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CODITECT UI/UX Agent Architecture

Version: 1.0
Date: January 19, 2026
Status: Design Specification
Based On: Anthropic Claude Code agent lifecycle model

Executive Summary​

This document defines the architecture for CODITECT's UI/UX agent system, modeled after Anthropic's Claude Code skill lifecycle. The system transforms CODITECT from generating "AI-looking" interfaces to producing professional, enterprise-grade UI/UX through a structured agent capability layer.

Core Innovation: Event-based agent-UI protocol with explicit lifecycle phases (Discovery → Activation → Execution → Reflection) that enables:

  • Consistent professional design output
  • Human-in-the-loop quality gates
  • Continuous improvement from user feedback
  • Reusable design system enforcement

System Architecture Overview​

High-Level Architecture​

┌─────────────────────────────────────────────────────────────────┐
│                    CODITECT Platform Layer                       │
├─────────────────────────────────────────────────────────────────┤
│                                                                  │
│  ┌────────────────┐      ┌──────────────────┐                  │
│  │  Lead Agent    │──────│  UI/UX Agent     │                  │
│  │  (Orchestrator)│      │  (Specialist)    │                  │
│  └────────────────┘      └──────────────────┘                  │
│         │                        │                               │
│         │                        │                               │
│  ┌──────▼────────────────────────▼──────────────────────────┐  │
│  │          Agent Capability Layer (Skills Registry)         │  │
│  ├───────────────────────────────────────────────────────────┤  │
│  │  • UI/UX Skills        • Design System Tools              │  │
│  │  • Commands            • Scripts & Hooks                  │  │
│  │  • Lifecycle Hooks     • Quality Gates                    │  │
│  └───────────────────────────────────────────────────────────┘  │
│         │                        │                               │
│         │                        │                               │
│  ┌──────▼────────────────────────▼──────────────────────────┐  │
│  │            Event-Based Protocol Layer                      │  │
│  ├───────────────────────────────────────────────────────────┤  │
│  │  Event Stream: skill_activation_request,                  │  │
│  │               tool_call, human_input_request,             │  │
│  │               permission_request, quality_check           │  │
│  └───────────────────────────────────────────────────────────┘  │
│         │                        │                               │
│         │                        │                               │
│  ┌──────▼────────────────────────▼──────────────────────────┐  │
│  │              Frontend/UI Rendering Layer                   │  │
│  ├───────────────────────────────────────────────────────────┤  │
│  │  • Generated UI Code    • Quality Indicators              │  │
│  │  • Design Preview       • Approval Interfaces             │  │
│  │  • HITL Controls        • Metrics Dashboard               │  │
│  └───────────────────────────────────────────────────────────┘  │
│                                                                  │
└─────────────────────────────────────────────────────────────────┘

External Integrations:
├─ Customer Design Systems (Brand Assets, Style Guides)
├─ Quality Validation Services (Accessibility, Performance)
└─ Design Tool Exports (Penpot, Figma APIs)

Core Lifecycle Model​

Phase 1: Discovery​

Purpose: Make UI/UX capabilities discoverable without loading full instructions

Implementation:

skill_registry:
  storage: /mnt/H.P.003-SKILLS/public/ui_ux/
  metadata_only_load: true  # Keep context lean
  
  H.P.003-SKILLS:
    - name: "ui_ux_agent_skill"
      description: "Professional UI/UX design with header consolidation, navigation optimization"
      tags: ["design", "frontend", "ui", "ux", "enterprise"]
      visibility: "auto-discovered"
      
    - name: "header_consolidation"
      description: "Compress multi-level headers into single navigation bar"
      tags: ["design", "navigation", "optimization"]
      visibility: "user-invocable"
      
    - name: "navigation_frequency"
      description: "Optimize navigation hierarchy based on access patterns"
      tags: ["ux", "navigation", "information-architecture"]
      visibility: "auto-discovered"
      
    - name: "design_system_generator"
      description: "Generate brand-aligned design systems from customer assets"
      tags: ["branding", "design-system", "consistency"]
      visibility: "user-invocable"
      
    - name: "quality_validation"
      description: "Validate UI against accessibility and design standards"
      tags: ["qa", "accessibility", "standards"]
      visibility: "auto-discovered"

UX Affordances:

// Contextual skill suggestions
interface SkillSuggestion {
  skill_name: string;
  reason: string;
  confidence: number;
  auto_apply?: boolean;
}

// Example: When generating dashboard UI
const suggestions: SkillSuggestion[] = [
  {
    skill_name: "ui_ux_agent_skill",
    reason: "Dashboard detected - apply professional layout patterns",
    confidence: 0.95,
    auto_apply: true
  },
  {
    skill_name: "navigation_frequency",
    reason: "Multiple navigation sections found - optimize hierarchy",
    confidence: 0.88,
    auto_apply: true
  }
];

// Slash-command palette
const H.P.002-COMMANDS = [
  { trigger: "/optimize-ui", skill: "ui_ux_agent_skill" },
  { trigger: "/compress-headers", skill: "header_consolidation" },
  { trigger: "/design-system", skill: "design_system_generator" }
];

Discovery Flow:

Phase 2: Activation & Permissions​

Purpose: Load full skill instructions only after user approval

Implementation:

interface SkillActivationRequest {
  event_type: "skill_activation_request";
  skill_name: string;
  rationale: string;
  scope: ActivationScope;
  permissions_required: Permission[];
  estimated_impact: ImpactEstimate;
}

interface ActivationScope {
  scope_type: "session" | "file" | "folder" | "project" | "customer";
  target: string;
  duration?: "one-time" | "persistent";
}

interface Permission {
  permission_type: string;
  resource: string;
  justification: string;
  risk_level: "low" | "medium" | "high";
}

interface ImpactEstimate {
  files_affected: number;
  code_changes: number;
  style_changes: number;
  breaking_changes: boolean;
}

// Example activation request
const activationRequest: SkillActivationRequest = {
  event_type: "skill_activation_request",
  skill_name: "ui_ux_agent_skill",
  rationale: "Dashboard UI requires professional header consolidation and navigation optimization to meet enterprise design standards",
  scope: {
    scope_type: "project",
    target: "avivate-financial-dashboard",
    duration: "persistent"
  },
  permissions_required: [
    {
      permission_type: "file_write",
      resource: "src/components/**/*.tsx",
      justification: "Rewrite UI components to apply design patterns",
      risk_level: "medium"
    },
    {
      permission_type: "style_modification",
      resource: "src/styles/**/*.css",
      justification: "Apply design system tokens and consolidated styles",
      risk_level: "low"
    }
  ],
  estimated_impact: {
    files_affected: 12,
    code_changes: 350,
    style_changes: 120,
    breaking_changes: false
  }
};

UX Prompt Example:

┌─────────────────────────────────────────────────────────────┐
│ 🎨 Skill Activation Request                                 │
├─────────────────────────────────────────────────────────────┤
│                                                             │
│ Skill: UI/UX Agent (Professional Design)                   │
│                                                             │
│ Why: Dashboard UI requires professional header             │
│      consolidation and navigation optimization to meet     │
│      enterprise design standards                           │
│                                                             │
│ Scope: Entire project (avivate-financial-dashboard)        │
│                                                             │
│ Permissions Required:                                       │
│   ⚠️ Modify UI components (12 files, ~350 changes)         │
│   ✓ Update styles (120 changes)                            │
│                                                             │
│ Impact: Medium - Will restructure navigation and headers   │
│         No breaking changes expected                       │
│                                                             │
│ ┌──────────┐  ┌──────────┐  ┌────────────────────┐        │
│ │ Approve  │  │  Deny    │  │ Limit to Dashboard │        │
│ └──────────┘  └──────────┘  └────────────────────┘        │
│                                                             │
└─────────────────────────────────────────────────────────────┘

Approval Workflow:

class SkillActivationManager:
    """Manages skill activation and permission negotiation."""
    
    def __init__(self):
        self.pending_activations: Dict[str, SkillActivationRequest] = {}
        self.active_H.P.003-SKILLS: Dict[str, ActivatedSkill] = {}
        self.user_preferences: ActivationPreferences = None
    
    async def request_activation(
        self,
        skill_name: str,
        context: ExecutionContext
    ) -> ActivationResponse:
        """Request skill activation with context-aware permissions."""
        
        # Build activation request
        request = SkillActivationRequest(
            skill_name=skill_name,
            rationale=self.generate_rationale(skill_name, context),
            scope=self.determine_scope(context),
            permissions_required=self.calculate_permissions(skill_name),
            estimated_impact=self.estimate_impact(skill_name, context)
        )
        
        # Check user preferences for auto-approval
        if self.should_auto_approve(request):
            return await self.activate_skill(skill_name, request.scope)
        
        # Request human approval
        self.pending_activations[request.id] = request
        await self.emit_event({
            "event_type": "skill_activation_request",
            "request": request
        })
        
        # Wait for user decision
        response = await self.wait_for_approval(request.id)
        
        if response.approved:
            return await self.activate_skill(
                skill_name,
                response.approved_scope or request.scope
            )
        else:
            return ActivationResponse(
                approved=False,
                reason=response.reason
            )
    
    async def activate_skill(
        self,
        skill_name: str,
        scope: ActivationScope
    ) -> ActivationResponse:
        """Activate skill and load full instructions."""
        
        # Load full skill from registry
        skill = await self.skill_registry.load_full_skill(skill_name)
        
        # Apply scope constraints
        skill.apply_scope(scope)
        
        # Register activated skill
        self.active_H.P.003-SKILLS[skill_name] = ActivatedSkill(
            skill=skill,
            scope=scope,
            activated_at=time.time()
        )
        
        # Load associated H.P.005-HOOKS
        await self.hook_manager.register_H.P.005-HOOKS(skill.H.P.005-HOOKS, scope)
        
        return ActivationResponse(
            approved=True,
            skill=skill,
            scope=scope
        )

Phase 3: Execution & Monitoring​

Purpose: Execute with visible intermediate steps and quality gates

Implementation:

// Event stream for execution monitoring
interface ExecutionEvent {
  event_type: 
    | "tool_call"
    | "tool_result"
    | "hook_triggered"
    | "quality_check"
    | "human_input_request"
    | "skill_step_complete"
    | "skill_complete";
  
  timestamp: number;
  skill_name?: string;
  details: Record<string, any>;
}

// Tool execution with streaming
interface ToolExecution {
  tool_name: string;
  input: Record<string, any>;
  streaming: boolean;
  
  // Hook points
  pre_execution_hook?: string;
  post_execution_hook?: string;
  
  // Quality gates
  quality_checks?: QualityCheck[];
}

// Example execution flow
class UIUXExecutor {
  async execute_ui_generation(
    requirements: UIRequirements,
    active_H.P.003-SKILLS: ActivatedSkill[]
  ): Promise<UIOutput> {
    
    // Phase 1: Header consolidation
    await this.emit_event({
      event_type: "skill_step_complete",
      skill_name: "header_consolidation",
      details: { step: "analyzing_current_headers" }
    });
    
    const header_analysis = await this.tools.analyze_headers(
      requirements.current_ui
    );
    
    await this.emit_event({
      event_type: "tool_result",
      details: {
        tool: "analyze_headers",
        result: header_analysis,
        finding: `Found ${header_analysis.header_count} nested headers`
      }
    });
    
    // Trigger quality check
    const quality_result = await this.quality_gates.check(
      "header_count",
      header_analysis
    );
    
    await this.emit_event({
      event_type: "quality_check",
      details: {
        check: "header_count",
        passed: quality_result.passed,
        threshold: quality_result.threshold,
        actual: quality_result.actual
      }
    });
    
    // Phase 2: Navigation optimization
    await this.emit_event({
      event_type: "skill_step_complete",
      skill_name: "navigation_frequency",
      details: { step: "calculating_access_patterns" }
    });
    
    const navigation_plan = await this.tools.optimize_navigation(
      requirements.sections,
      requirements.user_personas
    );
    
    // Human-in-loop checkpoint for critical changes
    if (navigation_plan.requires_approval) {
      const approval = await this.request_human_input({
        event_type: "human_input_request",
        reason: "Navigation restructuring will change user flow",
        options: ["Approve", "Modify", "Skip"],
        details: navigation_plan
      });
      
      if (approval.response !== "Approve") {
        navigation_plan = await this.modify_navigation_plan(
          navigation_plan,
          approval.feedback
        );
      }
    }
    
    // Phase 3: Design system application
    const design_system = await this.load_design_system(
      requirements.customer_id
    );
    
    const styled_ui = await this.tools.apply_design_system(
      base_ui,
      design_system
    );
    
    // Final quality validation
    const final_validation = await this.quality_gates.validate_all(
      styled_ui
    );
    
    await this.emit_event({
      event_type: "skill_complete",
      skill_name: "ui_ux_agent_skill",
      details: {
        quality_score: final_validation.score,
        improvements: final_validation.improvements,
        files_generated: styled_ui.files.length
      }
    });
    
    return styled_ui;
  }
}

Visual Monitoring UI:

┌─────────────────────────────────────────────────────────────┐
│ 🎨 UI/UX Generation Progress                                │
├─────────────────────────────────────────────────────────────┤
│                                                             │
│ ✓ Header Consolidation                         [2.3s]      │
│   ├─ Analyzed 4 nested headers                             │
│   ├─ Compressed to 1 navigation bar                        │
│   └─ ✓ Quality: Header height < 100px                      │
│                                                             │
│ ⚙️ Navigation Optimization                     [in progress]│
│   ├─ Calculated access frequency patterns                  │
│   ├─ Projects: Daily (landing page)                        │
│   ├─ Settings: Monthly (nested)                            │
│   └─ ⏸️ Awaiting approval for restructuring                │
│                                                             │
│ ⏳ Design System Application                   [pending]    │
│                                                             │
│ ⏳ Quality Validation                          [pending]    │
│                                                             │
└─────────────────────────────────────────────────────────────┘

┌─────────────────────────────────────────────────────────────┐
│ 🔍 Quality Checks                                           │
├─────────────────────────────────────────────────────────────┤
│ ✓ Header count: 1 (target: ≤1)                             │
│ ✓ Navigation depth: 2 (target: ≤2)                         │
│ ✓ Accessibility: WCAG AA (target: AA)                      │
│ ⚠️ Visual complexity: 3.2 (target: ≤3.0)                   │
└─────────────────────────────────────────────────────────────┘

Phase 4: Reflection & Learning​

Purpose: Capture improvements and update H.P.003-SKILLS based on feedback

Implementation:

interface SkillReflection {
  skill_name: string;
  execution_id: string;
  outcomes: ExecutionOutcome;
  user_feedback: UserFeedback;
  proposed_updates: SkillUpdate[];
}

interface ExecutionOutcome {
  success: boolean;
  quality_score: number;
  user_satisfaction: number;
  issues_encountered: Issue[];
  improvements_identified: Improvement[];
}

interface UserFeedback {
  rating: number;  // 1-10
  comments: string;
  specific_likes: string[];
  specific_dislikes: string[];
  correction_applied: boolean;
}

interface SkillUpdate {
  update_type: "rule_addition" | "rule_modification" | "example_addition";
  section: string;
  current_content: string;
  proposed_content: string;
  rationale: string;
  confidence: number;
}

class SkillLearningEngine {
  async reflect_on_execution(
    skill_name: string,
    execution_context: ExecutionContext,
    user_feedback: UserFeedback
  ): Promise<SkillReflection> {
    
    // Analyze what worked and what didn't
    const analysis = await this.analyze_execution(
      execution_context,
      user_feedback
    );
    
    // Generate proposed updates
    const proposed_updates = await this.generate_skill_updates(
      skill_name,
      analysis
    );
    
    // Create reflection
    const reflection: SkillReflection = {
      skill_name,
      execution_id: execution_context.id,
      outcomes: analysis.outcomes,
      user_feedback,
      proposed_updates
    };
    
    // If high-confidence updates, propose to user
    const high_confidence_updates = proposed_updates.filter(
      u => u.confidence > 0.85
    );
    
    if (high_confidence_updates.length > 0) {
      await this.propose_skill_updates(
        skill_name,
        high_confidence_updates
      );
    }
    
    // Store reflection for future learning
    await this.reflection_store.save(reflection);
    
    return reflection;
  }
  
  async propose_skill_updates(
    skill_name: string,
    updates: SkillUpdate[]
  ): Promise<void> {
    
    await this.emit_event({
      event_type: "skill_update_proposal",
      skill_name,
      updates: updates.map(u => ({
        section: u.section,
        change_preview: this.generate_diff(
          u.current_content,
          u.proposed_content
        ),
        rationale: u.rationale,
        confidence: u.confidence
      }))
    });
  }
}

User Feedback Collection:

┌─────────────────────────────────────────────────────────────┐
│ 📊 Rate This UI Generation                                  │
├─────────────────────────────────────────────────────────────┤
│                                                             │
│ Overall Quality: ⭐⭐⭐⭐⭐⭐⭐⭐⚪⚪ (8/10)                     │
│                                                             │
│ What worked well?                                           │
│ ☑ Header consolidation                                     │
│ ☑ Navigation organization                                  │
│ ☐ Visual design                                             │
│ ☑ Accessibility                                             │
│                                                             │
│ What needs improvement?                                     │
│ ☐ Color contrast too low                                   │
│ ☑ Spacing inconsistent in cards                            │
│ ☐ Icons too large                                           │
│                                                             │
│ Additional comments:                                        │
│ ┌─────────────────────────────────────────────────────┐   │
│ │ The header compression worked great, but the card   │   │
│ │ spacing feels uneven. Some cards have 16px padding  │   │
│ │ while others have 24px.                              │   │
│ └─────────────────────────────────────────────────────┘   │
│                                                             │
│ [ Submit Feedback ]                                         │
│                                                             │
└─────────────────────────────────────────────────────────────┘

Skill Update Proposal UI:

┌─────────────────────────────────────────────────────────────┐
│ 🔄 Proposed Skill Update                                    │
├─────────────────────────────────────────────────────────────┤
│                                                             │
│ Skill: ui_ux_agent_skill                                    │
│ Section: Card Component Spacing                            │
│ Confidence: 92%                                             │
│                                                             │
│ Based on 3 instances of user feedback about inconsistent   │
│ card spacing, propose adding this rule:                    │
│                                                             │
│ ┌───────────────────────────────────────────────────────┐ │
│ │ - card:                                               │ │
│ │     padding: 24                                       │ │
│ │ +   padding: 24  # Standardize to 24px               │ │
│ │ +   enforce_consistency: true  # Validate all cards  │ │
│ └───────────────────────────────────────────────────────┘ │
│                                                             │
│ This will ensure all card components use consistent 24px   │
│ padding and automatically flag violations during QA.       │
│                                                             │
│ ┌──────────┐  ┌──────────┐  ┌────────────┐               │
│ │ Accept   │  │  Reject  │  │  Preview   │               │
│ └──────────┘  └──────────┘  └────────────┘               │
│                                                             │
└─────────────────────────────────────────────────────────────┘

Skills, Commands, Tools, Scripts, Hooks​

Skill Structure​

skill_definition:
  metadata:
    name: "ui_ux_agent_skill"
    version: "1.0.0"
    description: "Professional UI/UX design patterns"
    author: "CODITECT"
    tags: ["design", "ui", "ux", "enterprise"]
    visibility: "auto-discovered"
  
  instructions:
    file: "SKILL.md"
    sections:
      - header_consolidation
      - navigation_optimization
      - visual_design_principles
      - content_prioritization
      - design_system_application
  
  H.P.005-HOOKS:
    pre_generation:
      - validate_requirements
      - load_design_system
    
    post_generation:
      - quality_validation
      - accessibility_check
    
    on_error:
      - rollback_changes
      - notify_user
  
  H.P.004-SCRIPTS:
    - name: "generate_design_system"
      path: "H.P.004-SCRIPTS/design_system_generator.py"
      parameters:
        - logo_path
        - brand_colors
        - industry
    
    - name: "validate_accessibility"
      path: "H.P.004-SCRIPTS/wcag_validator.js"
      parameters:
        - html_content
        - wcag_level
  
  tools:
    - name: "analyze_headers"
      type: "analysis"
      input_schema: { ui_code: "string" }
      output_schema: { header_count: "int", structure: "object" }
    
    - name: "optimize_navigation"
      type: "transformation"
      input_schema: { sections: "array", personas: "array" }
      output_schema: { navigation_tree: "object", priority_map: "object" }
    
    - name: "apply_design_system"
      type: "generation"
      input_schema: { base_ui: "string", design_system: "object" }
      output_schema: { styled_ui: "string", applied_tokens: "array" }
  
  quality_gates:
    - name: "header_count"
      threshold: 1
      severity: "error"
    
    - name: "navigation_depth"
      threshold: 2
      severity: "warning"
    
    - name: "wcag_aa_compliance"
      threshold: "pass"
      severity: "error"
    
    - name: "visual_complexity"
      threshold: 3.0
      severity: "warning"

Commands (User-Invocable)​

// Command registry
const H.P.002-COMMANDS: Command[] = [
  {
    id: "optimize-ui",
    name: "Optimize UI/UX",
    description: "Apply professional design patterns to current UI",
    category: "design",
    shortcut: "Cmd+Shift+U",
    skill: "ui_ux_agent_skill",
    parameters: []
  },
  {
    id: "compress-headers",
    name: "Compress Headers",
    description: "Consolidate multiple headers into single navigation",
    category: "design",
    shortcut: "Cmd+Shift+H",
    skill: "header_consolidation",
    parameters: []
  },
  {
    id: "optimize-navigation",
    name: "Optimize Navigation",
    description: "Reorganize navigation based on access frequency",
    category: "ux",
    skill: "navigation_frequency",
    parameters: [
      {
        name: "user_persona",
        type: "select",
        options: ["manager", "developer", "end_user"],
        default: "manager"
      }
    ]
  },
  {
    id: "generate-design-system",
    name: "Generate Design System",
    description: "Create brand-aligned design system from assets",
    category: "branding",
    skill: "design_system_generator",
    parameters: [
      {
        name: "logo_file",
        type: "file",
        accept: ".svg,.png"
      },
      {
        name: "brand_color",
        type: "color"
      }
    ]
  },
  {
    id: "validate-quality",
    name: "Validate UI Quality",
    description: "Run all quality checks on current UI",
    category: "qa",
    skill: "quality_validation",
    parameters: []
  }
];

// Command palette implementation
class CommandPalette {
  private H.P.002-COMMANDS: Command[];
  private fuzzy_matcher: FuzzyMatcher;
  
  search(query: string): Command[] {
    return this.fuzzy_matcher.match(query, this.H.P.002-COMMANDS, {
      keys: ["name", "description", "tags"],
      threshold: 0.6
    });
  }
  
  async execute(command_id: string, parameters: Record<string, any>): Promise<void> {
    const command = this.H.P.002-COMMANDS.find(c => c.id === command_id);
    
    if (!command) {
      throw new Error(`Command ${command_id} not found`);
    }
    
    // Request skill activation
    const activation = await this.skill_manager.request_activation(
      command.skill,
      { trigger: "user_command", parameters }
    );
    
    if (activation.approved) {
      await this.execute_skill(command.skill, parameters);
    }
  }
}

Tools & Programmatic Tool Use​

from typing import Protocol, Dict, Any, List
from dataclasses import dataclass

class Tool(Protocol):
    """Base protocol for all UI/UX tools."""
    
    name: str
    description: str
    input_schema: Dict[str, Any]
    output_schema: Dict[str, Any]
    
    async def execute(self, **kwargs) -> Dict[str, Any]:
        """Execute the tool with given parameters."""
        ...

@dataclass
class ToolExecution:
    """Tool execution context with error handling."""
    
    tool: Tool
    input: Dict[str, Any]
    dry_run: bool = False
    preview: bool = False
    
    async def execute(self) -> Dict[str, Any]:
        """Execute with safety checks."""
        
        # Validate input
        if not self.validate_input(self.input):
            raise ValueError("Invalid input for tool")
        
        # Dry run mode
        if self.dry_run:
            return await self.tool.simulate(**self.input)
        
        # Preview mode
        if self.preview:
            return await self.tool.preview(**self.input)
        
        # Actual execution
        try:
            result = await self.tool.execute(**self.input)
            return result
        except Exception as e:
            # Error surface
            return {
                "success": False,
                "error": str(e),
                "recovery_suggestions": self.generate_recovery_suggestions(e)
            }

# Example: Header analysis tool
class HeaderAnalysisTool:
    """Analyzes header structure in UI code."""
    
    name = "analyze_headers"
    description = "Analyze nested header structure and identify consolidation opportunities"
    
    input_schema = {
        "ui_code": {"type": "string", "required": True},
        "framework": {"type": "string", "enum": ["react", "vue", "html"], "default": "react"}
    }
    
    output_schema = {
        "header_count": {"type": "integer"},
        "nesting_depth": {"type": "integer"},
        "structure": {"type": "object"},
        "consolidation_opportunities": {"type": "array"}
    }
    
    async def execute(self, ui_code: str, framework: str = "react") -> Dict[str, Any]:
        """Analyze header structure."""
        
        # Parse UI code
        ast = self.parse_ui_code(ui_code, framework)
        
        # Find all header elements
        headers = self.extract_headers(ast)
        
        # Analyze nesting
        structure = self.build_header_tree(headers)
        
        # Identify consolidation opportunities
        opportunities = self.find_consolidation_opportunities(structure)
        
        return {
            "header_count": len(headers),
            "nesting_depth": self.calculate_depth(structure),
            "structure": structure,
            "consolidation_opportunities": opportunities,
            "recommendation": self.generate_recommendation(opportunities)
        }
    
    def find_consolidation_opportunities(self, structure: Dict) -> List[Dict]:
        """Identify where headers can be consolidated."""
        
        opportunities = []
        
        # Check for multiple top-level headers
        if structure.get("top_level_count", 0) > 1:
            opportunities.append({
                "type": "multiple_top_headers",
                "current": structure["top_level_count"],
                "target": 1,
                "action": "Merge into single navigation bar"
            })
        
        # Check for redundant breadcrumb + page title
        if structure.get("has_breadcrumb") and structure.get("has_page_title"):
            opportunities.append({
                "type": "redundant_breadcrumb",
                "action": "Remove breadcrumb or integrate into top nav"
            })
        
        # Check for excessive nesting
        if structure.get("max_depth", 0) > 2:
            opportunities.append({
                "type": "excessive_nesting",
                "current_depth": structure["max_depth"],
                "target_depth": 2,
                "action": "Flatten header hierarchy"
            })
        
        return opportunities

# Tool chaining
class ToolChain:
    """Chain multiple tools together."""
    
    def __init__(self):
        self.tools: Dict[str, Tool] = {}
        self.execution_graph: Dict[str, List[str]] = {}
    
    def add_tool(self, tool: Tool):
        """Register a tool."""
        self.tools[tool.name] = tool
    
    def define_chain(self, chain: List[str]):
        """Define a sequence of tools to execute."""
        for i in range(len(chain) - 1):
            current = chain[i]
            next_tool = chain[i + 1]
            
            if current not in self.execution_graph:
                self.execution_graph[current] = []
            
            self.execution_graph[current].append(next_tool)
    
    async def execute_chain(
        self,
        start_tool: str,
        initial_input: Dict[str, Any]
    ) -> Dict[str, Any]:
        """Execute a chain of tools."""
        
        result = initial_input
        current = start_tool
        
        while current:
            tool = self.tools[current]
            result = await tool.execute(**result)
            
            # Get next tool in chain
            next_tools = self.execution_graph.get(current, [])
            current = next_tools[0] if next_tools else None
        
        return result

# Example chain: Complete UI optimization
ui_optimization_chain = [
    "analyze_headers",
    "consolidate_headers",
    "analyze_navigation",
    "optimize_navigation",
    "apply_design_system",
    "validate_quality"
]

Scripts & Automation​

#!/bin/bash
# H.P.004-SCRIPTS/generate_design_system.sh
# Generate design system from brand assets

set -e

LOGO_PATH=$1
BRAND_COLOR=$2
INDUSTRY=${3:-"general"}
OUTPUT_DIR=${4:-"/mnt/user-data/outputs"}

echo "🎨 Generating design system..."

# Extract colors from logo
echo "📊 Analyzing logo colors..."
python3 /home/claude/H.P.004-SCRIPTS/extract_logo_colors.py \
  --logo "$LOGO_PATH" \
  --output "$OUTPUT_DIR/extracted_colors.json"

# Generate color palette
echo "🌈 Generating color palette..."
python3 /home/claude/H.P.004-SCRIPTS/generate_color_palette.py \
  --base-color "$BRAND_COLOR" \
  --extracted-colors "$OUTPUT_DIR/extracted_colors.json" \
  --output "$OUTPUT_DIR/color_palette.json"

# Select typography
echo "🔤 Selecting typography..."
python3 /home/claude/H.P.004-SCRIPTS/select_typography.py \
  --industry "$INDUSTRY" \
  --output "$OUTPUT_DIR/typography.json"

# Generate component library
echo "🧩 Generating components..."
python3 /home/claude/H.P.004-SCRIPTS/generate_components.py \
  --colors "$OUTPUT_DIR/color_palette.json" \
  --typography "$OUTPUT_DIR/typography.json" \
  --output "$OUTPUT_DIR/components.json"

# Compile design system
echo "📦 Compiling design system..."
python3 /home/claude/H.P.004-SCRIPTS/compile_design_system.py \
  --colors "$OUTPUT_DIR/color_palette.json" \
  --typography "$OUTPUT_DIR/typography.json" \
  --components "$OUTPUT_DIR/components.json" \
  --output "$OUTPUT_DIR/design_system.yaml"

# Validate accessibility
echo "✓ Validating accessibility..."
python3 /home/claude/H.P.004-SCRIPTS/validate_design_system.py \
  --design-system "$OUTPUT_DIR/design_system.yaml" \
  --wcag-level "AA"

echo "✅ Design system generated: $OUTPUT_DIR/design_system.yaml"
# H.P.004-SCRIPTS/validate_accessibility.py
# WCAG accessibility validation

from typing import Dict, List
import re

class AccessibilityValidator:
    """Validate UI against WCAG standards."""
    
    WCAG_AA_CONTRAST = {
        "normal_text": 4.5,
        "large_text": 3.0,
        "ui_components": 3.0
    }
    
    def validate_color_contrast(
        self,
        foreground: str,
        background: str,
        text_size: str = "normal"
    ) -> Dict:
        """Validate color contrast ratio."""
        
        ratio = self.calculate_contrast_ratio(foreground, background)
        
        if text_size == "large":
            threshold = self.WCAG_AA_CONTRAST["large_text"]
        else:
            threshold = self.WCAG_AA_CONTRAST["normal_text"]
        
        return {
            "ratio": ratio,
            "threshold": threshold,
            "passed": ratio >= threshold,
            "level": "AA" if ratio >= threshold else "fail"
        }
    
    def validate_ui_code(self, html_content: str) -> Dict:
        """Comprehensive UI validation."""
        
        issues = []
        
        # Check for missing alt text
        img_tags = re.findall(r'<img[^>]*>', html_content)
        for img in img_tags:
            if 'alt=' not in img:
                issues.append({
                    "type": "missing_alt_text",
                    "severity": "error",
                    "element": img
                })
        
        # Check for proper heading hierarchy
        headings = re.findall(r'<h([1-6])[^>]*>', html_content)
        if headings and headings[0] != '1':
            issues.append({
                "type": "invalid_heading_hierarchy",
                "severity": "warning",
                "message": "First heading should be h1"
            })
        
        # Check for form labels
        inputs = re.findall(r'<input[^>]*>', html_content)
        for input_tag in inputs:
            if 'aria-label=' not in input_tag and 'id=' not in input_tag:
                issues.append({
                    "type": "missing_form_label",
                    "severity": "error",
                    "element": input_tag
                })
        
        return {
            "passed": len([i for i in issues if i["severity"] == "error"]) == 0,
            "issues": issues,
            "score": self.calculate_accessibility_score(issues)
        }

Hooks (Lifecycle Integration)​

// Hook types
type HookType = 
  | "PreToolUse"
  | "PostToolUse"
  | "PreSkillActivation"
  | "PostSkillActivation"
  | "OnError"
  | "OnComplete";

interface Hook {
  type: HookType;
  name: string;
  handler: (context: HookContext) => Promise<HookResult>;
  scope: "session" | "skill" | "tool";
  enabled: boolean;
}

interface HookContext {
  event: string;
  data: Record<string, any>;
  metadata: Record<string, any>;
}

interface HookResult {
  continue: boolean;
  modified_data?: Record<string, any>;
  messages?: string[];
}

// Hook manager
class HookManager {
  private H.P.005-HOOKS: Map<HookType, Hook[]> = new Map();
  
  register(hook: Hook): void {
    if (!this.H.P.005-HOOKS.has(hook.type)) {
      this.H.P.005-HOOKS.set(hook.type, []);
    }
    this.H.P.005-HOOKS.get(hook.type)!.push(hook);
  }
  
  async trigger(
    hook_type: HookType,
    context: HookContext
  ): Promise<HookResult> {
    
    const H.P.005-HOOKS = this.H.P.005-HOOKS.get(hook_type) || [];
    const enabled_H.P.005-HOOKS = H.P.005-HOOKS.filter(h => h.enabled);
    
    let result: HookResult = { continue: true };
    
    for (const hook of enabled_H.P.005-HOOKS) {
      const hook_result = await hook.handler(context);
      
      if (!hook_result.continue) {
        return hook_result;
      }
      
      if (hook_result.modified_data) {
        context.data = { ...context.data, ...hook_result.modified_data };
      }
      
      result.messages = [...(result.messages || []), ...(hook_result.messages || [])];
    }
    
    return result;
  }
}

// Example H.P.005-HOOKS
const H.P.005-HOOKS: Hook[] = [
  {
    type: "PreToolUse",
    name: "validate_design_system_loaded",
    scope: "skill",
    enabled: true,
    handler: async (context) => {
      // Ensure design system is loaded before applying
      if (context.data.tool === "apply_design_system") {
        if (!context.data.design_system) {
          return {
            continue: false,
            messages: ["Design system not loaded. Loading customer design system..."]
          };
        }
      }
      return { continue: true };
    }
  },
  {
    type: "PostToolUse",
    name: "quality_check_ui_output",
    scope: "skill",
    enabled: true,
    handler: async (context) => {
      // Automatically run quality checks after UI generation
      if (context.data.tool === "generate_ui") {
        const quality_result = await runQualityChecks(context.data.output);
        
        if (!quality_result.passed) {
          return {
            continue: false,
            messages: ["Quality checks failed. Refining output..."],
            modified_data: { needs_refinement: true }
          };
        }
      }
      return { continue: true };
    }
  },
  {
    type: "OnError",
    name: "rollback_on_failure",
    scope: "session",
    enabled: true,
    handler: async (context) => {
      // Rollback changes if error occurs
      await rollbackChanges(context.data.session_id);
      return {
        continue: false,
        messages: ["Error occurred. Changes rolled back."]
      };
    }
  }
];

Event-Based Protocol (Agent ↔ UI Communication)​

Protocol Definition​

// Core event types
type EventType =
  | "message"                    // Chat message
  | "tool_call"                  // Tool invocation
  | "tool_result"                // Tool output
  | "skill_activation_request"   // Request to activate skill
  | "skill_activated"            // Skill activated
  | "permission_request"         // Permission needed
  | "permission_granted"         // Permission approved
  | "layout_update"              // UI layout change
  | "human_input_request"        // Need user input
  | "human_input_received"       // User provided input
  | "action_guard"               // High-risk action approval
  | "memory_update"              // Agent learned something
  | "quality_check"              // Quality validation result
  | "progress_update"            // Execution progress
  | "error"                      // Error occurred
  | "complete";                  // Task complete

interface AgentEvent {
  event_type: EventType;
  event_id: string;
  timestamp: number;
  session_id: string;
  skill_name?: string;
  data: Record<string, any>;
  metadata?: Record<string, any>;
}

// Event stream
interface EventStream {
  subscribe(
    event_type: EventType | EventType[],
    handler: (event: AgentEvent) => void
  ): () => void;
  
  publish(event: AgentEvent): void;
  
  replay(session_id: string): AgentEvent[];
}

// WebSocket transport
class WebSocketEventStream implements EventStream {
  private ws: WebSocket;
  private handlers: Map<EventType, Set<(event: AgentEvent) => void>>;
  private event_buffer: AgentEvent[] = [];
  
  constructor(url: string) {
    this.ws = new WebSocket(url);
    this.handlers = new Map();
    
    this.ws.onmessage = (msg) => {
      const event: AgentEvent = JSON.parse(msg.data);
      this.event_buffer.push(event);
      this.dispatch(event);
    };
  }
  
  subscribe(
    event_type: EventType | EventType[],
    handler: (event: AgentEvent) => void
  ): () => void {
    
    const types = Array.isArray(event_type) ? event_type : [event_type];
    
    types.forEach(type => {
      if (!this.handlers.has(type)) {
        this.handlers.set(type, new Set());
      }
      this.handlers.get(type)!.add(handler);
    });
    
    // Return unsubscribe function
    return () => {
      types.forEach(type => {
        this.handlers.get(type)?.delete(handler);
      });
    };
  }
  
  publish(event: AgentEvent): void {
    this.ws.send(JSON.stringify(event));
  }
  
  private dispatch(event: AgentEvent): void {
    const handlers = this.handlers.get(event.event_type) || new Set();
    handlers.forEach(handler => handler(event));
  }
  
  replay(session_id: string): AgentEvent[] {
    return this.event_buffer.filter(e => e.session_id === session_id);
  }
}

Frontend Integration​

// React hook for event stream
function useAgentEventStream(session_id: string) {
  const [events, setEvents] = useState<AgentEvent[]>([]);
  const [stream] = useState(() => new WebSocketEventStream(WS_URL));
  
  useEffect(() => {
    // Subscribe to all events for this session
    const unsubscribe = stream.subscribe(
      [
        "message",
        "tool_call",
        "tool_result",
        "skill_activation_request",
        "human_input_request",
        "quality_check",
        "progress_update",
        "complete"
      ],
      (event) => {
        if (event.session_id === session_id) {
          setEvents(prev => [...prev, event]);
        }
      }
    );
    
    return unsubscribe;
  }, [session_id, stream]);
  
  return { events, stream };
}

// UI component
function AgentExecutionView({ session_id }: { session_id: string }) {
  const { events, stream } = useAgentEventStream(session_id);
  
  const handleApproval = (event_id: string, approved: boolean) => {
    stream.publish({
      event_type: "permission_granted",
      event_id: generateEventId(),
      timestamp: Date.now(),
      session_id,
      data: { original_event_id: event_id, approved }
    });
  };
  
  return (
    <div className="execution-view">
      {events.map(event => (
        <EventRenderer 
          key={event.event_id}
          event={event}
          onApproval={handleApproval}
        />
      ))}
    </div>
  );
}

// Event renderer
function EventRenderer({ event, onApproval }: EventRendererProps) {
  switch (event.event_type) {
    case "message":
      return <ChatMessage message={event.data.content} />;
    
    case "tool_call":
      return (
        <ToolCallCard
          tool={event.data.tool_name}
          input={event.data.input}
        />
      );
    
    case "skill_activation_request":
      return (
        <SkillActivationPrompt
          request={event.data}
          onApprove={() => onApproval(event.event_id, true)}
          onDeny={() => onApproval(event.event_id, false)}
        />
      );
    
    case "human_input_request":
      return (
        <HumanInputPrompt
          request={event.data}
          onSubmit={(response) => {
            // Submit user input back to agent
          }}
        />
      );
    
    case "quality_check":
      return (
        <QualityCheckResult
          check={event.data.check}
          result={event.data.result}
        />
      );
    
    case "progress_update":
      return (
        <ProgressIndicator
          current={event.data.current}
          total={event.data.total}
          message={event.data.message}
        />
      );
    
    default:
      return null;
  }
}

Human-in-the-Loop (HITL) Patterns​

Interaction Modes​

// Co-planning mode
interface TaskPlan {
  steps: TaskStep[];
  estimated_duration: number;
  risk_level: "low" | "medium" | "high";
}

interface TaskStep {
  id: string;
  description: string;
  tools: string[];
  estimated_duration: number;
  requires_approval: boolean;
  dependencies: string[];
}

class CoPlanningInterface {
  async propose_plan(plan: TaskPlan): Promise<TaskPlan> {
    // Show plan to user with editable steps
    await this.emit_event({
      event_type: "human_input_request",
      data: {
        request_type: "plan_approval",
        plan,
        actions: ["approve", "edit", "reject"]
      }
    });
    
    const response = await this.wait_for_user_input();
    
    if (response.action === "edit") {
      // User modified the plan
      return response.modified_plan;
    } else if (response.action === "approve") {
      return plan;
    } else {
      throw new Error("Plan rejected by user");
    }
  }
  
  render_plan_editor(plan: TaskPlan): ReactElement {
    return (
      <PlanEditor
        steps={plan.steps}
        onReorder={(new_order) => this.reorderSteps(new_order)}
        onEdit={(step_id, new_step) => this.editStep(step_id, new_step)}
        onDelete={(step_id) => this.deleteStep(step_id)}
        onApprove={() => this.approvePlan(plan)}
      />
    );
  }
}

// Action guards for high-risk operations
const ACTION_GUARDS = {
  file_write: {
    paths: ["/src/**/*.tsx", "/src/**/*.css"],
    requires_approval: true,
    approval_message: "About to modify UI components. Review changes?"
  },
  
  design_system_change: {
    requires_approval: true,
    approval_message: "This will update design system affecting all pages. Continue?"
  },
  
  navigation_restructure: {
    requires_approval: true,
    approval_message: "Navigation changes will affect user flow. Approve restructuring?"
  }
};

class ActionGuardManager {
  async check_guard(
    action: string,
    context: Record<string, any>
  ): Promise<boolean> {
    
    const guard = ACTION_GUARDS[action];
    
    if (!guard || !guard.requires_approval) {
      return true;
    }
    
    await this.emit_event({
      event_type: "action_guard",
      data: {
        action,
        message: guard.approval_message,
        context,
        risk_assessment: this.assess_risk(action, context)
      }
    });
    
    const response = await this.wait_for_approval();
    return response.approved;
  }
}

HumanInputRequest UX​

interface HumanInputRequest {
  event_type: "human_input_request";
  request_id: string;
  reason: string;
  input_type: "approval" | "choice" | "freeform" | "review";
  options?: string[];
  default_value?: string;
  timeout_seconds?: number;
  deferrable?: boolean;
  context: Record<string, any>;
}

// Example: Review UI changes before applying
const review_request: HumanInputRequest = {
  event_type: "human_input_request",
  request_id: generateId(),
  reason: "Review consolidated header before applying",
  input_type: "review",
  options: ["Apply", "Modify", "Reject"],
  default_value: "Apply",
  timeout_seconds: 300,
  deferrable: true,
  context: {
    before_preview: "<!-- Current header structure -->",
    after_preview: "<!-- Consolidated header structure -->",
    changes_summary: {
      headers_removed: 3,
      navigation_items_moved: 5,
      height_reduction_px: 320
    }
  }
};

// UI Component
function ReviewChangesModal({ request }: { request: HumanInputRequest }) {
  const [selected, setSelected] = useState(request.default_value);
  
  return (
    <Modal title="Review Changes">
      <div className="split-view">
        <div className="before">
          <h3>Current</h3>
          <CodePreview code={request.context.before_preview} />
        </div>
        
        <div className="after">
          <h3>After Changes</h3>
          <CodePreview code={request.context.after_preview} />
        </div>
      </div>
      
      <div className="changes-summary">
        <h4>Summary</h4>
        <ul>
          <li>Headers removed: {request.context.changes_summary.headers_removed}</li>
          <li>Navigation items reorganized: {request.context.changes_summary.navigation_items_moved}</li>
          <li>Vertical space reclaimed: {request.context.changes_summary.height_reduction_px}px</li>
        </ul>
      </div>
      
      <div className="actions">
        {request.options.map(option => (
          <Button
            key={option}
            variant={option === selected ? "primary" : "secondary"}
            onClick={() => setSelected(option)}
          >
            {option}
          </Button>
        ))}
      </div>
    </Modal>
  );
}

Oversight & Auditability​

// Session timeline
interface SessionTimeline {
  session_id: string;
  started_at: number;
  ended_at?: number;
  events: TimelineEvent[];
  summary: SessionSummary;
}

interface TimelineEvent {
  timestamp: number;
  event_type: EventType;
  actor: "agent" | "user" | "system";
  action: string;
  details: Record<string, any>;
  artifacts?: Artifact[];
}

interface Artifact {
  type: "code_diff" | "file_created" | "file_modified" | "screenshot";
  path: string;
  before?: string;
  after?: string;
  metadata: Record<string, any>;
}

interface SessionSummary {
  H.P.003-SKILLS_used: string[];
  tools_called: string[];
  files_modified: string[];
  human_interventions: number;
  quality_score: number;
  duration_seconds: number;
}

// Timeline viewer component
function SessionTimelineViewer({ session_id }: { session_id: string }) {
  const timeline = useSessionTimeline(session_id);
  
  return (
    <div className="timeline-viewer">
      <SessionSummary summary={timeline.summary} />
      
      <div className="timeline">
        {timeline.events.map(event => (
          <TimelineEventCard
            key={event.timestamp}
            event={event}
            artifacts={event.artifacts}
          />
        ))}
      </div>
      
      <div className="export-options">
        <Button onClick={() => exportTimeline(timeline, "json")}>
          Export JSON
        </Button>
        <Button onClick={() => exportTimeline(timeline, "pdf")}>
          Export PDF Report
        </Button>
      </div>
    </div>
  );
}

// Exportable audit log
function exportTimeline(timeline: SessionTimeline, format: "json" | "pdf"): void {
  if (format === "json") {
    const blob = new Blob([JSON.stringify(timeline, null, 2)], {
      type: "application/json"
    });
    download(blob, `session-${timeline.session_id}.json`);
  } else if (format === "pdf") {
    // Generate PDF report with timeline visualization
    generatePDFReport(timeline);
  }
}

Implementation Roadmap for CODITECT​

Phase 1: Foundation (Week 1 - Jan 19-25)​

Goal: Core skill system with UI/UX capabilities

deliverables:
  - skill_registry_implementation:
      - Metadata-only loading
      - Discovery API
      - Activation flow
  
  - ui_ux_H.P.003-SKILLS:
      - header_consolidation (SKILL.md)
      - navigation_frequency (SKILL.md)
      - visual_design_principles (SKILL.md)
      - design_system_application (SKILL.md)
  
  - basic_event_protocol:
      - Event types defined
      - WebSocket server
      - Frontend event subscription
  
  - quality_gates:
      - Header count validation
      - Navigation depth validation
      - Basic accessibility checks

success_criteria:
  - Skills load without errors
  - Avivate UI regenerated with improvements
  - Will McKinley approval
  - Before/after comparison shows measurable quality gain

Phase 2: Human-in-Loop (Week 2 - Jan 26-Feb 1)​

Goal: HITL approval flows and action guards

deliverables:
  - approval_ui_components:
      - SkillActivationPrompt
      - ActionGuardModal
      - ReviewChangesModal
  
  - action_guards:
      - File write protection
      - Design system changes
      - Navigation restructuring
  
  - permission_negotiation:
      - Scope selection
      - Risk assessment
      - User preferences

success_criteria:
  - Users can approve/deny skill activations
  - High-risk actions trigger approval H.P.007-PROMPTS
  - Preference system reduces approval fatigue

Phase 3: Tools & Automation (Week 3-4 - Feb 2-15)​

Goal: Programmatic tools and H.P.004-SCRIPTS

deliverables:
  - core_tools:
      - analyze_headers
      - optimize_navigation
      - apply_design_system
      - validate_quality
  
  - automation_H.P.004-SCRIPTS:
      - generate_design_system.sh
      - validate_accessibility.py
      - extract_logo_colors.py
  
  - tool_chaining:
      - Define common chains
      - Dependency management
      - Error recovery

success_criteria:
  - Tools execute reliably
  - Scripts generate valid design systems
  - Tool chains complete without manual intervention

Phase 4: Reflection & Learning (Month 2 - Feb 16-Mar 15)​

Goal: Continuous improvement from feedback

deliverables:
  - feedback_collection:
      - Post-execution surveys
      - Rating system
      - Comment capture
  
  - skill_evolution:
      - Identify update opportunities
      - Generate proposed changes
      - User approval flow
  
  - learning_engine:
      - Pattern detection
      - Rule extraction
      - Confidence scoring

success_criteria:
  - 80%+ users provide feedback
  - 3+ skill improvements identified
  - 1+ skill update applied successfully

Integration with Existing CODITECT Platform​

Current Architecture Touchpoints​

integration_points:
  agent_orchestrator:
    - Register UI/UX agent as specialist
    - Route UI generation requests
    - Coordinate with lead agent
  
  skill_loader:
    - Load H.P.003-SKILLS from /mnt/H.P.003-SKILLS/public/ui_ux/
    - Cache metadata for quick discovery
    - Inject into agent context
  
  event_bus:
    - Publish skill events
    - Subscribe to approval responses
    - Maintain event log
  
  customer_data:
    - Load design systems from customer profiles
    - Store user preferences
    - Track quality metrics
  
  output_pipeline:
    - Apply quality gates before delivery
    - Generate before/after comparisons
    - Package artifacts for customer

Backward Compatibility​

class BackwardCompatibilityLayer:
    """Ensure existing CODITECT functionality continues working."""
    
    async def generate_ui(
        self,
        requirements: Dict[str, Any],
        use_new_system: bool = True
    ) -> Dict[str, Any]:
        """Generate UI with optional new skill system."""
        
        if not use_new_system:
            # Fallback to legacy generation
            return await self.legacy_ui_generator.generate(requirements)
        
        # New skill-based generation
        try:
            # Discover applicable H.P.003-SKILLS
            H.P.003-SKILLS = await self.skill_registry.discover_for_context(
                requirements
            )
            
            # Request activation
            activated = await self.activation_manager.request_activation_batch(
                H.P.003-SKILLS,
                requirements
            )
            
            # Execute with H.P.003-SKILLS
            result = await self.ui_executor.generate(
                requirements,
                activated_H.P.003-SKILLS=activated
            )
            
            return result
            
        except Exception as e:
            # Fallback to legacy on error
            logger.warning(f"New system failed, falling back: {e}")
            return await self.legacy_ui_generator.generate(requirements)

Success Metrics & KPIs​

Quality Metrics​

ui_quality:
  header_efficiency:
    metric: "Average header count per page"
    target: "≤ 1.2"
    baseline: "3.8"
    
  vertical_space:
    metric: "Pixels to first content"
    target: "< 100px"
    baseline: "380px"
    
  navigation_depth:
    metric: "Clicks to most-accessed content"
    target: "≤ 1.5"
    baseline: "3.2"
    
  accessibility:
    metric: "WCAG AA compliance rate"
    target: "> 95%"
    baseline: "68%"
    
  visual_complexity:
    metric: "Visual layers per component"
    target: "< 2.5"
    baseline: "4.1"

customer_satisfaction:
  design_quality_rating:
    metric: "Post-project design rating (1-10)"
    target: "> 8.0"
    baseline: "6.2"
    
  looks_ai_generated:
    metric: "% mentioning 'looks AI-generated'"
    target: "< 5%"
    baseline: "42%"
    
  professional_appearance:
    metric: "% rating as 'professional/enterprise'"
    target: "> 90%"
    baseline: "58%"
    
  nps_score:
    metric: "Net Promoter Score"
    target: "> 50"
    baseline: "28"

operational:
  skill_activation_rate:
    metric: "% of UI tasks using H.P.003-SKILLS"
    target: "100%"
    current: "0%"
    
  approval_fatigue:
    metric: "Average approvals per session"
    target: "< 3"
    baseline: "N/A"
    
  skill_improvement_cycle:
    metric: "Days between skill updates"
    target: "< 30"
    baseline: "N/A"

Conclusion: Competitive Advantage Through Architecture​

This Claude-style agentic architecture transforms CODITECT's UI/UX generation from ad-hoc AI output to a systematic, continuously-improving capability. The key advantages:

1. Quality Assurance: Built-in quality gates ensure professional output every time

2. Human Oversight: HITL patterns prevent errors while building user trust

3. Continuous Improvement: Reflection loop updates H.P.003-SKILLS based on real feedback

4. Auditability: Complete execution logs support enterprise compliance

5. Extensibility: Modular skill system enables rapid capability expansion

6. Differentiation: Structured approach impossible for competitors to replicate quickly

By implementing this architecture, CODITECT moves from "AI that generates code" to "AI that generates professional, enterprise-grade applications" - the difference between commodity tool and platform category leader.