Skip to main content
Glama

CTS MCP Server

by EricA1019
suggestion_engine.d.tsโ€ข2.72 kB
/** * Refactoring Suggestion Engine - Phase 3 HOP 3.4 * * AI-powered refactoring suggestion engine using similarity detection and naming validation. * * Architecture: * - Similarity detection: Levenshtein distance with early termination heuristics * - Naming validation: GDScript snake_case convention enforcement * - Confidence scoring: Heuristic-based confidence for merge suggestions * * Performance: * - Target: <2s for 300 signals * - Optimization: Early termination reduces 45K โ†’ 5K comparisons * - Heuristics: First char match, length difference โ‰ค3 * * @module refactoring/suggestion_engine */ import type { SignalGraph } from '../graph/types.js'; import { type RefactorSuggestion, type RefactoringStats } from './types.js'; /** * Generates refactoring suggestions for signal names. * * @example * ```typescript * const engine = new RefactoringEngine(); * const suggestions = await engine.generateSuggestions(signalGraph); * * console.log(`Generated ${suggestions.length} suggestions`); * suggestions.forEach(s => { * console.log(`${s.type}: ${s.target} โ†’ ${s.replacement} (${s.confidence})`); * }); * ``` */ export declare class RefactoringEngine { private stats; /** * Generate refactoring suggestions for signal graph. * * @param graph - Complete signal graph * @returns Array of refactoring suggestions sorted by confidence (highest first) */ generateSuggestions(graph: SignalGraph): Promise<RefactorSuggestion[]>; /** * Detect similar signal names using Levenshtein distance with early termination. * * Early termination heuristics: * 1. First character mismatch โ†’ skip (different category likely) * 2. Length difference > 3 โ†’ skip (too dissimilar) * * @param signals - Array of signal names * @returns Array of merge suggestions */ private detectSimilarSignals; /** * Compute confidence for similarity-based merge suggestions. * * Confidence factors: * - Distance 1 + both snake_case: 0.99 * - Distance 1: 0.98 * - Distance 2 + both snake_case: 0.98 * - Distance 2: 0.97 (below threshold, not suggested) * * @param s1 - First signal name * @param s2 - Second signal name * @param distance - Levenshtein distance * @returns Confidence score (0.0-1.0) */ private computeSimilarityConfidence; /** * Format violation type for human-readable reason. */ private formatViolationType; /** * Get refactoring statistics. */ getStats(): RefactoringStats; /** * Reset refactoring statistics. */ resetStats(): void; } //# sourceMappingURL=suggestion_engine.d.ts.map

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/EricA1019/CTS_MCP'

If you have feedback or need assistance with the MCP directory API, please join our Discord server