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Graphql Apollo Expert

Community
roedyrustam
graphql-apollo-expert

GraphQL APIs with Apollo Server/Client, NestJS, and query caching / API GraphQL dengan Apollo Server/Client, NestJS, dan optimasi query.

Overview

Publisherroedyrustam
Repositoryvibes-plug
Skill namegraphql-apollo-expert
Stars
117
Forks
27
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by roedyrustam on GitHub. Read the source before you install it.

Installation

Install the Graphql Apollo Expert AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/roedyrustam/vibes-plug/tree/main/skills/graphql-apollo-expert
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/roedyrustam/vibes-plug.git /tmp/vibes-plug
mkdir -p .claude/skills
cp -r /tmp/vibes-plug/skills/graphql-apollo-expert .claude/skills/graphql-apollo-expert
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Graphql Apollo Expert in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Graphql Apollo Expert on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Graphql Apollo Expert is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

GraphQL & Apollo Expert

English | Bahasa Indonesia


English

Orchestration & Integration

  • Upstream Specs & Design: api-design-expert, spec-driven-development-expert, brainstorming
  • Backend & Resolvers: js-backend-expert, database-orm-expert, sse-websocket-streaming-expert
  • Frontend Apollo Consumers: senior-frontend, vue-frontend-expert, tanstack-query-expert
  • Security & Quality: rate-limit-abuse-prevention, autonomous-red-teamer, e2e-testing-expert, anti-slop
  • Lifecycle & Governance: zero-to-prod-orchestrator, session-memory-manager

Description

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.

Trigger Conditions

Activate this skill when the user is:

  • Setting up a GraphQL server with NestJS, Express, or Apollo Server.
  • Using @apollo/client or @vue/apollo-composable on the frontend.
  • Deciding between Code-First vs. Schema-First GraphQL design.
  • Optimizing backend database queries triggered by GraphQL resolvers (N+1 problem).
  • Implementing GraphQL Subscriptions via WebSockets.

Core Concepts

1. Code-First vs Schema-First (NestJS)
  • Code-First (Recommended for TypeScript): Define resolvers and object types using TS decorators. The schema .gql file is automatically generated. Ensures a single source of truth.
  • Schema-First: Write raw .gql files and use tools to generate TypeScript interfaces.
typescript
// 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' }];
  }
}
2. The N+1 Problem & DataLoader

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.

3. Apollo Client (Frontend)

Use Apollo Client for robust caching and normalized state management on the frontend.

tsx
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>;
}

Sovereign Execution, Token Efficiency & Invariants

DimensionSovereign Mandate & Deterministic Contract
Frontier Model CascadeMedium / High (GPT-5.6 Sol Medium, Gemini 4 Argon, Claude Sonnet 5.5 High, Grok 4.7 High Fast)
Availability FallbackGemini 4 Argon/Pro -> Gemini 3.8 Flash; Claude Opus 5.5 -> Claude Opus 4.6 (Zero unhandled missing-model errors)
KV-Cache & Token ProtocolPin static instructions & schemas at prompt prefix (kv-cache-prefix-optimizer); pass surgical CONTEXT_MAP.md slices (<250 tokens/call) during Swarm Fan-Out
SaaT CLI & MCP DispatchCLI: vibes skill exec graphql-apollo-expert <audit|eval|verify|generate|blueprint> / MCP: vibes_skill_dispatch, vibes_ast_query, vibes_compile_cache, vibes_optimize_budget, vibes_verify_gate
NFR & Anti-Slop InvariantsP99 API Gateway Latency < 85ms, OpenAPI 3.1 / TypeSpec strict schema parity, RFC 9457 Problem Details error contracts, Idempotency-Key enforcement; 100% complete zero-placeholder output verified via node scripts/check-anti-slop.js --strict

Bahasa Indonesia

Integrasi Orkestrasi

  • Ideasi Hulu & Desain: api-design-expert, spec-driven-development-expert, brainstorming
  • Backend & Resolver: js-backend-expert, database-orm-expert, sse-websocket-streaming-expert
  • Konsumen Frontend Apollo: senior-frontend, vue-frontend-expert, tanstack-query-expert
  • Keamanan & Kualitas: rate-limit-abuse-prevention, autonomous-red-teamer, e2e-testing-expert, anti-slop
  • Siklus Hidup & Tata Kelola: zero-to-prod-orchestrator, session-memory-manager

Deskripsi

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.

Kondisi Pemicu

  • Mengonfigurasi server GraphQL menggunakan NestJS atau Apollo Server.
  • Mengintegrasikan Apollo Client pada frontend React atau Vue.
  • Memilih antara pendekatan Code-First vs Schema-First di TypeScript.
  • Menyelesaikan masalah query berulang N+1 pada relasi database bersarang.

Implementasi Pola Kunci

1. Pendekatan Code-First dengan NestJS GraphQL
typescript
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' }];
  }
}
2. Mengatasi Masalah N+1 Query dengan DataLoader
typescript
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)!);
});
3. Konsumsi di Sisi Klien dengan Apollo Client
tsx
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>;
}

Matriks Eksekusi Berdaulat, Efisiensi Token & Invarian

DimensiMandat Berdaulat & Kontrak Deterministik
Kaskade Model FrontierMedium / High (GPT-5.6 Sol Medium, Gemini 4 Argon, Claude Sonnet 5.5 High, Grok 4.7 High Fast)
Invarian Fallback KetersediaanGemini 4 Argon/Pro -> Gemini 3.8 Flash; Claude Opus 5.5 -> Claude Opus 4.6 (Bebas gagal saat model belum tersedia/kuota penuh)
Protokol Hemat Token & KV-CacheKunci instruksi & skema statis di prefix awal (kv-cache-prefix-optimizer); kirim potongan CONTEXT_MAP.md (<250 token/panggilan) saat Fan-Out
Eksekusi SaaT CLI & MCPCLI: vibes skill exec graphql-apollo-expert <audit|eval|verify|generate|blueprint> / MCP: vibes_skill_dispatch, vibes_ast_query, vibes_compile_cache, vibes_optimize_budget, vibes_verify_gate
Invarian NFR & Anti-SlopLatensi P99 API < 85ms, paritas skema ketat OpenAPI 3.1 / TypeSpec, kontrak error RFC 9457 Problem Details, penegakan Idempotency-Key; kode 100% tuntas tanpa placeholder diverifikasi melalui node scripts/check-anti-slop.js --strict

Frequently asked questions

What does the Graphql Apollo Expert AI skill do?

GraphQL APIs with Apollo Server/Client, NestJS, and query caching / API GraphQL dengan Apollo Server/Client, NestJS, dan optimasi query.

Why use Graphql Apollo Expert on TypingMind?

Because you install it once and use it with any model. Graphql Apollo Expert is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Graphql Apollo Expert in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/roedyrustam/vibes-plug/tree/main/skills/graphql-apollo-expert. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Graphql Apollo Expert?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Graphql Apollo Expert?

As many as you like. As long as a model supports skills, you can use Graphql Apollo Expert with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Graphql Apollo Expert AI skill free?

Yes. It is published on GitHub by roedyrustam under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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