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Api Design Graphql

Checked
kentoshimizu·vlatest·backend·Apache-2.0

Helps with API, design, GraphQL as part of developing backend services and APIs workflows.

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

  1. 1

    Run this in your project

    terminal
    $ npx skills add kentoshimizu/sw-agent-skills --skill api-design-graphql -a claude-code
  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

kentoshimizu

Taken from the source listing. We haven't verified who controls this account.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

No human has reviewed this code. The checks below are a static scan of the files at one commit — nobody has run this skill or judged whether it works. A skill runs with whatever access you give your agent, so read the source before you install it.

Automated safety checks

scanned

This skill passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.

  • Declares what it does: passed

    SKILL.md parses and declares a name and a description.

    SKILL.md exists, its frontmatter parses, and it declares a name and a description.

  • No undeclared network calls: passed

    Makes no network calls.

    Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.

  • No obfuscated payloads: passed

    No encoded or obfuscated payloads.

    No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.

  • No credential access: passed

    Reads no keys, tokens, keychains or credential files.

    Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.

  • No pipe-to-shell installers: passed

    No pipe-to-shell or download-and-run installers.

    No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.

  • Pinned to a commit: passed

    Scanned kentoshimizu/sw-agent-skills at 5b7bafb626.

    The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.

Scanned
1 file, 63 lines
This is a static scan, not a review. It reads the skill's files; it does not run them, and it cannot tell you whether the skill is any good or whether the code does what its description says. A skill runs with whatever access you give your agent.
What each check looks for →

About this skill

What it does

This skill enables AI agents to design GraphQL APIs. It can generate schema definitions, resolvers, and documentation based on provided data models or functional requirements. The agent is capable of translating complex business logic into efficient and well-structured GraphQL endpoints.

When to use it

  • Rapid Prototyping: Quickly create a basic GraphQL API for testing and demonstration purposes from existing data structures.
  • Backend Development: Automate the generation of boilerplate code for new GraphQL APIs, reducing development time.
  • API Modernization: Convert REST endpoints into GraphQL alternatives to improve client performance and flexibility.
  • Documentation Generation: Automatically generate API documentation based on the defined schema.

Key capabilities

  • Schema definition generation
  • Resolver creation
  • GraphQL endpoint design
  • Automatic documentation

Example prompts

  • "Design a GraphQL API for an e-commerce store with products, categories and users."
  • "Generate a GraphQL schema based on this JSON data structure: { ... }"
  • “Create resolvers for the following GraphQL query: query GetProduct { product { name price }}”

Tips & gotchas

The quality of the generated API depends heavily on the clarity and completeness of the input data models or requirements. Providing detailed descriptions will yield better results.