feat: CRM Clinicas SaaS - MVP completo

- Auth: Login/Register con creacion de clinica - Dashboard: KPIs reales, graficas recharts - Pacientes: CRUD completo con busqueda - Agenda: FullCalendar, drag-and-drop, vista recepcion - Expediente: Notas SOAP, signos vitales, CIE-10 - Facturacion: Facturas con IVA, campos CFDI SAT - Inventario: Productos, stock, movimientos, alertas - Configuracion: Clinica, equipo, catalogo servicios - Supabase self-hosted: 18 tablas con RLS multi-tenant - Docker + Nginx para produccion Co-Authored-By: claude-flow <ruv@ruv.net>
2026-03-03 07:04:14 +00:00
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--- a/.claude/skills/v3-cli-modernization/SKILL.md
+++ b/.claude/skills/v3-cli-modernization/SKILL.md
@@ -0,0 +1,872 @@
+---
+name: "V3 CLI Modernization"
+description: "CLI modernization and hooks system enhancement for claude-flow v3. Implements interactive prompts, command decomposition, enhanced hooks integration, and intelligent workflow automation."
+---
+
+# V3 CLI Modernization
+
+## What This Skill Does
+
+Modernizes claude-flow v3 CLI with interactive prompts, intelligent command decomposition, enhanced hooks integration, performance optimization, and comprehensive workflow automation capabilities.
+
+## Quick Start
+
+```bash
+# Initialize CLI modernization analysis
+Task("CLI architecture", "Analyze current CLI structure and identify optimization opportunities", "cli-hooks-developer")
+
+# Modernization implementation (parallel)
+Task("Command decomposition", "Break down large CLI files into focused modules", "cli-hooks-developer")
+Task("Interactive prompts", "Implement intelligent interactive CLI experience", "cli-hooks-developer")
+Task("Hooks enhancement", "Deep integrate hooks with CLI lifecycle", "cli-hooks-developer")
+```
+
+## CLI Architecture Modernization
+
+### Current State Analysis
+```
+Current CLI Issues:
+├── index.ts: 108KB monolithic file
+├── enterprise.ts: 68KB feature module
+├── Limited interactivity: Basic command parsing
+├── Hooks integration: Basic pre/post execution
+└── No intelligent workflows: Manual command chaining
+
+Target Architecture:
+├── Modular Commands: <500 lines per command
+├── Interactive Prompts: Smart context-aware UX
+├── Enhanced Hooks: Deep lifecycle integration
+├── Workflow Automation: Intelligent command orchestration
+└── Performance: <200ms command response time
+```
+
+### Modular Command Architecture
+```typescript
+// src/cli/core/command-registry.ts
+interface CommandModule {
+  name: string;
+  description: string;
+  category: CommandCategory;
+  handler: CommandHandler;
+  middleware: MiddlewareStack;
+  permissions: Permission[];
+  examples: CommandExample[];
+}
+
+export class ModularCommandRegistry {
+  private commands = new Map<string, CommandModule>();
+  private categories = new Map<CommandCategory, CommandModule[]>();
+  private aliases = new Map<string, string>();
+
+  registerCommand(command: CommandModule): void {
+    this.commands.set(command.name, command);
+
+    // Register in category index
+    if (!this.categories.has(command.category)) {
+      this.categories.set(command.category, []);
+    }
+    this.categories.get(command.category)!.push(command);
+  }
+
+  async executeCommand(name: string, args: string[]): Promise<CommandResult> {
+    const command = this.resolveCommand(name);
+    if (!command) {
+      throw new CommandNotFoundError(name, this.getSuggestions(name));
+    }
+
+    // Execute middleware stack
+    const context = await this.buildExecutionContext(command, args);
+    const result = await command.middleware.execute(context);
+
+    return result;
+  }
+
+  private resolveCommand(name: string): CommandModule | undefined {
+    // Try exact match first
+    if (this.commands.has(name)) {
+      return this.commands.get(name);
+    }
+
+    // Try alias
+    const aliasTarget = this.aliases.get(name);
+    if (aliasTarget) {
+      return this.commands.get(aliasTarget);
+    }
+
+    // Try fuzzy match
+    return this.findFuzzyMatch(name);
+  }
+}
+```
+
+## Command Decomposition Strategy
+
+### Swarm Commands Module
+```typescript
+// src/cli/commands/swarm/swarm.command.ts
+@Command({
+  name: 'swarm',
+  description: 'Swarm coordination and management',
+  category: 'orchestration'
+})
+export class SwarmCommand {
+  constructor(
+    private swarmCoordinator: UnifiedSwarmCoordinator,
+    private promptService: InteractivePromptService
+  ) {}
+
+  @SubCommand('init')
+  @Option('--topology', 'Swarm topology (mesh|hierarchical|adaptive)', 'hierarchical')
+  @Option('--agents', 'Number of agents to spawn', 5)
+  @Option('--interactive', 'Interactive agent configuration', false)
+  async init(
+    @Arg('projectName') projectName: string,
+    options: SwarmInitOptions
+  ): Promise<CommandResult> {
+
+    if (options.interactive) {
+      return this.interactiveSwarmInit(projectName);
+    }
+
+    return this.quickSwarmInit(projectName, options);
+  }
+
+  private async interactiveSwarmInit(projectName: string): Promise<CommandResult> {
+    console.log(`🚀 Initializing Swarm for ${projectName}`);
+
+    // Interactive topology selection
+    const topology = await this.promptService.select({
+      message: 'Select swarm topology:',
+      choices: [
+        { name: 'Hierarchical (Queen-led coordination)', value: 'hierarchical' },
+        { name: 'Mesh (Peer-to-peer collaboration)', value: 'mesh' },
+        { name: 'Adaptive (Dynamic topology switching)', value: 'adaptive' }
+      ]
+    });
+
+    // Agent configuration
+    const agents = await this.promptAgentConfiguration();
+
+    // Initialize with configuration
+    const swarm = await this.swarmCoordinator.initialize({
+      name: projectName,
+      topology,
+      agents,
+      hooks: {
+        onAgentSpawn: this.handleAgentSpawn.bind(this),
+        onTaskComplete: this.handleTaskComplete.bind(this),
+        onSwarmComplete: this.handleSwarmComplete.bind(this)
+      }
+    });
+
+    return CommandResult.success({
+      message: `✅ Swarm ${projectName} initialized with ${agents.length} agents`,
+      data: { swarmId: swarm.id, topology, agentCount: agents.length }
+    });
+  }
+
+  @SubCommand('status')
+  async status(): Promise<CommandResult> {
+    const swarms = await this.swarmCoordinator.listActiveSwarms();
+
+    if (swarms.length === 0) {
+      return CommandResult.info('No active swarms found');
+    }
+
+    // Interactive swarm selection if multiple
+    const selectedSwarm = swarms.length === 1
+      ? swarms[0]
+      : await this.promptService.select({
+          message: 'Select swarm to inspect:',
+          choices: swarms.map(s => ({
+            name: `${s.name} (${s.agents.length} agents, ${s.topology})`,
+            value: s
+          }))
+        });
+
+    return this.displaySwarmStatus(selectedSwarm);
+  }
+}
+```
+
+### Learning Commands Module
+```typescript
+// src/cli/commands/learning/learning.command.ts
+@Command({
+  name: 'learning',
+  description: 'Learning system management and optimization',
+  category: 'intelligence'
+})
+export class LearningCommand {
+  constructor(
+    private learningService: IntegratedLearningService,
+    private promptService: InteractivePromptService
+  ) {}
+
+  @SubCommand('start')
+  @Option('--algorithm', 'RL algorithm to use', 'auto')
+  @Option('--tier', 'Learning tier (basic|standard|advanced)', 'standard')
+  async start(options: LearningStartOptions): Promise<CommandResult> {
+    // Auto-detect optimal algorithm if not specified
+    if (options.algorithm === 'auto') {
+      const taskContext = await this.analyzeCurrentContext();
+      options.algorithm = this.learningService.selectOptimalAlgorithm(taskContext);
+
+      console.log(`🧠 Auto-selected ${options.algorithm} algorithm based on context`);
+    }
+
+    const session = await this.learningService.startSession({
+      algorithm: options.algorithm,
+      tier: options.tier,
+      userId: await this.getCurrentUser()
+    });
+
+    return CommandResult.success({
+      message: `🚀 Learning session started with ${options.algorithm}`,
+      data: { sessionId: session.id, algorithm: options.algorithm, tier: options.tier }
+    });
+  }
+
+  @SubCommand('feedback')
+  @Arg('reward', 'Reward value (0-1)', 'number')
+  async feedback(
+    @Arg('reward') reward: number,
+    @Option('--context', 'Additional context for learning')
+    context?: string
+  ): Promise<CommandResult> {
+    const activeSession = await this.learningService.getActiveSession();
+    if (!activeSession) {
+      return CommandResult.error('No active learning session found. Start one with `learning start`');
+    }
+
+    await this.learningService.submitFeedback({
+      sessionId: activeSession.id,
+      reward,
+      context,
+      timestamp: new Date()
+    });
+
+    return CommandResult.success({
+      message: `📊 Feedback recorded (reward: ${reward})`,
+      data: { reward, sessionId: activeSession.id }
+    });
+  }
+
+  @SubCommand('metrics')
+  async metrics(): Promise<CommandResult> {
+    const metrics = await this.learningService.getMetrics();
+
+    // Interactive metrics display
+    await this.displayInteractiveMetrics(metrics);
+
+    return CommandResult.success('Metrics displayed');
+  }
+}
+```
+
+## Interactive Prompt System
+
+### Advanced Prompt Service
+```typescript
+// src/cli/services/interactive-prompt.service.ts
+interface PromptOptions {
+  message: string;
+  type: 'select' | 'multiselect' | 'input' | 'confirm' | 'progress';
+  choices?: PromptChoice[];
+  default?: any;
+  validate?: (input: any) => boolean | string;
+  transform?: (input: any) => any;
+}
+
+export class InteractivePromptService {
+  private inquirer: any; // Dynamic import for tree-shaking
+
+  async select<T>(options: SelectPromptOptions<T>): Promise<T> {
+    const { default: inquirer } = await import('inquirer');
+
+    const result = await inquirer.prompt([{
+      type: 'list',
+      name: 'selection',
+      message: options.message,
+      choices: options.choices,
+      default: options.default
+    }]);
+
+    return result.selection;
+  }
+
+  async multiSelect<T>(options: MultiSelectPromptOptions<T>): Promise<T[]> {
+    const { default: inquirer } = await import('inquirer');
+
+    const result = await inquirer.prompt([{
+      type: 'checkbox',
+      name: 'selections',
+      message: options.message,
+      choices: options.choices,
+      validate: (input: T[]) => {
+        if (options.minSelections && input.length < options.minSelections) {
+          return `Please select at least ${options.minSelections} options`;
+        }
+        if (options.maxSelections && input.length > options.maxSelections) {
+          return `Please select at most ${options.maxSelections} options`;
+        }
+        return true;
+      }
+    }]);
+
+    return result.selections;
+  }
+
+  async input(options: InputPromptOptions): Promise<string> {
+    const { default: inquirer } = await import('inquirer');
+
+    const result = await inquirer.prompt([{
+      type: 'input',
+      name: 'input',
+      message: options.message,
+      default: options.default,
+      validate: options.validate,
+      transformer: options.transform
+    }]);
+
+    return result.input;
+  }
+
+  async progressTask<T>(
+    task: ProgressTask<T>,
+    options: ProgressOptions
+  ): Promise<T> {
+    const { default: cliProgress } = await import('cli-progress');
+
+    const progressBar = new cliProgress.SingleBar({
+      format: `${options.title} |{bar}| {percentage}% | {status}`,
+      barCompleteChar: '█',
+      barIncompleteChar: '░',
+      hideCursor: true
+    });
+
+    progressBar.start(100, 0, { status: 'Starting...' });
+
+    try {
+      const result = await task({
+        updateProgress: (percent: number, status?: string) => {
+          progressBar.update(percent, { status: status || 'Processing...' });
+        }
+      });
+
+      progressBar.update(100, { status: 'Complete!' });
+      progressBar.stop();
+
+      return result;
+    } catch (error) {
+      progressBar.stop();
+      throw error;
+    }
+  }
+
+  async confirmWithDetails(
+    message: string,
+    details: ConfirmationDetails
+  ): Promise<boolean> {
+    console.log('\n' + chalk.bold(message));
+    console.log(chalk.gray('Details:'));
+
+    for (const [key, value] of Object.entries(details)) {
+      console.log(chalk.gray(`  ${key}: ${value}`));
+    }
+
+    return this.confirm('\nProceed?');
+  }
+}
+```
+
+## Enhanced Hooks Integration
+
+### Deep CLI Hooks Integration
+```typescript
+// src/cli/hooks/cli-hooks-manager.ts
+interface CLIHookEvent {
+  type: 'command_start' | 'command_end' | 'command_error' | 'agent_spawn' | 'task_complete';
+  command: string;
+  args: string[];
+  context: ExecutionContext;
+  timestamp: Date;
+}
+
+export class CLIHooksManager {
+  private hooks: Map<string, HookHandler[]> = new Map();
+  private learningIntegration: LearningHooksIntegration;
+
+  constructor() {
+    this.learningIntegration = new LearningHooksIntegration();
+    this.setupDefaultHooks();
+  }
+
+  private setupDefaultHooks(): void {
+    // Learning integration hooks
+    this.registerHook('command_start', async (event: CLIHookEvent) => {
+      await this.learningIntegration.recordCommandStart(event);
+    });
+
+    this.registerHook('command_end', async (event: CLIHookEvent) => {
+      await this.learningIntegration.recordCommandSuccess(event);
+    });
+
+    this.registerHook('command_error', async (event: CLIHookEvent) => {
+      await this.learningIntegration.recordCommandError(event);
+    });
+
+    // Intelligent suggestions
+    this.registerHook('command_start', async (event: CLIHookEvent) => {
+      const suggestions = await this.generateIntelligentSuggestions(event);
+      if (suggestions.length > 0) {
+        this.displaySuggestions(suggestions);
+      }
+    });
+
+    // Performance monitoring
+    this.registerHook('command_end', async (event: CLIHookEvent) => {
+      await this.recordPerformanceMetrics(event);
+    });
+  }
+
+  async executeHooks(type: string, event: CLIHookEvent): Promise<void> {
+    const handlers = this.hooks.get(type) || [];
+
+    await Promise.all(handlers.map(handler =>
+      this.executeHookSafely(handler, event)
+    ));
+  }
+
+  private async generateIntelligentSuggestions(event: CLIHookEvent): Promise<Suggestion[]> {
+    const context = await this.learningIntegration.getExecutionContext(event);
+    const patterns = await this.learningIntegration.findSimilarPatterns(context);
+
+    return patterns.map(pattern => ({
+      type: 'optimization',
+      message: `Based on similar executions, consider: ${pattern.suggestion}`,
+      confidence: pattern.confidence
+    }));
+  }
+}
+```
+
+### Learning Integration
+```typescript
+// src/cli/hooks/learning-hooks-integration.ts
+export class LearningHooksIntegration {
+  constructor(
+    private agenticFlowHooks: AgenticFlowHooksClient,
+    private agentDBLearning: AgentDBLearningClient
+  ) {}
+
+  async recordCommandStart(event: CLIHookEvent): Promise<void> {
+    // Start trajectory tracking
+    await this.agenticFlowHooks.trajectoryStart({
+      sessionId: event.context.sessionId,
+      command: event.command,
+      args: event.args,
+      context: event.context
+    });
+
+    // Record experience in AgentDB
+    await this.agentDBLearning.recordExperience({
+      type: 'command_execution',
+      state: this.encodeCommandState(event),
+      action: event.command,
+      timestamp: event.timestamp
+    });
+  }
+
+  async recordCommandSuccess(event: CLIHookEvent): Promise<void> {
+    const executionTime = Date.now() - event.timestamp.getTime();
+    const reward = this.calculateReward(event, executionTime, true);
+
+    // Complete trajectory
+    await this.agenticFlowHooks.trajectoryEnd({
+      sessionId: event.context.sessionId,
+      success: true,
+      reward,
+      verdict: 'positive'
+    });
+
+    // Submit feedback to learning system
+    await this.agentDBLearning.submitFeedback({
+      sessionId: event.context.learningSessionId,
+      reward,
+      success: true,
+      latencyMs: executionTime
+    });
+
+    // Store successful pattern
+    if (reward > 0.8) {
+      await this.agenticFlowHooks.storePattern({
+        pattern: event.command,
+        solution: event.context.result,
+        confidence: reward
+      });
+    }
+  }
+
+  async recordCommandError(event: CLIHookEvent): Promise<void> {
+    const executionTime = Date.now() - event.timestamp.getTime();
+    const reward = this.calculateReward(event, executionTime, false);
+
+    // Complete trajectory with error
+    await this.agenticFlowHooks.trajectoryEnd({
+      sessionId: event.context.sessionId,
+      success: false,
+      reward,
+      verdict: 'negative',
+      error: event.context.error
+    });
+
+    // Learn from failure
+    await this.agentDBLearning.submitFeedback({
+      sessionId: event.context.learningSessionId,
+      reward,
+      success: false,
+      latencyMs: executionTime,
+      error: event.context.error
+    });
+  }
+
+  private calculateReward(event: CLIHookEvent, executionTime: number, success: boolean): number {
+    if (!success) return 0;
+
+    // Base reward for success
+    let reward = 0.5;
+
+    // Performance bonus (faster execution)
+    const expectedTime = this.getExpectedExecutionTime(event.command);
+    if (executionTime < expectedTime) {
+      reward += 0.3 * (1 - executionTime / expectedTime);
+    }
+
+    // Complexity bonus
+    const complexity = this.calculateCommandComplexity(event);
+    reward += complexity * 0.2;
+
+    return Math.min(reward, 1.0);
+  }
+}
+```
+
+## Intelligent Workflow Automation
+
+### Workflow Orchestrator
+```typescript
+// src/cli/workflows/workflow-orchestrator.ts
+interface WorkflowStep {
+  id: string;
+  command: string;
+  args: string[];
+  dependsOn: string[];
+  condition?: WorkflowCondition;
+  retryPolicy?: RetryPolicy;
+}
+
+export class WorkflowOrchestrator {
+  constructor(
+    private commandRegistry: ModularCommandRegistry,
+    private promptService: InteractivePromptService
+  ) {}
+
+  async executeWorkflow(workflow: Workflow): Promise<WorkflowResult> {
+    const context = new WorkflowExecutionContext(workflow);
+
+    // Display workflow overview
+    await this.displayWorkflowOverview(workflow);
+
+    const confirmed = await this.promptService.confirm(
+      'Execute this workflow?'
+    );
+
+    if (!confirmed) {
+      return WorkflowResult.cancelled();
+    }
+
+    // Execute steps
+    return this.promptService.progressTask(
+      async ({ updateProgress }) => {
+        const steps = this.sortStepsByDependencies(workflow.steps);
+
+        for (let i = 0; i < steps.length; i++) {
+          const step = steps[i];
+          updateProgress((i / steps.length) * 100, `Executing ${step.command}`);
+
+          await this.executeStep(step, context);
+        }
+
+        return WorkflowResult.success(context.getResults());
+      },
+      { title: `Workflow: ${workflow.name}` }
+    );
+  }
+
+  async generateWorkflowFromIntent(intent: string): Promise<Workflow> {
+    // Use learning system to generate workflow
+    const patterns = await this.findWorkflowPatterns(intent);
+
+    if (patterns.length === 0) {
+      throw new Error('Could not generate workflow for intent');
+    }
+
+    // Select best pattern or let user choose
+    const selectedPattern = patterns.length === 1
+      ? patterns[0]
+      : await this.promptService.select({
+          message: 'Select workflow template:',
+          choices: patterns.map(p => ({
+            name: `${p.name} (${p.confidence}% match)`,
+            value: p
+          }))
+        });
+
+    return this.customizeWorkflow(selectedPattern, intent);
+  }
+
+  private async executeStep(step: WorkflowStep, context: WorkflowExecutionContext): Promise<void> {
+    // Check conditions
+    if (step.condition && !this.evaluateCondition(step.condition, context)) {
+      context.skipStep(step.id, 'Condition not met');
+      return;
+    }
+
+    // Check dependencies
+    const missingDeps = step.dependsOn.filter(dep => !context.isStepCompleted(dep));
+    if (missingDeps.length > 0) {
+      throw new WorkflowError(`Step ${step.id} has unmet dependencies: ${missingDeps.join(', ')}`);
+    }
+
+    // Execute with retry policy
+    const retryPolicy = step.retryPolicy || { maxAttempts: 1 };
+    let lastError: Error | null = null;
+
+    for (let attempt = 1; attempt <= retryPolicy.maxAttempts; attempt++) {
+      try {
+        const result = await this.commandRegistry.executeCommand(step.command, step.args);
+        context.completeStep(step.id, result);
+        return;
+      } catch (error) {
+        lastError = error as Error;
+
+        if (attempt < retryPolicy.maxAttempts) {
+          await this.delay(retryPolicy.backoffMs || 1000);
+        }
+      }
+    }
+
+    throw new WorkflowError(`Step ${step.id} failed after ${retryPolicy.maxAttempts} attempts: ${lastError?.message}`);
+  }
+}
+```
+
+## Performance Optimization
+
+### Command Performance Monitoring
+```typescript
+// src/cli/performance/command-performance.ts
+export class CommandPerformanceMonitor {
+  private metrics = new Map<string, CommandMetrics>();
+
+  async measureCommand<T>(
+    commandName: string,
+    executor: () => Promise<T>
+  ): Promise<T> {
+    const start = performance.now();
+    const memBefore = process.memoryUsage();
+
+    try {
+      const result = await executor();
+      const end = performance.now();
+      const memAfter = process.memoryUsage();
+
+      this.recordMetrics(commandName, {
+        executionTime: end - start,
+        memoryDelta: memAfter.heapUsed - memBefore.heapUsed,
+        success: true
+      });
+
+      return result;
+    } catch (error) {
+      const end = performance.now();
+
+      this.recordMetrics(commandName, {
+        executionTime: end - start,
+        memoryDelta: 0,
+        success: false,
+        error: error as Error
+      });
+
+      throw error;
+    }
+  }
+
+  private recordMetrics(command: string, measurement: PerformanceMeasurement): void {
+    if (!this.metrics.has(command)) {
+      this.metrics.set(command, new CommandMetrics(command));
+    }
+
+    const metrics = this.metrics.get(command)!;
+    metrics.addMeasurement(measurement);
+
+    // Alert if performance degrades
+    if (metrics.getP95ExecutionTime() > 5000) { // 5 seconds
+      console.warn(`⚠️  Command '${command}' is performing slowly (P95: ${metrics.getP95ExecutionTime()}ms)`);
+    }
+  }
+
+  getCommandReport(command: string): PerformanceReport {
+    const metrics = this.metrics.get(command);
+    if (!metrics) {
+      throw new Error(`No metrics found for command: ${command}`);
+    }
+
+    return {
+      command,
+      totalExecutions: metrics.getTotalExecutions(),
+      successRate: metrics.getSuccessRate(),
+      avgExecutionTime: metrics.getAverageExecutionTime(),
+      p95ExecutionTime: metrics.getP95ExecutionTime(),
+      avgMemoryUsage: metrics.getAverageMemoryUsage(),
+      recommendations: this.generateRecommendations(metrics)
+    };
+  }
+}
+```
+
+## Smart Auto-completion
+
+### Intelligent Command Completion
+```typescript
+// src/cli/completion/intelligent-completion.ts
+export class IntelligentCompletion {
+  constructor(
+    private learningService: LearningService,
+    private commandRegistry: ModularCommandRegistry
+  ) {}
+
+  async generateCompletions(
+    partial: string,
+    context: CompletionContext
+  ): Promise<Completion[]> {
+    const completions: Completion[] = [];
+
+    // 1. Exact command matches
+    const exactMatches = this.commandRegistry.findCommandsByPrefix(partial);
+    completions.push(...exactMatches.map(cmd => ({
+      value: cmd.name,
+      description: cmd.description,
+      type: 'command',
+      confidence: 1.0
+    })));
+
+    // 2. Learning-based suggestions
+    const learnedSuggestions = await this.learningService.suggestCommands(
+      partial,
+      context
+    );
+    completions.push(...learnedSuggestions);
+
+    // 3. Context-aware suggestions
+    const contextualSuggestions = await this.generateContextualSuggestions(
+      partial,
+      context
+    );
+    completions.push(...contextualSuggestions);
+
+    // Sort by confidence and relevance
+    return completions
+      .sort((a, b) => b.confidence - a.confidence)
+      .slice(0, 10); // Top 10 suggestions
+  }
+
+  private async generateContextualSuggestions(
+    partial: string,
+    context: CompletionContext
+  ): Promise<Completion[]> {
+    const suggestions: Completion[] = [];
+
+    // If in git repository, suggest git-related commands
+    if (context.isGitRepository) {
+      if (partial.startsWith('git')) {
+        suggestions.push({
+          value: 'git commit',
+          description: 'Create git commit with generated message',
+          type: 'workflow',
+          confidence: 0.8
+        });
+      }
+    }
+
+    // If package.json exists, suggest npm commands
+    if (context.hasPackageJson) {
+      if (partial.startsWith('npm') || partial.startsWith('swarm')) {
+        suggestions.push({
+          value: 'swarm init',
+          description: 'Initialize swarm for this project',
+          type: 'workflow',
+          confidence: 0.9
+        });
+      }
+    }
+
+    return suggestions;
+  }
+}
+```
+
+## Success Metrics
+
+### CLI Performance Targets
+- [ ] **Command Response**: <200ms average command execution time
+- [ ] **File Decomposition**: index.ts (108KB) → <10KB per command module
+- [ ] **Interactive UX**: Smart prompts with context awareness
+- [ ] **Hook Integration**: Deep lifecycle integration with learning
+- [ ] **Workflow Automation**: Intelligent multi-step command orchestration
+- [ ] **Auto-completion**: >90% accuracy for command suggestions
+
+### User Experience Improvements
+```typescript
+const cliImprovements = {
+  before: {
+    commandResponse: '~500ms',
+    interactivity: 'Basic command parsing',
+    workflows: 'Manual command chaining',
+    suggestions: 'Static help text'
+  },
+
+  after: {
+    commandResponse: '<200ms with caching',
+    interactivity: 'Smart context-aware prompts',
+    workflows: 'Automated multi-step execution',
+    suggestions: 'Learning-based intelligent completion'
+  }
+};
+```
+
+## Related V3 Skills
+
+- `v3-core-implementation` - Core domain integration
+- `v3-memory-unification` - Memory-backed command caching
+- `v3-swarm-coordination` - CLI swarm management integration
+- `v3-performance-optimization` - CLI performance monitoring
+
+## Usage Examples
+
+### Complete CLI Modernization
+```bash
+# Full CLI modernization implementation
+Task("CLI modernization implementation",
+     "Implement modular commands, interactive prompts, and intelligent workflows",
+     "cli-hooks-developer")
+```
+
+### Interactive Command Enhancement
+```bash
+# Enhanced interactive commands
+claude-flow swarm init --interactive
+claude-flow learning start --guided
+claude-flow workflow create --from-intent "setup new project"
+```