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.
日本語の概要は準備中です。原文の説明を表示しています。
Expert guide for Generative UI architectures, ephemeral dynamic interfaces, and real-time streaming of React Server Components (RSC) driven by Gemini 4 Pro / Panduan ahli arsitektur Generative UI, antarmuka dinamis efemeral, dan streaming RSC real-time yang didorong oleh Gemini 4 Pro.
インストールする前に、エージェントに与えられる指示の中身を確認できます。
<a name="english"></a>
Connects and orchestrates with vercel-ai-sdk-expert, senior-frontend, ui-ux-pro-max, design-system-architect, gemini-agent-booster, and multi-agent-orchestration.
Standard UIs are static and pre-compiled. In the Gemini 4 Pro era, interfaces are ephemeral: generated in real-time based on the user's immediate intent, and destroyed when no longer needed. This skill orchestrates Generative UI systems using React Server Components (RSC), Tool-Driven UI injection, and Vercel AI SDK, allowing LLMs to directly stream fully functional, interactive components (charts, forms, dashboards) instead of markdown text.
streamUI or tool-call-to-component mappings.getWeather). The server intercepts this tool call and streams a <WeatherWidget /> React Server Component directly to the client.<WeatherSkeleton />) the millisecond the LLM begins emitting the tool call token, replaced by the final RSC once execution completes.Even when rendered dynamically on-the-fly, AI-generated components MUST strictly observe Sovereign Visual Hierarchy:
bg-white dark:bg-neutral-900 border border-neutral-200/80 dark:border-neutral-800 rounded-xl shadow-xs).text-[11px] font-semibold uppercase tracking-wider text-neutral-500) -> Title (text-lg font-semibold tracking-tight text-neutral-900 dark:text-neutral-50) -> Body (text-sm text-neutral-600 dark:text-neutral-300).tabular-nums on all streaming counters, prices, metrics, and telemetry stats.import { streamUI } from 'ai/rsc';
import { google } from '@ai-sdk/google';
import { z } from 'zod';
import { FlightTracker } from '@/components/flight-tracker';
import { Skeleton } from '@/components/skeleton';
export async function submitMessage(userInput: string) {
'use server';
const result = await streamUI({
model: google('gemini-4-pro'),
prompt: userInput,
text: ({ content, done }) => {
return <div>{content}</div>;
},
tools: {
trackFlight: {
description: 'Track a flight status in real-time',
parameters: z.object({ flightNumber: z.string() }),
generate: async function* ({ flightNumber }) {
yield <Skeleton className="h-40 w-full" />; // Optimistic UI
const data = await fetchFlightData(flightNumber); // Server-side execution
return <FlightTracker data={data} />; // Final RSC streamed to client with Sovereign Visual Hierarchy
},
},
},
});
return result.value;
}
<a name="bahasa-indonesia"></a>
Terhubung dan mengorkestrasi bersama vercel-ai-sdk-expert, senior-frontend, ui-ux-pro-max, design-system-architect, gemini-agent-booster, dan multi-agent-orchestration.
UI standar bersifat statis dan di-compile sebelumnya. Di era Gemini 4 Pro, antarmuka bersifat efemeral: dihasilkan secara real-time berdasarkan niat langsung pengguna, dan dihancurkan saat tidak lagi dibutuhkan. Skill ini mengatur sistem Generative UI menggunakan React Server Components (RSC), injeksi UI berbasis Tool, dan Vercel AI SDK, memungkinkan LLM untuk langsung men-streaming komponen fungsional interaktif (grafik, formulir, dashboard) sebagai pengganti teks biasa.
streamUI atau pemetaan panggilan alat (tool-call) ke komponen React.getWeather). Server mencegat panggilan alat ini dan men-streaming komponen React Server (<WeatherWidget />) langsung ke klien.<WeatherSkeleton />) pada milidetik pertama LLM mulai mengeluarkan token pemanggilan alat, yang kemudian diganti dengan RSC final setelah eksekusi selesai.Bahkan saat dirender secara dinamis seketika (on-the-fly), widget hasil AI WAJIB menerapkan Hierarki Visual Berdaulat:
bg-white dark:bg-neutral-900 border border-neutral-200/80 dark:border-neutral-800 rounded-xl shadow-xs).text-[11px] font-semibold uppercase tracking-wider text-neutral-500) -> Judul (text-lg font-semibold tracking-tight text-neutral-900 dark:text-neutral-50) -> Teks tubuh (text-sm text-neutral-600 dark:text-neutral-300).tabular-nums pada semua metrik angka, saldo, tarif, dan stempel waktu streaming.まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
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.
日本語の概要は準備中です。原文の説明を表示しています。
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.
日本語の概要は準備中です。原文の説明を表示しています。
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.
日本語の概要は準備中です。原文の説明を表示しています。
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.
日本語の概要は準備中です。原文の説明を表示しています。
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.
日本語の概要は準備中です。原文の説明を表示しています。
Expert guide for designing Machine-to-Machine (M2M) micro-economies, autonomous agent wallets, and swarm budget allocation / Panduan ahli merancang ekonomi mikro antar-agen (M2M), dompet agen otonom, dan alokasi anggaran swarm.
日本語の概要は準備中です。原文の説明を表示しています。