graphql
About
This Claude Skill provides expertise in designing and implementing GraphQL APIs, including schema design, type systems, and resolver logic. It helps implement Relay-style pagination, solve N+1 problems using DataLoader patterns, and handle efficient error handling. Use this skill when working on GraphQL schemas, resolver implementations, mutations, subscriptions, and performance optimization.
Documentation
GraphQL API Standards
네이밍 규칙
필드 네이밍
- boolean:
is/has/can접두사 강제 - 날짜:
~At접미사 강제 - 같은 개념은 프로젝트 전체 동일 용어 (create vs add 중 하나로 통일)
날짜 형식
- ISO 8601 UTC
- DateTime 타입 사용
페이지네이션
Relay Connection Specification
type UserConnection {
edges: [UserEdge!]!
pageInfo: PageInfo!
}
type UserEdge {
node: User!
cursor: String!
}
type PageInfo {
hasNextPage: Boolean!
endCursor: String
}
- 파라미터:
first,after
정렬
orderBy: [{ field: "createdAt", order: DESC }]
타입 네이밍
- Input:
{동사}{타입}Input - Connection:
{타입}Connection - Edge:
{타입}Edge
Input
- 생성/수정 분리 (생성은 필수, 수정은 선택)
- 중첩 피하기 - ID만
에러
extensions (기본)
errors[].extensions에code,field
Union (타입 안정성)
User | ValidationError
N+1
- DataLoader 강제
문서화
"""설명"""필수- Input 제약사항 명시
Deprecation
@deprecated(reason: "...")- 타입 삭제 금지
Quick Install
/plugin add https://github.com/KubrickCode/ai-config-toolkit/tree/main/graphqlCopy and paste this command in Claude Code to install this skill
GitHub 仓库
Related Skills
evaluating-llms-harness
TestingThis Claude Skill runs the lm-evaluation-harness to benchmark LLMs across 60+ standardized academic tasks like MMLU and GSM8K. It's designed for developers to compare model quality, track training progress, or report academic results. The tool supports various backends including HuggingFace and vLLM models.
langchain
MetaLangChain is a framework for building LLM applications using agents, chains, and RAG pipelines. It supports multiple LLM providers, offers 500+ integrations, and includes features like tool calling and memory management. Use it for rapid prototyping and deploying production systems like chatbots, autonomous agents, and question-answering services.
csv-data-summarizer
MetaThis skill automatically analyzes CSV files to generate comprehensive statistical summaries and visualizations using Python's pandas and matplotlib/seaborn. It should be triggered whenever a user uploads or references CSV data without prompting for analysis preferences. The tool provides immediate insights into data structure, quality, and patterns through automated analysis and visualization.
Excel Analysis
MetaThis skill enables developers to analyze Excel files and perform data operations using pandas. It can read spreadsheets, create pivot tables, generate charts, and conduct data analysis on .xlsx files and tabular data. Use it when working with Excel files, spreadsheets, or any structured tabular data within Claude Code.
