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Graphql Architect

Listed
sickn33·vlatest·backend·MIT

Designs efficient, scalable GraphQL APIs from specifications, optimizing performance and data fetching for complex backends.

Repository

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 sickn33/agentic-awesome-skills --skill graphql-architect -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

sickn33

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Install target

Live repository

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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 failed 1 of 6 checks. A failure is not proof of bad intent; it means something in the code needs a human to look at it before you run it.

  • Declares what it does: failed

    No SKILL.md was found in the skill's directory.

    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.

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  • No credential access: passed

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  • No pipe-to-shell installers: passed

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  • Pinned to a commit: passed

    Scanned sickn33/antigravity-awesome-skills at 5a4cdd9df8.

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Commit
5a4cdd9df8
Manifest
skills/graphql-architect/SKILL.md
Scanned
0 files
Copies in repo
3 — all of them scanned
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About this skill

The graphql-architect skill enables AI agents to design, structure, and optimize GraphQL schemas for complex backend systems. It assists in defining resolvers, managing data types, and ensuring efficient query resolution patterns across distributed services.

When to use it

  • Designing a new API layer for a microservices architecture that requires flexible querying.
  • Refactoring an existing RESTful service to adopt GraphQL for reduced over-fetching of data.
  • Defining strict type safety and validation rules for user-generated content in a real-time application.
  • Optimizing resolver logic to prevent N+1 query problems in high-traffic environments.

Key capabilities

  • Automated schema generation based on domain entity relationships.
  • Resolver function scaffolding with proper error handling patterns.
  • Type definition creation adhering to GraphQL best practices.
  • Query complexity analysis and optimization suggestions.

Example prompts

  • "Create a GraphQL schema for an e-commerce platform including Product, Order, and User types with nested relationships."
  • "Generate resolver functions for fetching user orders that include pagination logic and error handling."
  • "Refactor this REST API endpoint into a GraphQL query structure to support filtering by date range."

Tips & gotchas

Ensure your AI agent has access to the specific business domain context, as generic schemas may lack necessary nuance. Always validate generated resolvers against actual database constraints before deployment to avoid runtime failures.