perf-lens/dist/utils/codeAnalysis.d.ts

AI-powered frontend performance optimizer

import type { AIModelConfig, AnalysisConfig } from '../types/config.js';
import { type Finding } from '../ai/schema.js';
interface CodeAnalysisResult {
    critical: string[];
    warnings: string[];
    suggestions: string[];
    findings: Finding[];
    fileSpecificIssues: Record<string, {
        critical: string[];
        warnings: string[];
        suggestions: string[];
    }>;
}
interface LighthouseContext {
    metrics: string;
    analysis: {
        coreWebVitals: string;
        performanceOpportunities: string;
        diagnostics: string;
    };
}
interface CodeAnalysisConfig extends AnalysisConfig {
    lighthouseContext?: LighthouseContext;
    ai?: AIModelConfig;
    verbose?: boolean;
    noCache?: boolean;
}
/**
 * Builds the stable Lighthouse context string shared by every batch prompt.
 * It sits in the cached system prefix, so keep it byte-identical across calls.
 */
export declare function buildLighthouseContext(lighthouseContext?: LighthouseContext): string | undefined;
/**
 * Analyzes the codebase for performance issues
 * @param {CodeAnalysisConfig} config - Configuration for codebase analysis
 * @returns {Promise<CodeAnalysisResult>} Complete analysis results including critical issues, warnings, and suggestions
 */
export declare function analyzeCodebase(config: CodeAnalysisConfig): Promise<CodeAnalysisResult>;
/**
 * Agent-mode analysis: instead of batching every file into prompts, the model
 * investigates the codebase itself through tool use and reports findings.
 * @param {CodeAnalysisConfig} config - Same configuration as analyzeCodebase
 * @returns {Promise<CodeAnalysisResult>} Analysis results in the same report shape
 */
export declare function analyzeCodebaseWithAgent(config: CodeAnalysisConfig): Promise<CodeAnalysisResult>;
export {};
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