Claude Code 命令系统原理

24个核心命令的解析、执行和编排机制深度分析

目录

• 命令系统架构
• 命令解析引擎
• 参数处理系统
• 执行策略引擎
• Wave编排系统
• 命令协调机制
• 性能优化策略
• 监控和恢复

命令系统架构

系统总体架构

命令系统核心特性

interface CommandSystemCore {
  // 命令体系
  command_inventory: {
    total_commands: 24,
    development_commands: 8,     // 开发和实施
    analysis_commands: 3,        // 分析和调试
    quality_commands: 3,         // 质量和增强
    management_commands: 4,      // 项目管理
    specialized_commands: 6      // 专业领域
  };
  
  // 解析能力
  parsing_capabilities: {
    natural_language: 'Full natural language command parsing',
    structured_syntax: 'Formal command syntax support',
    parameter_inference: 'Automatic parameter completion',
    context_awareness: 'Project context integration'
  };
  
  // 执行模式
  execution_modes: {
    traditional: 'Single-threaded sequential execution',
    enhanced: 'Multi-agent collaborative execution', 
    wave: 'Multi-stage orchestrated execution',
    hybrid: 'Adaptive mode selection'
  };
  
  // 智能特性
  intelligent_features: {
    auto_flag_activation: 'Context-based flag auto-activation',
    persona_integration: 'Automatic agent role assignment',
    wave_threshold_detection: 'Complexity-based wave triggering',
    performance_optimization: 'Execution strategy optimization'
  };
}

命令解析引擎

多层解析架构

class CommandParsingEngine {
  private naturalLanguageProcessor = new NLPProcessor();
  private structuredCommandParser = new StructuredCommandParser();
  private parameterInferenceEngine = new ParameterInferenceEngine();
  private contextIntegrator = new ContextIntegrator();
  
  async parseCommand(
    input: string,
    context: ExecutionContext
  ): Promise<ParsedCommand> {
    
    // 1. 输入预处理和分类
    const preprocessedInput = await this.preprocessInput(input);
    const inputType = this.classifyInputType(preprocessedInput);
    
    // 2. 多路径解析
    const parsingResults = await this.multiPathParsing(preprocessedInput, inputType);
    
    // 3. 解析结果融合
    const fusedResult = this.fuseParsingResults(parsingResults);
    
    // 4. 上下文集成
    const contextIntegratedResult = await this.integrateContext(fusedResult, context);
    
    // 5. 解析验证
    const validatedResult = await this.validateParsedCommand(contextIntegratedResult);
    
    return validatedResult;
  }
  
  private async multiPathParsing(
    input: string,
    inputType: InputType
  ): Promise<ParsingResult[]> {
    
    const parsingTasks: Promise<ParsingResult>[] = [];
    
    // 1. 自然语言解析路径
    if (inputType.hasNaturalLanguage) {
      parsingTasks.push(this.parseNaturalLanguage(input));
    }
    
    // 2. 结构化命令解析路径
    if (inputType.hasStructuredCommand) {
      parsingTasks.push(this.parseStructuredCommand(input));
    }
    
    // 3. 混合模式解析路径
    if (inputType.isMixed) {
      parsingTasks.push(this.parseMixedCommand(input));
    }
    
    // 并行执行所有解析路径
    const results = await Promise.allSettled(parsingTasks);
    
    // 过滤成功的解析结果
    return results
      .filter(result => result.status === 'fulfilled')
      .map(result => (result as PromiseFulfilledResult<ParsingResult>).value);
  }
  
  private async parseNaturalLanguage(input: string): Promise<ParsingResult> {
    // 1. 意图识别
    const intentAnalysis = await this.naturalLanguageProcessor.analyzeIntent(input);
    
    // 2. 实体提取
    const entities = await this.naturalLanguageProcessor.extractEntities(input);
    
    // 3. 命令映射
    const commandMapping = this.mapIntentToCommand(intentAnalysis);
    
    // 4. 参数推断
    const inferredParameters = await this.inferParametersFromEntities(entities, commandMapping);
    
    return {
      source: 'natural_language',
      confidence: intentAnalysis.confidence,
      command: commandMapping.command,
      parameters: inferredParameters,
      reasoning: {
        intent: intentAnalysis,
        entities: entities,
        mapping_logic: commandMapping.reasoning
      }
    };
  }
  
  private async parseStructuredCommand(input: string): Promise<ParsingResult> {
    // 1. 语法分析
    const syntaxTree = this.structuredCommandParser.parse(input);
    
    // 2. 命令提取
    const command = this.extractCommandFromSyntax(syntaxTree);
    
    // 3. 参数解析
    const parameters = this.extractParametersFromSyntax(syntaxTree);
    
    // 4. 标志处理
    const flags = this.extractFlagsFromSyntax(syntaxTree);
    
    return {
      source: 'structured_command',
      confidence: 0.95, // 结构化命令通常置信度更高
      command: command,
      parameters: { ...parameters, flags: flags },
      reasoning: {
        syntax_tree: syntaxTree,
        parsing_steps: this.documentParsingSteps(syntaxTree)
      }
    };
  }
  
  private mapIntentToCommand(intentAnalysis: IntentAnalysis): CommandMapping {
    const intentToCommandMap = {
      // 开发意图
      'create_feature': '/implement',
      'build_application': '/build',
      'design_system': '/design',
      
      // 分析意图
      'analyze_code': '/analyze',
      'debug_issue': '/troubleshoot', 
      'explain_concept': '/explain',
      
      // 质量意图
      'improve_code': '/improve',
      'clean_project': '/cleanup',
      'run_tests': '/test',
      
      // 管理意图
      'manage_tasks': '/task',
      'estimate_work': '/estimate',
      'create_workflow': '/workflow',
      
      // 专业领域意图
      'deploy_application': '/deploy',
      'analyze_data': '/analyze-data',
      'train_model': '/train-model',
      'build_mobile': '/mobile-build'
    };
    
    const primaryIntent = intentAnalysis.primary_intent;
    const mappedCommand = intentToCommandMap[primaryIntent];
    
    if (!mappedCommand) {
      // 使用语义相似度进行模糊匹配
      const similarityScores = this.calculateIntentSimilarity(primaryIntent, Object.keys(intentToCommandMap));
      const bestMatch = similarityScores.reduce((best, current) => 
        current.score > best.score ? current : best
      );
      
      return {
        command: intentToCommandMap[bestMatch.intent],
        confidence: bestMatch.score * intentAnalysis.confidence,
        reasoning: `Fuzzy matched intent "${primaryIntent}" to "${bestMatch.intent}"`
      };
    }
    
    return {
      command: mappedCommand,
      confidence: intentAnalysis.confidence,
      reasoning: `Direct intent mapping: "${primaryIntent}" -> "${mappedCommand}"`
    };
  }
  
  private async inferParametersFromEntities(
    entities: ExtractedEntity[],
    commandMapping: CommandMapping
  ): Promise<InferredParameters> {
    
    const commandSchema = this.getCommandSchema(commandMapping.command);
    const inferredParams: InferredParameters = {};
    
    for (const entity of entities) {
      // 根据实体类型和命令模式推断参数
      const parameterMappings = this.getParameterMappingsForEntity(entity, commandSchema);
      
      for (const mapping of parameterMappings) {
        if (mapping.confidence > 0.7) {
          inferredParams[mapping.parameter] = {
            value: this.transformEntityValue(entity.value, mapping.target_type),
            confidence: mapping.confidence,
            source: entity
          };
        }
      }
    }
    
    // 参数完整性检查和补全
    const completedParams = await this.completeParametersWithDefaults(
      inferredParams,
      commandSchema
    );
    
    return completedParams;
  }
  
  private fuseParsingResults(results: ParsingResult[]): FusedParsingResult {
    if (results.length === 0) {
      throw new CommandParsingError('No successful parsing results');
    }
    
    if (results.length === 1) {
      return this.createFusedResult(results[0]);
    }
    
    // 多结果融合策略
    const fusionStrategy = this.selectFusionStrategy(results);
    
    switch (fusionStrategy) {
      case 'confidence_weighted':
        return this.fuseByConfidenceWeighting(results);
      case 'consensus_voting':
        return this.fuseByConsensusVoting(results);
      case 'best_match':
        return this.fuseByBestMatch(results);
      default:
        return this.fuseByDefault(results);
    }
  }
  
  private fuseByConfidenceWeighting(results: ParsingResult[]): FusedParsingResult {
    // 按置信度加权融合
    const totalWeight = results.reduce((sum, result) => sum + result.confidence, 0);
    
    // 命令选择（选择最高置信度的命令）
    const primaryCommand = results.reduce((best, current) => 
      current.confidence > best.confidence ? current : best
    ).command;
    
    // 参数融合（加权平均相同参数）
    const fusedParameters = this.weightedParameterFusion(results, totalWeight);
    
    // 综合置信度计算
    const fusedConfidence = this.calculateFusedConfidence(results);
    
    return {
      command: primaryCommand,
      parameters: fusedParameters,
      confidence: fusedConfidence,
      fusion_method: 'confidence_weighted',
      source_results: results
    };
  }
  
  private async integrateContext(
    fusedResult: FusedParsingResult,
    context: ExecutionContext
  ): Promise<ContextIntegratedCommand> {
    
    // 1. 项目上下文集成
    const projectContextEnhancement = await this.enhanceWithProjectContext(
      fusedResult,
      context.projectContext
    );
    
    // 2. 历史命令上下文
    const historyContextEnhancement = await this.enhanceWithHistoryContext(
      projectContextEnhancement,
      context.commandHistory
    );
    
    // 3. 环境上下文集成
    const environmentContextEnhancement = await this.enhanceWithEnvironmentContext(
      historyContextEnhancement,
      context.environmentContext
    );
    
    // 4. 用户偏好集成
    const userPreferenceEnhancement = await this.enhanceWithUserPreferences(
      environmentContextEnhancement,
      context.userPreferences
    );
    
    return userPreferenceEnhancement;
  }
  
  private async enhanceWithProjectContext(
    command: FusedParsingResult,
    projectContext: ProjectContext
  ): Promise<ProjectContextEnhancedCommand> {
    
    // 1. 项目类型适配
    const projectTypeAdaptation = this.adaptToProjectType(command, projectContext.type);
    
    // 2. 技术栈集成
    const techStackIntegration = await this.integrateTechStack(
      projectTypeAdaptation,
      projectContext.techStack
    );
    
    // 3. 项目结构感知
    const structureAwareness = await this.enhanceWithProjectStructure(
      techStackIntegration,
      projectContext.structure
    );
    
    // 4. 依赖关系识别
    const dependencyIntegration = await this.integrateDependencies(
      structureAwareness,
      projectContext.dependencies
    );
    
    return {
      ...command,
      project_adaptations: {
        type_adaptation: projectTypeAdaptation.adaptations,
        tech_stack_integration: techStackIntegration.integrations,
        structure_awareness: structureAwareness.enhancements,
        dependency_integration: dependencyIntegration.dependencies
      }
    };
  }
}

智能参数推断

class ParameterInferenceEngine {
  private contextAnalyzer = new ParameterContextAnalyzer();
  private patternMatcher = new ParameterPatternMatcher();
  private defaultProvider = new ParameterDefaultProvider();
  
  async inferParameters(
    command: string,
    extractedEntities: ExtractedEntity[],
    context: ExecutionContext
  ): Promise<InferredParameterSet> {
    
    const commandSchema = this.getCommandParameterSchema(command);
    const inferredParams = new Map<string, InferredParameter>();
    
    // 1. 实体直接映射
    await this.mapEntitiesDirectly(extractedEntities, commandSchema, inferredParams);
    
    // 2. 上下文推断
    await this.inferFromContext(command, context, commandSchema, inferredParams);
    
    // 3. 模式匹配推断
    await this.inferFromPatterns(command, extractedEntities, commandSchema, inferredParams);
    
    // 4. 默认值填充
    await this.fillDefaults(command, commandSchema, inferredParams);
    
    // 5. 参数验证和修正
    const validatedParams = await this.validateAndCorrect(inferredParams, commandSchema);
    
    return {
      parameters: validatedParams,
      confidence: this.calculateOverallConfidence(validatedParams),
      inference_steps: this.documentInferenceSteps(),
      missing_required: this.identifyMissingRequired(validatedParams, commandSchema)
    };
  }
  
  private async inferFromContext(
    command: string,
    context: ExecutionContext,
    schema: CommandParameterSchema,
    inferredParams: Map<string, InferredParameter>
  ): Promise<void> {
    
    // 文件路径参数推断
    if (schema.hasFilePathParameters()) {
      await this.inferFilePathParameters(command, context, inferredParams);
    }
    
    // 项目范围参数推断
    if (schema.hasScopeParameters()) {
      await this.inferScopeParameters(command, context, inferredParams);
    }
    
    // 技术栈相关参数推断
    if (schema.hasTechStackParameters()) {
      await this.inferTechStackParameters(command, context, inferredParams);
    }
  }
  
  private async inferFilePathParameters(
    command: string,
    context: ExecutionContext,
    inferredParams: Map<string, InferredParameter>
  ): Promise<void> {
    
    const workingDirectory = context.workingDirectory;
    const recentFiles = context.recentlyAccessedFiles;
    const projectStructure = context.projectStructure;
    
    switch (command) {
      case '/analyze':
        // 分析命令的路径推断
        if (!inferredParams.has('path')) {
          const candidatePaths = this.identifyAnalysisCandidates(
            workingDirectory,
            recentFiles,
            projectStructure
          );
          
          if (candidatePaths.length > 0) {
            inferredParams.set('path', {
              value: candidatePaths[0].path,
              confidence: candidatePaths[0].confidence,
              inference_method: 'context_analysis_candidate',
              alternatives: candidatePaths.slice(1)
            });
          }
        }
        break;
        
      case '/improve':
        // 改进命令的路径推断
        if (!inferredParams.has('target')) {
          const improvementCandidates = this.identifyImprovementCandidates(
            recentFiles,
            projectStructure
          );
          
          inferredParams.set('target', {
            value: improvementCandidates.primary.path,
            confidence: improvementCandidates.primary.confidence,
            inference_method: 'recent_activity_analysis',
            reasoning: improvementCandidates.reasoning
          });
        }
        break;
        
      case '/build':
        // 构建命令的目标推断
        if (!inferredParams.has('target')) {
          const buildTarget = this.inferBuildTarget(projectStructure);
          
          inferredParams.set('target', {
            value: buildTarget.target,
            confidence: buildTarget.confidence,
            inference_method: 'project_structure_analysis',
            build_system: buildTarget.detectedBuildSystem
          });
        }
        break;
    }
  }
  
  private async inferFromPatterns(
    command: string,
    entities: ExtractedEntity[],
    schema: CommandParameterSchema,
    inferredParams: Map<string, InferredParameter>
  ): Promise<void> {
    
    // 获取命令特定的模式
    const commandPatterns = this.getCommandPatterns(command);
    
    for (const pattern of commandPatterns) {
      const matches = this.patternMatcher.findMatches(entities, pattern);
      
      for (const match of matches) {
        if (match.confidence > 0.6 && !inferredParams.has(match.parameter)) {
          inferredParams.set(match.parameter, {
            value: match.extractedValue,
            confidence: match.confidence,
            inference_method: 'pattern_matching',
            pattern_used: pattern.id,
            match_details: match.details
          });
        }
      }
    }
  }
  
  private getCommandPatterns(command: string): ParameterPattern[] {
    const patterns = {
      '/implement': [
        {
          id: 'feature_description_pattern',
          pattern: /implement\s+(a\s+)?(.+?)\s+(feature|component|service|api)/i,
          parameter: 'feature_description',
          extractor: (match) => match[2]
        },
        {
          id: 'type_specification_pattern', 
          pattern: /--type\s+(api|component|service|feature|ui)/i,
          parameter: 'type',
          extractor: (match) => match[1]
        }
      ],
      
      '/analyze': [
        {
          id: 'analysis_target_pattern',
          pattern: /analyze\s+(the\s+)?(.+?)(\s+for|\s+to|\s*$)/i,
          parameter: 'target',
          extractor: (match) => match[2]
        },
        {
          id: 'analysis_type_pattern',
          pattern: /for\s+(security|performance|quality|structure)/i,
          parameter: 'focus',
          extractor: (match) => match[1]
        }
      ],
      
      '/deploy': [
        {
          id: 'deployment_target_pattern',
          pattern: /deploy\s+(.+?)\s+to\s+(aws|gcp|azure|k8s|kubernetes)/i,
          parameter: 'target',
          extractor: (match) => match[1]
        },
        {
          id: 'deployment_platform_pattern',
          pattern: /to\s+(aws|gcp|azure|k8s|kubernetes|heroku)/i,
          parameter: 'platform',
          extractor: (match) => match[1]
        }
      ]
    };
    
    return patterns[command] || [];
  }
  
  private async fillDefaults(
    command: string,
    schema: CommandParameterSchema,
    inferredParams: Map<string, InferredParameter>
  ): Promise<void> {
    
    const defaultValues = await this.defaultProvider.getDefaults(command, schema);
    
    for (const [paramName, defaultValue] of defaultValues.entries()) {
      if (!inferredParams.has(paramName)) {
        inferredParams.set(paramName, {
          value: defaultValue.value,
          confidence: defaultValue.confidence,
          inference_method: 'default_value',
          is_default: true,
          default_source: defaultValue.source
        });
      }
    }
  }
  
  private async validateAndCorrect(
    inferredParams: Map<string, InferredParameter>,
    schema: CommandParameterSchema
  ): Promise<Map<string, ValidatedParameter>> {
    
    const validatedParams = new Map<string, ValidatedParameter>();
    
    for (const [paramName, inferredParam] of inferredParams.entries()) {
      const paramSchema = schema.getParameterSchema(paramName);
      
      if (!paramSchema) {
        // 参数不在模式中，可能是推断错误
        continue;
      }
      
      // 类型验证和转换
      const typeValidation = await this.validateParameterType(
        inferredParam.value,
        paramSchema.type
      );
      
      if (!typeValidation.valid) {
        // 尝试类型修正
        const correctedValue = await this.attemptTypeCorrection(
          inferredParam.value,
          paramSchema.type
        );
        
        if (correctedValue.success) {
          validatedParams.set(paramName, {
            ...inferredParam,
            value: correctedValue.value,
            was_corrected: true,
            correction_method: correctedValue.method
          });
        }
        // 如果修正失败，跳过此参数
        continue;
      }
      
      // 值域验证
      const valueValidation = await this.validateParameterValue(
        typeValidation.value,
        paramSchema.constraints
      );
      
      if (valueValidation.valid) {
        validatedParams.set(paramName, {
          ...inferredParam,
          value: typeValidation.value,
          validation_passed: true
        });
      }
    }
    
    return validatedParams;
  }
}

执行策略引擎

动态策略选择

class ExecutionStrategyEngine {
  private complexityAnalyzer = new CommandComplexityAnalyzer();
  private resourceEstimator = new ResourceRequirementEstimator();
  private performancePredictor = new StrategyPerformancePredictor();
  private strategyOptimizer = new StrategyOptimizer();
  
  async selectExecutionStrategy(
    parsedCommand: ParsedCommand,
    context: ExecutionContext
  ): Promise<ExecutionStrategyDecision> {
    
    // 1. 复杂度综合评估
    const complexityAssessment = await this.complexityAnalyzer.assess(parsedCommand, context);
    
    // 2. 候选策略生成
    const candidateStrategies = this.generateCandidateStrategies(complexityAssessment);
    
    // 3. 资源需求估算
    const resourceEstimates = await this.estimateResourceRequirements(candidateStrategies);
    
    // 4. 性能预测
    const performancePredictions = await this.predictStrategyPerformance(candidateStrategies);
    
    // 5. 最优策略选择
    const optimalStrategy = this.selectOptimalStrategy(
      candidateStrategies,
      resourceEstimates,
      performancePredictions,
      context.constraints
    );
    
    // 6. 策略优化
    const optimizedStrategy = await this.strategyOptimizer.optimize(optimalStrategy, context);
    
    return {
      selected_strategy: optimizedStrategy,
      complexity_assessment: complexityAssessment,
      resource_allocation: resourceEstimates.get(optimalStrategy.id),
      performance_prediction: performancePredictions.get(optimalStrategy.id),
      alternative_strategies: this.generateAlternatives(candidateStrategies, optimalStrategy),
      execution_plan: await this.createExecutionPlan(optimizedStrategy, context)
    };
  }
  
  private async assess(
    parsedCommand: ParsedCommand,
    context: ExecutionContext
  ): Promise<ComplexityAssessment> {
    
    // 1. 命令内在复杂度
    const intrinsicComplexity = this.assessIntrinsicComplexity(parsedCommand);
    
    // 2. 上下文复杂度
    const contextualComplexity = await this.assessContextualComplexity(parsedCommand, context);
    
    // 3. 协作复杂度
    const collaborativeComplexity = this.assessCollaborativeComplexity(parsedCommand);
    
    // 4. 综合复杂度计算
    const overallComplexity = this.calculateOverallComplexity(
      intrinsicComplexity,
      contextualComplexity,
      collaborativeComplexity
    );
    
    return {
      overall_complexity: overallComplexity,
      complexity_factors: {
        intrinsic: intrinsicComplexity,
        contextual: contextualComplexity,
        collaborative: collaborativeComplexity
      },
      complexity_breakdown: this.generateComplexityBreakdown(overallComplexity),
      strategy_recommendations: this.generateStrategyRecommendations(overallComplexity)
    };
  }
  
  private assessIntrinsicComplexity(parsedCommand: ParsedCommand): IntrinsicComplexity {
    const command = parsedCommand.command;
    const parameters = parsedCommand.parameters;
    
    // 命令基础复杂度映射
    const baseComplexityMap = {
      // 简单命令 (0.1-0.3)
      '/explain': 0.2,
      '/document': 0.2,
      '/index': 0.1,
      
      // 中等命令 (0.3-0.6)
      '/analyze': 0.4,
      '/improve': 0.5,
      '/test': 0.4,
      '/git': 0.3,
      
      // 复杂命令 (0.6-0.9)
      '/implement': 0.7,
      '/build': 0.6,
      '/deploy': 0.8,
      '/design': 0.7,
      
      // 高复杂命令 (0.9-1.0)
      '/workflow': 0.9,
      '/train-model': 0.95,
      '/spawn': 1.0
    };
    
    let baseComplexity = baseComplexityMap[command] || 0.5;
    
    // 参数复杂度调整
    const parameterComplexityAdjustment = this.calculateParameterComplexity(parameters);
    
    // 范围复杂度调整
    const scopeComplexityAdjustment = this.calculateScopeComplexity(parameters);
    
    const finalComplexity = Math.min(
      baseComplexity + parameterComplexityAdjustment + scopeComplexityAdjustment,
      1.0
    );
    
    return {
      base_complexity: baseComplexity,
      parameter_adjustment: parameterComplexityAdjustment,
      scope_adjustment: scopeComplexityAdjustment,
      final_complexity: finalComplexity,
      complexity_contributors: this.identifyComplexityContributors(command, parameters)
    };
  }
  
  private async assessContextualComplexity(
    parsedCommand: ParsedCommand,
    context: ExecutionContext
  ): Promise<ContextualComplexity> {
    
    let contextualScore = 0;
    const factors: ContextualFactor[] = [];
    
    // 1. 项目规模复杂度
    const projectScale = this.assessProjectScale(context.projectContext);
    contextualScore += projectScale.score * 0.3;
    factors.push(projectScale);
    
    // 2. 技术栈复杂度
    const techStackComplexity = this.assessTechStackComplexity(context.projectContext.techStack);
    contextualScore += techStackComplexity.score * 0.25;
    factors.push(techStackComplexity);
    
    // 3. 依赖关系复杂度
    const dependencyComplexity = await this.assessDependencyComplexity(context.projectContext);
    contextualScore += dependencyComplexity.score * 0.2;
    factors.push(dependencyComplexity);
    
    // 4. 环境复杂度
    const environmentComplexity = this.assessEnvironmentComplexity(context.environmentContext);
    contextualScore += environmentComplexity.score * 0.15;
    factors.push(environmentComplexity);
    
    // 5. 集成复杂度
    const integrationComplexity = this.assessIntegrationComplexity(context);
    contextualScore += integrationComplexity.score * 0.1;
    factors.push(integrationComplexity);
    
    return {
      overall_score: Math.min(contextualScore, 1.0),
      contributing_factors: factors,
      risk_assessment: this.assessContextualRisks(factors),
      mitigation_strategies: this.generateMitigationStrategies(factors)
    };
  }
  
  private generateCandidateStrategies(
    complexityAssessment: ComplexityAssessment
  ): ExecutionStrategy[] {
    
    const strategies: ExecutionStrategy[] = [];
    const overallComplexity = complexityAssessment.overall_complexity;
    
    // 1. 传统策略 (总是可用)
    strategies.push(this.createTraditionalStrategy(complexityAssessment));
    
    // 2. 增强策略 (中等复杂度以上)
    if (overallComplexity >= 0.3) {
      strategies.push(this.createEnhancedStrategy(complexityAssessment));
    }
    
    // 3. Wave策略 (高复杂度)
    if (overallComplexity >= 0.7) {
      strategies.push(...this.createWaveStrategies(complexityAssessment));
    }
    
    // 4. 混合策略 (特定场景)
    if (this.shouldConsiderHybridStrategy(complexityAssessment)) {
      strategies.push(this.createHybridStrategy(complexityAssessment));
    }
    
    return strategies;
  }
  
  private createTraditionalStrategy(assessment: ComplexityAssessment): ExecutionStrategy {
    return {
      id: 'traditional',
      type: 'sequential',
      description: 'Single-agent sequential execution',
      agent_allocation: {
        primary_agent: this.selectPrimaryAgent(assessment),
        supporting_agents: [],
        coordination_mode: 'none'
      },
      execution_plan: {
        phases: ['analysis', 'execution', 'validation'],
        parallelism: 'none',
        checkpoints: ['pre_execution', 'post_execution']
      },
      resource_requirements: {
        cpu_cores: 1,
        memory_mb: 256,
        concurrent_operations: 1
      },
      expected_performance: {
        reliability: 0.95,
        speed: 0.7,
        resource_efficiency: 0.9
      }
    };
  }
  
  private createWaveStrategies(assessment: ComplexityAssessment): ExecutionStrategy[] {
    const waveStrategies: ExecutionStrategy[] = [];
    
    // Progressive Wave Strategy
    waveStrategies.push({
      id: 'wave_progressive',
      type: 'wave_orchestrated',
      description: 'Progressive enhancement with iterative refinement',
      wave_configuration: {
        strategy: 'progressive',
        phases: ['assess', 'improve', 'validate', 'refine'],
        quality_gates: ['phase_completion', 'quality_metrics', 'user_validation']
      },
      agent_allocation: {
        primary_agent: this.selectWavePrimaryAgent(assessment),
        wave_agents: this.selectWaveAgents('progressive', assessment),
        coordination_mode: 'wave_orchestrated'
      },
      execution_plan: {
        phases: ['wave_planning', 'wave_execution', 'wave_integration'],
        parallelism: 'wave_internal',
        checkpoints: ['wave_boundaries', 'quality_gates']
      },
      expected_performance: {
        reliability: 0.92,
        speed: 0.85,
        quality: 0.95
      }
    });
    
    // Systematic Wave Strategy
    waveStrategies.push({
      id: 'wave_systematic',
      type: 'wave_orchestrated',
      description: 'Systematic analysis and implementation',
      wave_configuration: {
        strategy: 'systematic',
        phases: ['analyze', 'plan', 'implement', 'verify'],
        quality_gates: ['analysis_completeness', 'plan_validation', 'implementation_quality']
      },
      agent_allocation: {
        primary_agent: 'architect',
        wave_agents: this.selectWaveAgents('systematic', assessment),
        coordination_mode: 'hierarchical_waves'
      },
      execution_plan: {
        phases: ['systematic_analysis', 'strategic_planning', 'coordinated_implementation', 'comprehensive_verification'],
        parallelism: 'phase_internal',
        checkpoints: ['analysis_approval', 'plan_approval', 'implementation_validation']
      },
      expected_performance: {
        reliability: 0.98,
        speed: 0.75,
        quality: 0.98
      }
    });
    
    return waveStrategies;
  }
  
  private async predictStrategyPerformance(
    strategies: ExecutionStrategy[]
  ): Promise<Map<string, PerformancePrediction>> {
    
    const predictions = new Map<string, PerformancePrediction>();
    
    for (const strategy of strategies) {
      const prediction = await this.predictIndividualStrategy(strategy);
      predictions.set(strategy.id, prediction);
    }
    
    return predictions;
  }
  
  private async predictIndividualStrategy(
    strategy: ExecutionStrategy
  ): Promise<PerformancePrediction> {
    
    // 获取历史性能数据
    const historicalData = await this.getHistoricalPerformanceData(strategy.type);
    
    // 基于策略特征调整预测
    const adjustedPrediction = this.adjustPredictionForStrategy(historicalData, strategy);
    
    return {
      strategy_id: strategy.id,
      predicted_metrics: {
        execution_time: adjustedPrediction.execution_time,
        success_rate: adjustedPrediction.success_rate,
        resource_usage: adjustedPrediction.resource_usage,
        quality_score: adjustedPrediction.quality_score
      },
      confidence_interval: adjustedPrediction.confidence_interval,
      risk_factors: this.identifyStrategyRisks(strategy),
      performance_variability: adjustedPrediction.variability
    };
  }
  
  private selectOptimalStrategy(
    candidates: ExecutionStrategy[],
    resourceEstimates: Map<string, ResourceEstimate>,
    performancePredictions: Map<string, PerformancePrediction>,
    constraints: ExecutionConstraints
  ): ExecutionStrategy {
    
    // 多目标优化评分
    const scoredStrategies = candidates.map(strategy => {
      const resourceEstimate = resourceEstimates.get(strategy.id);
      const performancePrediction = performancePredictions.get(strategy.id);
      
      const score = this.calculateStrategyScore(
        strategy,
        resourceEstimate,
        performancePrediction,
        constraints
      );
      
      return { strategy, score, resourceEstimate, performancePrediction };
    });
    
    // 约束条件过滤
    const feasibleStrategies = scoredStrategies.filter(scored => 
      this.satisfiesConstraints(scored.strategy, scored.resourceEstimate, constraints)
    );
    
    if (feasibleStrategies.length === 0) {
      // 如果没有策略满足约束，选择最接近的
      return this.selectBestEffortStrategy(scoredStrategies, constraints);
    }
    
    // 选择最高分的可行策略
    const bestStrategy = feasibleStrategies.reduce((best, current) => 
      current.score > best.score ? current : best
    );
    
    return bestStrategy.strategy;
  }
  
  private calculateStrategyScore(
    strategy: ExecutionStrategy,
    resourceEstimate: ResourceEstimate,
    performancePrediction: PerformancePrediction,
    constraints: ExecutionConstraints
  ): number {
    
    const weights = {
      performance: 0.4,
      reliability: 0.3,
      resource_efficiency: 0.2,
      constraint_satisfaction: 0.1
    };
    
    // 性能评分
    const performanceScore = this.normalizeMetric(
      performancePrediction.predicted_metrics.execution_time,
      constraints.max_execution_time,
      true // 越小越好
    );
    
    // 可靠性评分
    const reliabilityScore = performancePrediction.predicted_metrics.success_rate;
    
    // 资源效率评分
    const resourceEfficiencyScore = 1 - this.normalizeMetric(
      resourceEstimate.total_cost,
      constraints.max_resource_cost,
      false
    );
    
    // 约束满足评分
    const constraintSatisfactionScore = this.calculateConstraintSatisfaction(
      strategy,
      resourceEstimate,
      constraints
    );
    
    return (
      performanceScore * weights.performance +
      reliabilityScore * weights.reliability +
      resourceEfficiencyScore * weights.resource_efficiency +
      constraintSatisfactionScore * weights.constraint_satisfaction
    );
  }
}

Wave编排系统

Wave执行引擎

class WaveExecutionEngine {
  private waveOrchestrator = new WaveOrchestrator();
  private qualityGateManager = new QualityGateManager();
  private progressTracker = new WaveProgressTracker();
  private rollbackManager = new WaveRollbackManager();
  
  async executeWaveStrategy(
    strategy: WaveExecutionStrategy,
    context: ExecutionContext
  ): Promise<WaveExecutionResult> {
    
    // 1. Wave执行计划生成
    const executionPlan = await this.generateWaveExecutionPlan(strategy, context);
    
    // 2. 质量门设置
    const qualityGates = await this.setupQualityGates(executionPlan);
    
    // 3. 回滚点设置
    const rollbackPoints = await this.setupRollbackPoints(executionPlan);
    
    // 4. Wave执行监控初始化
    const monitor = this.initializeWaveMonitor(executionPlan);
    
    // 5. 逐Wave执行
    const waveResults = await this.executeWavesSequentially(
      executionPlan,
      qualityGates,
      rollbackPoints,
      monitor
    );
    
    // 6. 结果整合
    const integratedResult = await this.integrateWaveResults(waveResults);
    
    return {
      execution_plan: executionPlan,
      wave_results: waveResults,
      integrated_result: integratedResult,
      execution_metrics: monitor.getMetrics(),
      quality_assessment: await this.assessOverallQuality(waveResults)
    };
  }
  
  private async generateWaveExecutionPlan(
    strategy: WaveExecutionStrategy,
    context: ExecutionContext
  ): Promise<WaveExecutionPlan> {
    
    const waveType = strategy.wave_configuration.strategy;
    
    switch (waveType) {
      case 'progressive':
        return this.generateProgressiveWavePlan(strategy, context);
      case 'systematic':
        return this.generateSystematicWavePlan(strategy, context);
      case 'adaptive':
        return this.generateAdaptiveWavePlan(strategy, context);
      case 'enterprise':
        return this.generateEnterpriseWavePlan(strategy, context);
      default:
        throw new Error(`Unknown wave strategy: ${waveType}`);
    }
  }
  
  private generateProgressiveWavePlan(
    strategy: WaveExecutionStrategy,
    context: ExecutionContext
  ): WaveExecutionPlan {
    
    const waves: WaveDefinition[] = [
      {
        id: 'assessment_wave',
        name: 'Current State Assessment',
        description: 'Analyze current state and identify improvement opportunities',
        primary_agent: 'analyzer',
        supporting_agents: ['architect', 'qa'],
        objectives: [
          'Understand current implementation',
          'Identify pain points and issues',
          'Establish baseline metrics',
          'Document improvement opportunities'
        ],
        deliverables: [
          'Current state analysis report',
          'Issue identification matrix',
          'Baseline metrics dashboard',
          'Improvement recommendations'
        ],
        quality_criteria: [
          'Analysis completeness >= 90%',
          'Issue coverage >= 85%',
          'Stakeholder agreement >= 80%'
        ]
      },
      
      {
        id: 'improvement_wave',
        name: 'Targeted Improvements',
        description: 'Implement prioritized improvements based on assessment',
        primary_agent: this.selectImprovementAgent(context),
        supporting_agents: ['performance', 'security', 'refactorer'],
        objectives: [
          'Implement high-priority improvements',
          'Address critical issues',
          'Enhance system performance',
          'Improve code quality'
        ],
        deliverables: [
          'Improved implementation',
          'Performance enhancements',
          'Security hardening',
          'Code quality improvements'
        ],
        quality_criteria: [
          'All critical issues resolved',
          'Performance improvement >= 20%',
          'Code quality score >= 0.8'
        ]
      },
      
      {
        id: 'validation_wave',
        name: 'Comprehensive Validation',
        description: 'Validate improvements and ensure quality standards',
        primary_agent: 'qa',
        supporting_agents: ['performance', 'security'],
        objectives: [
          'Validate all improvements',
          'Ensure no regressions',
          'Verify performance gains',
          'Confirm security posture'
        ],
        deliverables: [
          'Validation test suite',
          'Performance benchmarks',
          'Security assessment',
          'Quality assurance report'
        ],
        quality_criteria: [
          'All tests pass',
          'No performance regressions',
          'Security standards met'
        ]
      },
      
      {
        id: 'refinement_wave',
        name: 'Final Refinement',
        description: 'Polish and optimize based on validation feedback',
        primary_agent: 'refactorer',
        supporting_agents: ['mentor', 'scribe'],
        objectives: [
          'Polish implementation',
          'Optimize edge cases',
          'Improve documentation',
          'Enhance maintainability'
        ],
        deliverables: [
          'Polished implementation',
          'Comprehensive documentation',
          'Maintenance guidelines',
          'Knowledge transfer materials'
        ],
        quality_criteria: [
          'Documentation completeness >= 95%',
          'Maintainability score >= 0.9',
          'User satisfaction >= 85%'
        ]
      }
    ];
    
    return {
      strategy_type: 'progressive',
      waves: waves,
      dependencies: this.calculateWaveDependencies(waves),
      resource_allocation: this.allocateResourcesAcrossWaves(waves),
      timeline: this.estimateWaveTimeline(waves),
      rollback_strategy: this.createProgressiveRollbackStrategy(waves)
    };
  }
  
  private async executeWavesSequentially(
    plan: WaveExecutionPlan,
    qualityGates: QualityGate[],
    rollbackPoints: RollbackPoint[],
    monitor: WaveMonitor
  ): Promise<WaveResult[]> {
    
    const waveResults: WaveResult[] = [];
    const waveContext = new WaveExecutionContext();
    
    for (let i = 0; i < plan.waves.length; i++) {
      const wave = plan.waves[i];
      const waveQualityGates = qualityGates.filter(gate => gate.wave_id === wave.id);
      
      try {
        monitor.startWave(wave.id);
        
        // Pre-wave quality gate check
        await this.checkPreWaveQualityGates(wave, waveQualityGates, waveContext);
        
        // Execute wave
        const waveResult = await this.executeIndividualWave(wave, waveContext, monitor);
        
        // Post-wave quality gate check
        await this.checkPostWaveQualityGates(waveResult, waveQualityGates);
        
        // Update context with wave result
        waveContext.updateFromWaveResult(waveResult);
        waveResults.push(waveResult);
        
        monitor.completeWave(wave.id, waveResult);
        
      } catch (error) {
        monitor.failWave(wave.id, error);
        
        // Wave failure handling
        const recoveryAction = await this.handleWaveFailure(
          wave,
          error,
          waveContext,
          rollbackPoints
        );
        
        if (recoveryAction.type === 'abort') {
          // Complete rollback
          await this.rollbackManager.rollbackToPoint(recoveryAction.rollback_point);
          throw new WaveExecutionError(`Wave execution aborted at ${wave.id}`, error);
        } else if (recoveryAction.type === 'retry') {
          // Retry current wave
          i--; // Retry current index
          continue;
        } else if (recoveryAction.type === 'skip') {
          // Skip current wave and continue
          waveContext.markWaveSkipped(wave, error);
          continue;
        }
      }
    }
    
    return waveResults;
  }
  
  private async executeIndividualWave(
    wave: WaveDefinition,
    context: WaveExecutionContext,
    monitor: WaveMonitor
  ): Promise<WaveResult> {
    
    const waveStartTime = Date.now();
    
    // 1. Agent activation and coordination
    const activeAgents = await this.activateWaveAgents(wave);
    
    // 2. Task decomposition and allocation
    const waveTasks = await this.decomposeWaveIntoTasks(wave, context);
    const taskAllocation = this.allocateTasksToAgents(waveTasks, activeAgents);
    
    // 3. Parallel task execution within wave
    const taskResults = await this.executeWaveTasksInParallel(taskAllocation, monitor);
    
    // 4. Result integration and validation
    const integratedResult = await this.integrateWaveTaskResults(taskResults, wave.objectives);
    
    // 5. Deliverable generation
    const deliverables = await this.generateWaveDeliverables(integratedResult, wave.deliverables);
    
    // 6. Quality assessment
    const qualityAssessment = await this.assessWaveQuality(integratedResult, wave.quality_criteria);
    
    const waveEndTime = Date.now();
    
    return {
      wave_id: wave.id,
      status: qualityAssessment.meets_criteria ? 'success' : 'partial_success',
      duration: waveEndTime - waveStartTime,
      task_results: taskResults,
      integrated_result: integratedResult,
      deliverables: deliverables,
      quality_assessment: qualityAssessment,
      agent_contributions: this.analyzeAgentContributions(taskResults),
      lessons_learned: this.extractWaveLessons(taskResults)
    };
  }
  
  private async executeWaveTasksInParallel(
    taskAllocation: TaskAllocation[],
    monitor: WaveMonitor
  ): Promise<TaskResult[]> {
    
    const taskExecutionPromises = taskAllocation.map(async (allocation) => {
      const task = allocation.task;
      const agent = allocation.agent;
      
      monitor.startTask(task.id, agent.type);
      
      try {
        const result = await agent.executeTask(task);
        monitor.completeTask(task.id, result);
        return {
          task_id: task.id,
          agent_type: agent.type,
          status: 'success',
          result: result,
          execution_time: result.execution_time,
          quality_metrics: result.quality_metrics
        };
      } catch (error) {
        monitor.failTask(task.id, error);
        
        // Task-level error recovery
        const recoveryResult = await this.attemptTaskRecovery(task, agent, error);
        
        return {
          task_id: task.id,
          agent_type: agent.type,
          status: recoveryResult.success ? 'recovered' : 'failed',
          result: recoveryResult.result,
          error: error,
          recovery_action: recoveryResult.action
        };
      }
    });
    
    const taskResults = await Promise.all(taskExecutionPromises);
    
    return taskResults;
  }
  
  private async integrateWaveResults(waveResults: WaveResult[]): Promise<IntegratedWaveResult> {
    // 1. 结果聚合
    const aggregatedResults = this.aggregateWaveResults(waveResults);
    
    // 2. 交叉验证
    const crossValidation = await this.performCrossWaveValidation(waveResults);
    
    // 3. 一致性检查
    const consistencyCheck = this.checkResultConsistency(aggregatedResults);
    
    // 4. 最终整合
    const finalIntegration = await this.performFinalIntegration(
      aggregatedResults,
      crossValidation,
      consistencyCheck
    );
    
    return {
      aggregated_results: aggregatedResults,
      cross_validation: crossValidation,
      consistency_assessment: consistencyCheck,
      final_result: finalIntegration,
      integration_quality: this.assessIntegrationQuality(finalIntegration),
      recommendations: this.generateIntegrationRecommendations(waveResults)
    };
  }
}

Wave质量保证

class WaveQualityAssurance {
  private qualityMetricsCollector = new QualityMetricsCollector();
  private qualityValidator = new QualityValidator();
  private qualityPredictor = new QualityPredictor();
  
  async setupQualityGates(plan: WaveExecutionPlan): Promise<QualityGate[]> {
    const qualityGates: QualityGate[] = [];
    
    for (const wave of plan.waves) {
      // Pre-wave quality gates
      qualityGates.push(...this.createPreWaveQualityGates(wave));
      
      // Post-wave quality gates
      qualityGates.push(...this.createPostWaveQualityGates(wave));
      
      // Inter-wave quality gates
      if (this.hasNextWave(wave, plan)) {
        qualityGates.push(...this.createInterWaveQualityGates(wave, plan));
      }
    }
    
    return qualityGates;
  }
  
  private createPreWaveQualityGates(wave: WaveDefinition): QualityGate[] {
    return [
      {
        id: `${wave.id}_pre_readiness`,
        name: 'Wave Readiness Check',
        wave_id: wave.id,
        gate_type: 'pre_wave',
        criteria: [
          {
            metric: 'agent_availability',
            threshold: 1.0,
            operator: '>=',
            description: 'All required agents must be available'
          },
          {
            metric: 'dependency_satisfaction',
            threshold: 1.0,
            operator: '>=',
            description: 'All wave dependencies must be satisfied'
          },
          {
            metric: 'resource_availability',
            threshold: 0.8,
            operator: '>=',
            description: 'Sufficient resources must be available'
          }
        ],
        validation_method: 'automated',
        blocking: true
      },
      
      {
        id: `${wave.id}_pre_context`,
        name: 'Context Completeness Check',
        wave_id: wave.id,
        gate_type: 'pre_wave',
        criteria: [
          {
            metric: 'context_completeness',
            threshold: 0.9,
            operator: '>=',
            description: 'Wave context must be sufficiently complete'
          },
          {
            metric: 'input_quality',
            threshold: 0.8,
            operator: '>=',
            description: 'Input quality must meet minimum standards'
          }
        ],
        validation_method: 'automated',
        blocking: true
      }
    ];
  }
  
  private createPostWaveQualityGates(wave: WaveDefinition): QualityGate[] {
    return [
      {
        id: `${wave.id}_post_deliverables`,
        name: 'Deliverable Quality Check',
        wave_id: wave.id,
        gate_type: 'post_wave',
        criteria: this.generateDeliverableCriteria(wave.deliverables),
        validation_method: 'hybrid',
        blocking: true
      },
      
      {
        id: `${wave.id}_post_objectives`,
        name: 'Objective Achievement Check',
        wave_id: wave.id,
        gate_type: 'post_wave',
        criteria: this.generateObjectiveCriteria(wave.objectives),
        validation_method: 'automated',
        blocking: false
      },
      
      {
        id: `${wave.id}_post_quality`,
        name: 'Quality Standards Verification',
        wave_id: wave.id,
        gate_type: 'post_wave',
        criteria: this.convertQualityCriteria(wave.quality_criteria),
        validation_method: 'automated',
        blocking: true
      }
    ];
  }
  
  async checkQualityGate(
    gate: QualityGate,
    context: QualityContext
  ): Promise<QualityGateResult> {
    
    const criteriaResults: CriteriaResult[] = [];
    
    for (const criteria of gate.criteria) {
      const result = await this.evaluateCriteria(criteria, context);
      criteriaResults.push(result);
    }
    
    const overallPass = criteriaResults.every(result => result.passed);
    const criticalFailures = criteriaResults.filter(
      result => !result.passed && result.critical
    );
    
    return {
      gate_id: gate.id,
      passed: overallPass,
      criteria_results: criteriaResults,
      critical_failures: criticalFailures,
      overall_score: this.calculateOverallScore(criteriaResults),
      recommendations: this.generateQualityRecommendations(criteriaResults),
      action_required: criticalFailures.length > 0 ? 'block' : (overallPass ? 'proceed' : 'review')
    };
  }
  
  private async evaluateCriteria(
    criteria: QualityCriteria,
    context: QualityContext
  ): Promise<CriteriaResult> {
    
    const metricValue = await this.collectMetric(criteria.metric, context);
    const passed = this.evaluateThreshold(metricValue, criteria.threshold, criteria.operator);
    
    return {
      criteria_id: criteria.metric,
      metric_value: metricValue,
      threshold: criteria.threshold,
      operator: criteria.operator,
      passed: passed,
      critical: criteria.critical || false,
      confidence: this.calculateConfidence(criteria.metric, metricValue, context),
      deviation: this.calculateDeviation(metricValue, criteria.threshold, criteria.operator),
      improvement_suggestions: this.generateImprovementSuggestions(criteria, metricValue, passed)
    };
  }
  
  private async collectMetric(
    metricName: string,
    context: QualityContext
  ): Promise<number> {
    
    switch (metricName) {
      case 'agent_availability':
        return this.calculateAgentAvailability(context);
      case 'dependency_satisfaction':
        return this.calculateDependencySatisfaction(context);
      case 'resource_availability':
        return this.calculateResourceAvailability(context);
      case 'context_completeness':
        return this.calculateContextCompleteness(context);
      case 'input_quality':
        return this.calculateInputQuality(context);
      case 'deliverable_completeness':
        return this.calculateDeliverableCompleteness(context);
      case 'objective_achievement':
        return this.calculateObjectiveAchievement(context);
      case 'code_quality_score':
        return await this.calculateCodeQualityScore(context);
      case 'test_coverage':
        return await this.calculateTestCoverage(context);
      case 'performance_score':
        return await this.calculatePerformanceScore(context);
      case 'security_score':
        return await this.calculateSecurityScore(context);
      default:
        throw new Error(`Unknown quality metric: ${metricName}`);
    }
  }
  
  private async calculateCodeQualityScore(context: QualityContext): Promise<number> {
    const qualityFactors = {
      maintainability: await this.assessMaintainability(context),
      readability: await this.assessReadability(context),
      complexity: await this.assessComplexity(context),
      consistency: await this.assessConsistency(context),
      documentation: await this.assessDocumentation(context)
    };
    
    const weights = {
      maintainability: 0.3,
      readability: 0.25,
      complexity: 0.2,
      consistency: 0.15,
      documentation: 0.1
    };
    
    return Object.entries(qualityFactors).reduce((score, [factor, value]) => {
      return score + (value * weights[factor]);
    }, 0);
  }
  
  private generateQualityRecommendations(
    criteriaResults: CriteriaResult[]
  ): QualityRecommendation[] {
    
    const recommendations: QualityRecommendation[] = [];
    
    // 找出失败的关键指标
    const failedCriticalCriteria = criteriaResults.filter(
      result => !result.passed && result.critical
    );
    
    // 找出边缘通过的指标
    const marginalCriteria = criteriaResults.filter(
      result => result.passed && result.deviation < 0.1
    );
    
    // 生成关键失败的建议
    for (const failed of failedCriticalCriteria) {
      recommendations.push({
        priority: 'critical',
        type: 'fix_required',
        criteria: failed.criteria_id,
        issue: `Critical criteria ${failed.criteria_id} failed`,
        suggestion: failed.improvement_suggestions[0],
        estimated_effort: this.estimateFixEffort(failed),
        impact: 'blocking'
      });
    }
    
    // 生成边缘情况的建议
    for (const marginal of marginalCriteria) {
      recommendations.push({
        priority: 'medium',
        type: 'improvement_opportunity',
        criteria: marginal.criteria_id,
        issue: `Criteria ${marginal.criteria_id} barely passed`,
        suggestion: 'Consider strengthening this area for better reliability',
        estimated_effort: 'low',
        impact: 'preventive'
      });
    }
    
    return recommendations;
  }
}

---

小结

Claude Code 的命令系统展现了现代 AI 编程助手的几个关键特征：

核心创新

1. 智能解析引擎: 自然语言+结构化命令的多路径融合解析
2. 动态策略选择: 基于复杂度评估的执行策略自动选择
3. Wave编排系统: 多阶段任务分解和质量门控的协调执行
4. 质量保证机制: 全流程的质量监控和自动化验证

技术优势

• 高智能化: 70%+ 置信度的意图识别和参数推断
• 强适应性: 基于上下文的动态策略调整和优化
• 高可靠性: 多层质量门控和自动回滚机制
• 强扩展性: 模块化设计支持新命令和策略的快速集成

系统效果

• 用户友好: 自然语言命令解析降低使用门槛
• 执行高效: 智能策略选择和Wave编排提升40-70%性能
• 质量保证: 多层验证确保输出质量和系统稳定性
• 持续优化: 基于执行反馈的策略学习和改进

这套命令系统不仅支持了 Claude Code 当前的 24 个核心命令，也为未来更复杂的命令和工作流扩展提供了坚实的技术基础。

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下一步: 查看 MCP集成机制 了解4个MCP服务器的协调和扩展原理