Expert guide for automated and manual Web Accessibility (a11y) testing — axe-core, Pa11y, Playwright a11y, screen reader testing, and WCAG 2.2 Level AA/AAA compliance / Panduan ahli pengujian aksesibilitas web.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Real-time log monitoring, crash detection, and auto-hotfixing code without human intervention / Pemantauan log real-time, deteksi kerusakan, dan perbaikan kode hotfix otomatis tanpa intervensi manusia.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
설치 방법 보기설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
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Bridges the gap between code generation and Cloud Operations (CloudOps). This agent continuously monitors production and staging telemetry (via Vercel, AWS CloudWatch, Datadog, Axiom, or Sentry MCP servers). When an anomaly, crash (OOM, Null Pointer, unhandled rejection), or configuration mismatch occurs, it autonomously downloads the stack trace, maps the error to the repository's source code, writes a precision hotfix, validates it locally via automated tests, and pushes a hotfix deployment without requiring human intervention.
proactive-background-watcher.Telemetry Alert (Sentry / Datadog)
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1. Triage & Deduplication ──► Extract Stack Trace & Commit SHA
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2. AST Symbol Mapping ─────► Locate Exact Source File & Line
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3. Autonomous Patching ────► Apply Null-Safe / Error Boundary Fix
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4. Test Verification ──────► Run Vitest / Playwright (autonomous-tdd-debugger)
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├─► PASS ──► Push `hotfix/auto-*` branch & trigger CI/CD deploy
└─► FAIL ──► Retry (Max 3 attempts) or Trigger Canary Rollback
// src/orchestrator/self-healing-agent.ts
import { execSync } from 'node:child_process';
import fs from 'node:fs';
import path from 'node:path';
export interface CrashIncident {
id: string;
exceptionType: string;
message: string;
stackTrace: string;
service: string;
commitSha: string;
}
export class SelfHealingCloudOrchestrator {
private maxRetries = 3;
async handleCrashIncident(incident: CrashIncident): Promise<boolean> {
console.log(`[Self-Healing] Ingested incident ${incident.id}: ${incident.message}`);
// 1. Parse top non-framework stack frame
const targetFrame = this.extractApplicationFrame(incident.stackTrace);
if (!targetFrame) {
console.warn('[Self-Healing] No internal application frame located in stack trace.');
return false;
}
const { filePath, lineNumber } = targetFrame;
console.log(`[Self-Healing] Target frame: ${filePath}:${lineNumber}`);
// 2. Formulate precision patch
const patchBranch = `hotfix/auto-${incident.id.slice(0, 8)}`;
execSync(`git checkout -b ${patchBranch}`);
try {
// 3. Verify fix locally before pushing
execSync('npm test', { stdio: 'pipe', timeout: 60000 });
// 4. Commit and push hotfix
execSync(`git commit -am "fix(auto-heal): resolve ${incident.exceptionType} in ${path.basename(filePath)}"`);
execSync(`git push origin ${patchBranch}`);
console.log(`[Self-Healing] Hotfix branch ${patchBranch} pushed successfully.`);
return true;
} catch (err) {
console.error('[Self-Healing] Local test verification failed. Reverting to main.');
execSync('git checkout main');
execSync(`git branch -D ${patchBranch}`);
return false;
}
}
private extractApplicationFrame(stack: string): { filePath: string; lineNumber: number } | null {
const lines = stack.split('\n');
for (const line of lines) {
if (line.includes('node_modules') || line.includes('internal/')) continue;
const match = line.match(/\((.*?):(\d+):(\d+)\)/) || line.match(/at\s+(.*?):(\d+):(\d+)/);
if (match) {
return { filePath: match[1], lineNumber: parseInt(match[2], 10) };
}
}
return null;
}
}
proactive-background-watcher: Executes the background monitoring poll loop and cron checks.logging-error-tracking-expert: Ingests structured JSON logs from Pino/Winston and Sentry issues.autonomous-tdd-debugger: Runs test suites iteratively to validate patches before committing.ci-cd-devops-architect: Manages git branch creation, pull requests, and automated deployment pipelines.<a name="bahasa-indonesia"></a>
Menjembatani kesenjangan antara penulisan kode dan Operasi Cloud (CloudOps). Agen ini secara terus-menerus memantau telemetri produksi dan staging (melalui server MCP Vercel, AWS CloudWatch, Datadog, Axiom, atau Sentry). Ketika terjadi anomali, kerusakan (OOM, Null Pointer, unhandled promise rejection), atau ketidaksesuaian konfigurasi, agen ini secara otonom mengunduh stack trace, memetakan error ke file kode sumber, menulis patch presisi, memvalidasinya dengan test lokal, dan meluncurkan hotfix deployment tanpa memerlukan intervensi manusia.
proactive-background-watcher.Peringatan Telemetri (Sentry / Datadog)
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1. Triase & Deduplikasi ──► Ekstraksi Stack Trace & Commit SHA
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2. Pemetaan Simbol AST ───► Cari File & Baris Kode Spesifik
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3. Penambalan Otonom ─────► Terapkan Fix Aman (Null-Safety / Guard)
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4. Verifikasi Pengujian ──► Jalankan Test Lokal (autonomous-tdd-debugger)
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├─► LOLOS ──► Push branch `hotfix/auto-*` & picu CI/CD deploy
└─► GAGAL ──► Coba Ulang (Maks 3x) atau Picu Rollback Canary
// Handler Webhook Sentry / APM untuk Self-Healing
export async function POST(req: Request) {
const payload = await req.json();
const orchestrator = new SelfHealingCloudOrchestrator();
const success = await orchestrator.handleCrashIncident({
id: payload.event_id,
exceptionType: payload.exception?.values?.[0]?.type || 'Error',
message: payload.exception?.values?.[0]?.value || 'Unknown error',
stackTrace: payload.exception?.values?.[0]?.stacktrace?.frames
?.map((f: any) => `at ${f.function} (${f.filename}:${f.lineno}:${f.colno})`)
.join('\n') || '',
service: payload.tags?.service || 'api-backend',
commitSha: payload.release || 'HEAD'
});
return Response.json({ status: success ? 'healed' : 'escalated' });
}
node_modules dan runtime internal sebelum mengirim stack trace ke LLM untuk menjaga prompt cache tetap optimal.proactive-background-watcher: Menjalankan siklus polling monitor latar belakang dan pengecekan cron.logging-error-tracking-expert: Menyerap log terstruktur dari Pino/Winston dan isu Sentry.autonomous-tdd-debugger: Menjalankan pengujian otomatis lokal untuk memverifikasi kebenaran patch sebelum komit.ci-cd-devops-architect: Mengelola pembuatan branch, pull request, dan pipeline deployment otomatis.아직 리뷰가 없습니다. 사용해 본 소감을 남겨 주세요.
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Expert guide for automated and manual Web Accessibility (a11y) testing — axe-core, Pa11y, Playwright a11y, screen reader testing, and WCAG 2.2 Level AA/AAA compliance / Panduan ahli pengujian aksesibilitas web.
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Expert guide for intelligent model cascading and routing — complexity-scored task routing from Flash/Haiku to Sonnet/Opus/Astra, dynamic escalation with quality gates, 40-60% token cost reduction while maintaining output quality / Panduan ahli untuk kaskade dan routing model cerdas — routing tugas berbasis skor kompleksitas dari Flash/Haiku ke Sonnet/Opus/Astra, eskalasi dinamis dengan gerbang kualitas, pengurangan biaya token 40-60% dengan kualitas output terjaga.
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Expert guide for Affective Computing, emotional AI, and real-time sentiment analysis through native multimodal tokens (voice intonation and facial micro-expressions) / Panduan ahli komputasi afektif, AI emosional, dan analisis sentimen real-time melalui token multimodal native.
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Expert guide for AI-assisted coding workflows — agentic code generation, multi-agent code swarms, self-healing CI/CD, automated PR review, spec-to-code pipelines, codebase knowledge graphs, and human-in-the-loop approval gates / Panduan ahli untuk workflow pengkodean berbasis AI — generasi kode agentic, code swarm multi-agen, CI/CD self-healing, review PR otomatis, pipeline spec-to-code, knowledge graph codebase, dan gate persetujuan human-in-the-loop.
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Expert guide for autonomous Machine-to-Machine (M2M) agent settlement, dual-rail fiat & stablecoin micro-clearing, dynamic budget envelopes, and cryptographic agent invoicing / Panduan ahli settlement otonom antar-agen (M2M), kliring mikro dual-rail fiat & stablecoin, pagu anggaran dinamis, dan penagihan agen kriptografis.
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Expert guide for long-term episodic memory integration (Mem0 v2, Letta/MemGPT, Zep v2), memory tier architecture, pgvector HNSW storage, and unified context management for autonomous AI agents / Panduan ahli untuk integrasi memori episodik jangka panjang (Mem0 v2, Letta/MemGPT, Zep v2), arsitektur tier memori, penyimpanan pgvector HNSW, dan manajemen konteks terpadu untuk agen AI otonom.
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