graphql-expert

graphql-expert is a skill for Claude Code from personamanagmentlayer/pcl. It costs 67 tokens per session (1,438 once invoked), scanned A, original, Apache-2.0.

A reference guide for GraphQL, an API approach where clients ask for the exact data they need. It covers the schema that defines available data, resolver functions that fetch it, and real-time subscriptions.

In plain words
What is it for?
Use it to design schemas, queries, mutations, pagination, filtering, validation, resolvers, subscriptions over WebSockets, caching, batching, and query-cost limits.
Why use it?
It helps prevent unclear API contracts, unnecessary data transfer, and common performance problems such as repeated database queries.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter.

Good fit Use it to design schemas, queries, mutations, pagination, filtering, validation, resolvers, subscriptions over WebSockets, caching, batching, and query-cost limits.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/personamanagmentlayer/pcl/graphql-expert
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add personamanagmentlayer/pcl --skill graphql-expert
Clone the repo
git clone --depth 1 https://github.com/personamanagmentlayer/pcl

Made for: Claude Code.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for graphql-expert

README.md
[![agentmods](https://agentmods.dev/badge/skills/personamanagmentlayer/pcl/graphql-expert/github.svg)](https://agentmods.dev/skills/personamanagmentlayer/pcl/graphql-expert)
Your own site
<a href="https://agentmods.dev/skills/personamanagmentlayer/pcl/graphql-expert"><img src="https://agentmods.dev/badge/skills/personamanagmentlayer/pcl/graphql-expert/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for graphql-expert

Your own site · 80×15
<a href="https://agentmods.dev/skills/personamanagmentlayer/pcl/graphql-expert"><img src="https://agentmods.dev/badge/skills/personamanagmentlayer/pcl/graphql-expert.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 67 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,438 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00067 $0.01438
Opus 5 $0.00034 $0.00719
Sonnet 5 $0.00013 $0.00288
Haiku 4.5 $0.00007 $0.00144

Measured 3d ago against content hash 1648e72e4a88, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

graphql-expert scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

stdlib/api/graphql-expert/SKILL.md · 226 lines

How it starts

The opening of the file, as written. The whole thing — 226 lines — stays where its author put it; the contents beside it link to each section on GitHub.

GraphQL Expert

Expert guidance for GraphQL API development, schema design, resolvers, subscriptions, and best practices for building type-safe, efficient APIs.

Core Concepts

Schema Design

  • Type system and schema definition language (SDL)
  • Object types, interfaces, unions, and enums
  • Input types and custom scalars
  • Schema stitching and federation
  • Modular schema organization

Resolvers

  • Resolver functions and data sources
  • Context and info arguments
  • Field-level resolvers
  • Resolver chains and data loaders
  • Error handling in resolvers

Queries and Mutations

  • Query design and naming conventions
  • Mutation patterns and best practices
  • Input validation and sanitization
  • Pagination strategies (cursor-based, offset)
  • Filtering and sorting

Subscriptions

  • Real-time updates with WebSocket
  • Subscription resolvers
  • PubSub patterns
  • Subscription filtering
  • Connection management

Performance

  • N+1 query problem and DataLoader
  • Query complexity analysis
  • Depth limiting and query cost
  • Caching strategies (field-level, full response)
  • Batching and deduplication

GraphQL Federation

Federated Schema

// Users service
import { buildSubgraphSchema } from '@apollo/subgraph';

const typeDefs = gql`
  extend schema @link(url: "https://specs.apollo.dev/federation/v2.3")

  type User @key(fields: "id") {
    id: ID!
    email: String!
    name: String!
  }

  type Query {
    user(id: ID!): User
    users: [User!]!
  }
`;

const resolvers = {
  User: {
    __resolveReference: async (reference, { dataSources }) => {
      return dataSources.userAPI.getUserById(reference.id);
    },
  },
  Query: {
    user: (_, { id }, { dataSources }) => dataSources.userAPI.getUserById(id),
    users: (_, __, { dataSources }) => dataSources.userAPI.getUsers(),
  },
};

// Posts service
const typeDefs = gql`
  extend schema @link(url: "https://specs.apollo.dev/federation/v2.3")

  type Post @key(fields: "id") {
    id: ID!
    title: String!
    content: String!
    author: User!
  }

  extend type User @key(fields: "id") {
    id: ID! @external
    posts: [Post!]!
  }

  type Query {
    post(id: ID!): Post
    posts: [Post!]!
  }
`;

const resolvers = {
  Post: {
    author: (post) => ({ __typename: 'User', id: post.authorId }),
  },
  User: {
    posts: (user, _, { dataSources }) =>
      dataSources.postAPI.getPostsByAuthorId(user.id),
  },
};

// Gateway
import { ApolloGateway, IntrospectAndCompose } from '@apollo/gateway';

const gateway = new ApolloGateway({
  supergraphSdl: new IntrospectAndCompose({
    subgraphs: [
      { name: 'users', url: 'http://localhost:4001/graphql' },
      { name: 'posts', url: 'http://localhost:4002/graphql' },
    ],
  }),
});

const server = new ApolloServer({ gateway });

Read the full file on GitHub · 226 lines

Files

What ships with it

3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 3d ago Changed · -697 lines · +48 tokens per session 1648e72e4a88
  2. 9d ago First seen · 923 lines · 19 tokens per session scan A 52df8be99725

Subscribe to this mod's changes

graphql-expert is a skill published in the GitHub repository personamanagmentlayer/pcl (40 stars, last pushed yesterday), licensed Apache-2.0. It adds 67 tokens to every session and 1,438 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Related

Other skills, from other repositories

graphql-docs

Use this skill whenever the user asks about GraphQL, query languages for APIs, schema design, types, resolvers, mutations, subscriptions, introspection, pagination, federation, or API best practices. Covers the full GraphQL specification including schemas and types, queries, mutations, subscriptions, validation…

pledgeandgrow/pledge-skills · 119 tokens

graphql-api-development

AI-powered GraphQL API design, implementation, and optimization. Covers schema-first design, resolver architecture, query optimization with DataLoader for N+1 prevention, mutation patterns with idempotency, real-time subscriptions, Apollo Federation for distributed graphs, security hardening (depth limiting, rate…

JPeetz/agent-skills · 183 tokens

graphql-api-development

Comprehensive guide for building GraphQL APIs including schema design, queries, mutations, subscriptions, resolvers, type system, error handling, authentication, authorization, caching strategies, and production best practices.

manutej/luxor-claude-marketplace · 42 tokens

graphql-apis

Operational skill for GraphQL APIs: schema-first design, resolvers, N+1 prevention, authz in the graph, and client query discipline.

alivirgo/Major-AI-Skills · 34 tokens

GraphQL Testing

Comprehensive GraphQL API testing including query/mutation testing, schema validation, resolver testing, subscription testing, and N+1 query detection.

PramodDutta/qaskills · 32 tokens

clawrouter

Hosted-gateway LLM router — save 84% on inference costs. A local proxy that forwards each request to the blockrun.ai gateway, which routes to the cheapest capable model across 76 models from OpenAI, Anthropic, Google, DeepSeek, xAI, Z.AI, and more. 7 free open-weight models included. Also exposes realtime market data…

BlockRunAI/ClawRouter · 222 tokens