/**
 * @fileoverview Semantic skill matching using embeddings
 * @module @skillsmith/core/matching/SkillMatcher
 * @see SMI-602: Implement recommend_skills MCP tool
 *
 * Provides semantic similarity matching between skills using
 * the EmbeddingService for vector-based comparisons.
 *
 * @example
 * const matcher = new SkillMatcher({ useFallback: true });
 * const matches = await matcher.findSimilarSkills('react testing', skills, 5);
 */
import { type EmbeddingServiceOptions } from '../embeddings/index.js';
/**
 * Skill data for matching
 */
export interface MatchableSkill {
    /** Unique skill identifier */
    id: string;
    /** Skill display name */
    name: string;
    /** Skill description */
    description: string;
    /** Optional trigger phrases for overlap detection */
    triggerPhrases?: string[];
    /** Optional keywords for keyword-based fallback */
    keywords?: string[];
    /** Optional quality score (0-100) */
    qualityScore?: number;
}
/**
 * Result of a skill match
 */
export interface SkillMatchResult {
    /** Matched skill */
    skill: MatchableSkill;
    /** Semantic similarity score (0-1) */
    similarityScore: number;
    /** Why this skill matched */
    matchReason: string;
}
/**
 * Options for SkillMatcher
 */
export interface SkillMatcherOptions extends EmbeddingServiceOptions {
    /** Minimum similarity threshold (0-1, default 0.3) */
    minSimilarity?: number;
    /** Quality score weight (0-1, default 0.3) */
    qualityWeight?: number;
}
/**
 * Semantic skill matcher using embeddings.
 *
 * Finds skills similar to a query using vector similarity,
 * with optional quality score boosting.
 *
 * @example
 * const matcher = new SkillMatcher({ useFallback: true });
 * await matcher.initialize(skills);
 * const results = await matcher.findSimilarSkills('react testing', skills);
 */
export declare class SkillMatcher {
    private embeddingService;
    private skillEmbeddings;
    private initialized;
    private readonly minSimilarity;
    private readonly qualityWeight;
    constructor(options?: SkillMatcherOptions);
    /**
     * Check if matcher is using fallback mode
     */
    isUsingFallback(): boolean;
    /**
     * Initialize skill embeddings for a set of skills.
     * Call this before matching for best performance.
     */
    initialize(skills: MatchableSkill[]): Promise<void>;
    /**
     * Convert skill to text for embedding
     */
    private skillToText;
    /**
     * Find skills similar to a query string.
     *
     * @param query - Search query or context description
     * @param skills - Pool of skills to search
     * @param limit - Maximum results to return
     * @returns Ranked list of matching skills
     *
     * @example
     * const matches = await matcher.findSimilarSkills(
     *   'React TypeScript frontend testing',
     *   availableSkills,
     *   5
     * );
     */
    findSimilarSkills(query: string, skills: MatchableSkill[], limit?: number): Promise<SkillMatchResult[]>;
    /**
     * Find skills similar to a set of installed skills.
     *
     * @param installedSkills - Currently installed skills
     * @param candidateSkills - Pool of skills to recommend from
     * @param limit - Maximum results
     * @returns Ranked list of recommended skills
     */
    findComplementarySkills(installedSkills: MatchableSkill[], candidateSkills: MatchableSkill[], limit?: number): Promise<SkillMatchResult[]>;
    /**
     * Generate a human-readable match reason
     */
    private generateMatchReason;
    /**
     * Get embedding dimension
     */
    getEmbeddingDimension(): number;
    /**
     * Clear cached embeddings
     */
    clear(): void;
    /**
     * Close resources
     */
    close(): void;
}
export default SkillMatcher;
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