mcp-ai-agent-guidelines/dist/gateway/output-selector.d.ts

A comprehensive Model Context Protocol server providing advanced tools, resources, and prompts for implementing AI agent best practices

/**
 * Output Selector - Intelligent strategy selection based on context
 *
 * Analyzes context signals to recommend the most appropriate output strategy.
 * Provides automatic selection with confidence scoring and reasoning.
 *
 * @module gateway/output-selector
 */
import { OutputApproach } from "../strategies/output-strategy.js";
/**
 * Context signals used to determine the appropriate output strategy.
 *
 * @interface ContextSignals
 */
export interface ContextSignals {
    /** Keywords extracted from context or user input (expected to be normalized to lowercase) */
    keywords: string[];
    /** Optional domain type identifier (e.g., "PromptResult", "SessionState") */
    domainType?: string;
    /** Whether the context references a constitution or constraint document */
    hasConstitution?: boolean;
}
/**
 * Result of output strategy recommendation.
 *
 * @interface RecommendationResult
 */
export interface RecommendationResult {
    /** Recommended output approach */
    approach: OutputApproach;
    /** Confidence score (0-100) */
    confidence: number;
    /** Human-readable reasoning for the recommendation */
    reasoning: string;
}
/**
 * Extract keywords from context text.
 *
 * Simple extraction that splits on whitespace and punctuation,
 * filters out common stop words, and normalizes to lowercase.
 * Preserves file extensions like .md in filenames.
 *
 * @param context - Input text to analyze
 * @returns Array of extracted keywords
 */
export declare function extractKeywords(context: string): string[];
/**
 * Select the appropriate output approach based on context signals.
 *
 * Decision logic:
 * 1. If constitution is referenced → SPECKIT (high confidence)
 * 2. If ≥2 Spec-Kit signals detected → SPECKIT
 * 3. Otherwise → CHAT (default)
 *
 * @param signals - Context signals for strategy selection
 * @returns Recommended output approach
 */
export declare function selectApproach(signals: ContextSignals): OutputApproach;
/**
 * Calculate confidence score for a recommendation.
 *
 * Confidence scoring:
 * - Constitution present: 95%
 * - 3+ Spec-Kit signals: 90%
 * - 2 Spec-Kit signals: 75%
 * - Default (CHAT): 60%
 *
 * @param signals - Context signals
 * @param approach - Selected approach
 * @returns Confidence score (0-100)
 */
export declare function calculateConfidence(signals: ContextSignals, approach: OutputApproach): number;
/**
 * Generate human-readable reasoning for the recommendation.
 *
 * @param signals - Context signals
 * @param approach - Selected approach
 * @returns Reasoning explanation
 */
export declare function generateReasoning(signals: ContextSignals, approach: OutputApproach): string;
/**
 * Recommend an output approach based on context analysis.
 *
 * This is the main entry point for strategy selection. It:
 * 1. Extracts keywords from context
 * 2. Detects constitution references
 * 3. Selects appropriate approach
 * 4. Calculates confidence and generates reasoning
 *
 * @param context - Input context text to analyze
 * @returns Recommendation with approach, confidence, and reasoning
 *
 * @example
 * ```typescript
 * const result = recommendApproach('Create a spec.md and plan.md for the project');
 * // Returns: { approach: OutputApproach.SPECKIT, confidence: 75, reasoning: "..." }
 * ```
 */
export declare function recommendApproach(context: string): RecommendationResult;
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