2-5min): Includes linting, type checking, tests, agent evals

npm run validate:quick  # Fast feedback
npm run validate:full   # Comprehensive checks

📚 Enhanced Documentation

• .claude/CLAUDE.md - Complete Claude Code configuration guide
• FINAL-RESOURCE-COUNTS.md - Resource tracking and metrics
• docs/VALIDATION-SYSTEM.md - Validation methodology

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🚀 Quick Start

📖 New to this repository? Check out our Installation Guide and Quick Start Guide for step-by-step instructions.

For New Projects

# Clone the repository
git clone https://github.com/daffy0208/ai-dev-standards.git
cd ai-dev-standards

# Install dependencies
npm install

# Run validation to ensure everything works
npm run validate

For Existing Projects

# Clone as a reference
git clone https://github.com/daffy0208/ai-dev-standards.git ~/ai-dev-standards

# Reference skills and patterns in your .cursorrules or .claude/claude.md
# See docs/EXISTING-PROJECTS.md for integration guide

Using with Claude Code

1. Open your project in Claude Code

2. Reference this repository in your project instructions:

   You have access to ai-dev-standards at ~/ai-dev-standards
   
   When needed, reference skills from skills/ and patterns from standards/
   Use the skill-registry.json to find relevant skills for tasks
   

3. Claude will automatically discover and use appropriate skills

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📖 What This Repository Does

Think of this as a shared knowledge base between you and Claude:

🎓 64 Specialized Skills

Methodologies Claude follows automatically:

• Product: mvp-builder, product-strategist, go-to-market-planner
• AI/ML: rag-implementer, multi-agent-architect, knowledge-graph-builder
• Development: frontend-builder, api-designer, backend-architect
• Infrastructure: deployment-advisor, security-engineer, performance-optimizer
• Design: ux-designer, visual-designer, design-system-architect
• Quality: testing-strategist, quality-auditor, agent-evaluator

🔧 51 MCP Servers

Executable tools that extend Claude's capabilities:

• Search: semantic-search-mcp, dark-matter-analyzer-mcp
• Quality: code-quality-scanner-mcp, security-scanner-mcp, test-runner-mcp
• AI/Data: vector-database-mcp, embedding-generator-mcp, knowledge-base-mcp
• Design: figma-sync-mcp, design-token-manager-mcp, theme-builder-mcp
• DevOps: deployment-orchestrator-mcp, database-migration-mcp

📐 Architecture Patterns

Proven approaches for complex systems:

• RAG architectures (Naive, Advanced, Modular)
• Multi-agent coordination patterns
• Event-driven systems
• Real-time data pipelines
• Authentication patterns

🛡️ Quality Assurance

• Automated validation system (2-tier)
• Agent evaluation framework (EDD)
• Security best practices
• Performance standards
• Accessibility guidelines

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💡 Key Features

⚡ Automated Validation

# Quick validation (10-30 seconds)
npm run validate:quick