MCP WordPress Server

#!/usr/bin/env node import fs from "fs"; import path from "path"; import { fileURLToPath } from "url"; const __filename = fileURLToPath(import.meta.url); const __dirname = path.dirname(__filename); /** * Compare current performance with previous results */ function comparePerformance() { const currentFile = path.join(__dirname, "../results/current/evaluation-summary.json"); const previousFile = path.join(__dirname, "../results/previous/evaluation-summary.json"); try { if (!fs.existsSync(currentFile) || !fs.existsSync(previousFile)) { console.log("⚠️ Cannot compare: missing current or previous results"); return; } const current = JSON.parse(fs.readFileSync(currentFile, "utf8")); const previous = JSON.parse(fs.readFileSync(previousFile, "utf8")); // Compare overall scores const scoreDiff = parseFloat(current.overall_score) - parseFloat(previous.overall_score); const passRateDiff = current.tests_passed / current.total_tests - previous.tests_passed / previous.total_tests; console.log("📊 Performance Comparison"); console.log("========================"); console.log(`Current Score: ${current.overall_score}/5.0`); console.log(`Previous Score: ${previous.overall_score}/5.0`); console.log(`Change: ${scoreDiff > 0 ? "+" : ""}${scoreDiff.toFixed(2)}`); console.log(""); console.log(`Current Pass Rate: ${((current.tests_passed / current.total_tests) * 100).toFixed(1)}%`); console.log(`Previous Pass Rate: ${((previous.tests_passed / previous.total_tests) * 100).toFixed(1)}%`); console.log(`Change: ${passRateDiff > 0 ? "+" : ""}${(passRateDiff * 100).toFixed(1)}%`); // Check for regression const regressionThreshold = -0.2; // 0.2 point decrease if (scoreDiff < regressionThreshold) { console.log(""); console.log("❌ PERFORMANCE REGRESSION DETECTED!"); console.log(`Score decreased by ${Math.abs(scoreDiff).toFixed(2)} points`); // Compare failed tests const newFailures = current.failed_tests?.filter( (test) => !previous.failed_tests?.some((prevTest) => prevTest.name === test.name), ) || []; if (newFailures.length > 0) { console.log(""); console.log("New failing tests:"); newFailures.forEach((test) => { console.log(` - ${test.name}: ${test.score}/5.0`); }); } process.exit(1); } // Check for significant improvement const improvementThreshold = 0.2; if (scoreDiff > improvementThreshold) { console.log(""); console.log("✅ PERFORMANCE IMPROVEMENT DETECTED!"); console.log(`Score increased by ${scoreDiff.toFixed(2)} points`); // Compare newly passing tests const newPasses = previous.failed_tests?.filter( (test) => !current.failed_tests?.some((currentTest) => currentTest.name === test.name), ) || []; if (newPasses.length > 0) { console.log(""); console.log("Newly passing tests:"); newPasses.forEach((test) => { console.log(` - ${test.name}`); }); } } // Category comparison if (current.categories && previous.categories) { console.log(""); console.log("📂 Category Changes:"); Object.keys(current.categories).forEach((category) => { const curr = current.categories[category]; const prev = previous.categories[category]; if (prev) { const categoryDiff = parseFloat(curr.avg_score) - parseFloat(prev.avg_score); if (Math.abs(categoryDiff) > 0.1) { console.log( ` ${category}: ${prev.avg_score} → ${curr.avg_score} (${ categoryDiff > 0 ? "+" : "" }${categoryDiff.toFixed(2)})`, ); } } else { console.log(` ${category}: NEW - ${curr.avg_score}/5.0`); } }); } console.log(""); console.log("✅ Performance comparison complete"); } catch (error) { console.error("❌ Error comparing performance:", error.message); process.exit(1); } } if (import.meta.url === `file://${process.argv[1]}`) { comparePerformance(); } export { comparePerformance };