chore: restore .claude commands, agents, helpers & skills (lost in 1df208d)

Restores the entire .claude/ infrastructure that was accidentally deleted in commit 1df208d ('feat(timeline): add pulse animation for in-flight drag mutations'). Recovered via git checkout 1df208d^. Restored: - .claude/commands/ (gitlooper, sparc/, github/, automation/, monitoring/, optimization/, hooks/, plan, implement, research, review, perf, visualaudit) - .claude/agents/ (core/, github/, sparc/, v3/, swarm/, templates/, ...) - .claude/helpers/ (41 scripts incl. hook-handler.cjs, statusline.cjs) - .claude/skills/ (20 skills incl. sparc-methodology, github-*, v3-*) - .claude/settings.json (hooks configuration) Also updated all CapaKraken → Nexus references in affected command files. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-08-15 11:43:52 +02:00
parent 55b861cb43
commit f80808482d
269 changed files with 80697 additions and 0 deletions
@@ -0,0 +1,878 @@
+---
+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"
+```