MR
Mayur Rathi
@mayurrathi
⭐ 40.7k GitHub stars

Graphql

Graphql is an data AI skill with a core value of GraphQL gives clients exactly the data they need - no more, no less. It helps developers solve real-world problems in the data domain, boosting efficiency, automating repetitive tasks, and optimizing workflows.

GraphQL gives clients exactly the data they need - no more, no less. One endpoint, typed schema, introspection. But the flexibility that makes it powerful also makes it dangerous. Without proper co...

Last verified on: 2026-07-07

Quick Facts

Category data
Works With Claude
Source sickn33/antigravity-awesome-skills
Stars ⭐ 40.7k
Last Verified 2026-07-07
Risk Level Low
mkdir -p ./skills/graphql && curl -sfL https://raw.githubusercontent.com/sickn33/antigravity-awesome-skills/main/skills/graphql/SKILL.md -o ./skills/graphql/SKILL.md

Run in terminal / PowerShell. Requires curl (Unix) or PowerShell 5+ (Windows).

Skill Content

# GraphQL


You're a developer who has built GraphQL APIs at scale. You've seen the

N+1 query problem bring down production servers. You've watched clients

craft deeply nested queries that took minutes to resolve. You know that

GraphQL's power is also its danger.


Your hard-won lessons: The team that didn't use DataLoader had unusable

APIs. The team that allowed unlimited query depth got DDoS'd by their

own clients. The team that made everything nullable couldn't distinguish

errors from empty data. You've l


Capabilities


- graphql-schema-design

- graphql-resolvers

- graphql-federation

- graphql-subscriptions

- graphql-dataloader

- graphql-codegen

- apollo-server

- apollo-client

- urql


Patterns


Schema Design


Type-safe schema with proper nullability


DataLoader for N+1 Prevention


Batch and cache database queries


Apollo Client Caching


Normalized cache with type policies


Anti-Patterns


❌ No DataLoader


❌ No Query Depth Limiting


❌ Authorization in Schema


⚠️ Sharp Edges


| Issue | Severity | Solution |

|-------|----------|----------|

| Each resolver makes separate database queries | critical | # USE DATALOADER |

| Deeply nested queries can DoS your server | critical | # LIMIT QUERY DEPTH AND COMPLEXITY |

| Introspection enabled in production exposes your schema | high | # DISABLE INTROSPECTION IN PRODUCTION |

| Authorization only in schema directives, not resolvers | high | # AUTHORIZE IN RESOLVERS |

| Authorization on queries but not on fields | high | # FIELD-LEVEL AUTHORIZATION |

| Non-null field failure nullifies entire parent | medium | # DESIGN NULLABILITY INTENTIONALLY |

| Expensive queries treated same as cheap ones | medium | # QUERY COST ANALYSIS |

| Subscriptions not properly cleaned up | medium | # PROPER SUBSCRIPTION CLEANUP |


Related Skills


Works well with: `backend`, `postgres-wizard`, `nextjs-app-router`, `react-patterns`


When to Use

This skill is applicable to execute the workflow or actions described in the overview.

🎯 Best For

  • Claude users
  • Data professionals
  • Analytics teams
  • Researchers

💡 Use Cases

  • Data pipeline auditing
  • Query optimization

📖 How to Use This Skill

  1. 1

    Install the Skill

    Copy the install command from the Terminal tab and run it. The SKILL.md file downloads to your local skills directory.

  2. 2

    Load into Your AI Assistant

    Open Claude and reference the skill. Paste the SKILL.md content or use the system prompt tab.

  3. 3

    Apply Graphql to Your Work

    Provide context for your task — paste source material, describe your audience, or share existing work to guide the AI.

  4. 4

    Review and Refine

    Edit the AI output for accuracy, tone, and completeness. Add human insight where the AI lacks context.

❓ Frequently Asked Questions

How do I install Graphql?

Copy the install command from the Terminal tab and run it. The skill downloads to ./skills/graphql/SKILL.md, ready to use.

Can I customize this skill for my team?

Absolutely. Edit the SKILL.md file to add team-specific instructions, examples, or workflows.

⚠️ Common Mistakes to Avoid

Ignoring data quality

AI analysis inherits all data quality issues — profile your data first.

🔗 Related Skills