mcp-adr-analysis-server/dist/src/types/ape-framework.js

MCP server for analyzing Architectural Decision Records and project architecture

/**
 * TypeScript interfaces for Automatic Prompt Engineer (APE) Framework
 * Implements automatic prompt generation, evaluation, and optimization
 */
import { z } from 'zod';
export const APEConfigSchema = z.object({
    candidateCount: z.number().min(1).max(20),
    evaluationCriteria: z.array(z.enum([
        'task-completion',
        'clarity',
        'specificity',
        'robustness',
        'efficiency',
        'context-awareness'
    ])),
    optimizationRounds: z.number().min(1).max(10),
    selectionStrategy: z.enum([
        'highest-score',
        'multi-criteria',
        'ensemble',
        'context-aware',
        'balanced'
    ]),
    cacheEnabled: z.boolean(),
    performanceTracking: z.boolean(),
    maxOptimizationTime: z.number().min(1000),
    qualityThreshold: z.number().min(0).max(1),
    diversityWeight: z.number().min(0).max(1),
});
// ============================================================================
// Export Schemas for Runtime Validation
// ============================================================================
export const PromptCandidateSchema = z.object({
    id: z.string(),
    prompt: z.string(),
    instructions: z.string(),
    context: z.any(),
    generationStrategy: z.enum([
        'template-variation',
        'semantic-variation',
        'style-variation',
        'length-variation',
        'structure-variation',
        'hybrid-approach'
    ]),
    metadata: z.object({
        generatedAt: z.string(),
        generationTime: z.number(),
        strategy: z.string(),
        templateUsed: z.string().optional(),
        variationApplied: z.array(z.string()).optional(),
        complexity: z.number().min(0).max(1),
        estimatedQuality: z.number().min(0).max(1),
        tokens: z.number()
    }),
    parentId: z.string().optional(),
    generation: z.number()
});
export const OptimizationResultSchema = z.object({
    optimizedPrompt: z.object({
        prompt: z.string(),
        instructions: z.string(),
        context: z.any()
    }),
    originalPrompt: z.object({
        prompt: z.string(),
        instructions: z.string(),
        context: z.any()
    }),
    improvementScore: z.number().min(0).max(1),
    optimizationRounds: z.number(),
    candidatesEvaluated: z.number(),
    totalOptimizationTime: z.number(),
    cacheKey: z.string(),
    metadata: z.object({
        optimizedAt: z.string(),
        apeVersion: z.string(),
        configUsed: APEConfigSchema,
        strategiesApplied: z.array(z.string()),
        evaluationCriteria: z.array(z.string()),
        selectionStrategy: z.string(),
        qualityImprovement: z.number().min(0).max(1),
        convergenceRound: z.number()
    }),
    performanceMetrics: z.object({
        generationTime: z.number(),
        evaluationTime: z.number(),
        selectionTime: z.number(),
        totalTime: z.number(),
        candidatesGenerated: z.number(),
        candidatesEvaluated: z.number(),
        cacheHits: z.number(),
        cacheMisses: z.number(),
        memoryUsage: z.number(),
        successRate: z.number().min(0).max(1)
    })
});
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