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.
中文简介正在准备中。当前显示原文说明。
Expert guide for designing and consuming GraphQL APIs. Covers Apollo Server/Client, NestJS GraphQL (Code-First & Schema-First), TypeGraphQL, caching, and N+1 query optimization.
中文简介正在准备中。当前显示原文说明。
查看安装方法安装前可以查看交给 AI 代理的指令内容。
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Connects and orchestrates with relevant domain skills like brainstorming, zero-to-prod-orchestrator, and session-memory-manager to ensure cohesive execution.
Production-grade guidance for building and consuming GraphQL APIs. Focuses on the Apollo ecosystem (Apollo Server, Apollo Client, Federation), NestJS GraphQL integration, and solving common performance pitfalls like the N+1 query problem using DataLoaders.
Activate this skill when the user is:
@apollo/client or @vue/apollo-composable on the frontend..gql file is automatically generated. Ensures a single source of truth..gql files and use tools to generate TypeScript interfaces.// NestJS Code-First Example
import { ObjectType, Field, Int } from '@nestjs/graphql';
@ObjectType()
export class User {
@Field(() => Int)
id: number;
@Field()
email: string;
}
import { Resolver, Query } from '@nestjs/graphql';
@Resolver(() => User)
export class UserResolver {
@Query(() => [User])
async users(): Promise<User[]> {
return [{ id: 1, email: 'user@example.com' }];
}
}
GraphQL's resolver architecture easily causes the N+1 query problem (e.g., querying authors and their posts results in 1 query for authors, and N queries for each author's posts).
Solution: Always use DataLoader to batch and cache database requests within a single GraphQL execution tick.
Use Apollo Client for robust caching and normalized state management on the frontend.
import { useQuery, gql } from '@apollo/client';
const GET_USERS = gql`
query GetUsers {
users {
id
email
}
}
`;
function UserList() {
const { loading, error, data } = useQuery(GET_USERS);
if (loading) return <p>Loading...</p>;
return <div>{data.users[0].email}</div>;
}
This skill works best when combined with:
js-backend-expert — For setting up the underlying Node.js/NestJS server architecture.database-orm-expert — For connecting Prisma/Drizzle ORM directly to GraphQL resolvers and DataLoaders.senior-frontend / vue-frontend-expert — For integrating Apollo Client into React or Vue applications.brainstorming — Add to "API Design & Contracts".zero-to-prod-orchestrator — Phase 4 (Backend APIs).<a name="bahasa-indonesia"></a>
Terhubung dan mengorkestrasi skill domain yang relevan seperti brainstorming, zero-to-prod-orchestrator, dan session-memory-manager untuk memastikan eksekusi yang kohesif.
js-backend-expert — Setup arsitektur server Node.js/NestJS.database-orm-expert — Menghubungkan Prisma/Drizzle ORM ke resolver GraphQL dan DataLoader.senior-frontend / vue-frontend-expert — Integrasi Apollo Client ke aplikasi frontend.Panduan produksi untuk membangun dan mengonsumsi API GraphQL. Mencakup ekosistem Apollo (Apollo Server, Apollo Client, Federation), integrasi NestJS GraphQL, dan pemecahan masalah bottleneck query N+1 menggunakan DataLoader.
import { ObjectType, Field, Int, Resolver, Query } from '@nestjs/graphql';
@ObjectType()
export class Pengguna {
@Field(() => Int)
id: number;
@Field()
email: string;
}
@Resolver(() => Pengguna)
export class PenggunaResolver {
@Query(() => [Pengguna])
async daftarPengguna(): Promise<Pengguna[]> {
return [{ id: 1, email: 'pengguna@example.com' }];
}
}
import DataLoader from 'dataloader';
// Kumpulkan ID dan lakukan satu query batch (IN clause)
export const pemuatDataPenulis = new DataLoader<string, Penulis>(async (daftarId) => {
const baris = await db.penulis.findMany({
where: { id: { in: [...daftarId] } },
});
const mapPenulis = new Map(baris.map((p) => [p.id, p]));
return daftarId.map((id) => mapPenulis.get(id)!);
});
import { useQuery, gql } from '@apollo/client';
const QUERY_PENGGUNA = gql`
query AmbilDaftarPengguna {
daftarPengguna {
id
email
}
}
`;
export function KomponenDaftarPengguna() {
const { loading, error, data } = useQuery(QUERY_PENGGUNA);
if (loading) return <p>Memuat data...</p>;
if (error) return <p>Terjadi galat: {error.message}</p>;
return <div>Email: {data.daftarPengguna[0]?.email}</div>;
}
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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.
中文简介正在准备中。当前显示原文说明。
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.
中文简介正在准备中。当前显示原文说明。
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.
中文简介正在准备中。当前显示原文说明。
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.
中文简介正在准备中。当前显示原文说明。
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.
中文简介正在准备中。当前显示原文说明。
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.
中文简介正在准备中。当前显示原文说明。