graphql

sickn33/antigravity-awesome-skills · updated Apr 8, 2026

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$npx skills add https://github.com/sickn33/antigravity-awesome-skills --skill graphql
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summary

GraphQL schema design, resolver patterns, and production safety best practices.

  • Covers nine core capabilities including schema design, resolvers, federation, subscriptions, DataLoader, code generation, and Apollo tooling for both server and client
  • Emphasizes critical production hazards: N+1 query problems, unlimited query depth leading to DoS, introspection exposure, and improper authorization scoping
  • Provides patterns for type-safe schemas with intentional nullability, batch query o
skill.md

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.

how to use graphql

How to use graphql on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add graphql
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/sickn33/antigravity-awesome-skills --skill graphql

The skills CLI fetches graphql from GitHub repository sickn33/antigravity-awesome-skills and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/graphql

Reload or restart Cursor to activate graphql. Access the skill through slash commands (e.g., /graphql) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

Submit your Claude Code skill and start earning

GET_STARTED →

Use Cases

User Story & Requirements Generation

Create detailed user stories, acceptance criteria, and feature specs

Example

Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios

Reduce spec writing time by 50%, ensure comprehensive coverage

Competitive Analysis

Research competitors, compare features, identify gaps

Example

Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities

Complete competitive research in 2 hours instead of 2 days

Roadmap Prioritization

Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs

Example

Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale

Make data-driven prioritization decisions faster

Stakeholder Communication

Draft PRDs, status updates, and stakeholder presentations

Example

Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement

Save 3-5 hours/week on communication overhead

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client
  • Access to product documentation and roadmap tools (Jira, Notion, etc.)
  • Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
  • Stakeholder contact information and communication channels

Time Estimate

30-60 minutes to see productivity improvements

Installation Steps

  1. 1.Install product management skill
  2. 2.Start with user story generation for known feature
  3. 3.Progress to competitive analysis: research 2-3 competitors
  4. 4.Use for roadmap prioritization: apply RICE/ICE scoring
  5. 5.Draft stakeholder communications and refine based on feedback
  6. 6.Build template library for recurring PM tasks
  7. 7.Share effective prompts with product team

Common Pitfalls

  • Not validating competitive research—verify facts before sharing
  • Accepting user stories without involving engineering team
  • Over-relying on frameworks without qualitative judgment
  • Not customizing outputs to company culture and communication style
  • Skipping stakeholder validation of generated requirements

Best Practices

✓ Do

  • +Validate research and competitive analysis with real data
  • +Collaborate with engineering when generating technical requirements
  • +Customize frameworks and templates to your company context
  • +Use skill for first drafts, refine with stakeholder input
  • +Document successful prompt patterns for PM tasks
  • +Combine AI efficiency with human judgment and intuition

✗ Don't

  • Don't publish competitive analysis without fact-checking
  • Don't finalize user stories without engineering review
  • Don't make prioritization decisions solely on AI scoring
  • Don't skip customer validation of generated requirements
  • Don't ignore company-specific context and culture

💡 Pro Tips

  • Provide context: company goals, constraints, customer feedback
  • Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
  • Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
  • Use skill for 70% generation + 30% customization to company needs

When to Use This

✓ Use When

Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.

✗ Avoid When

Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.

Learning Path

  1. 1Basic: user stories, feature specs, status updates
  2. 2Intermediate: competitive analysis, prioritization frameworks, PRDs
  3. 3Advanced: product strategy, go-to-market planning, OKR setting
  4. 4Expert: product vision, market positioning, business model innovation

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.628 reviews
  • Kiara Gill· Dec 24, 2024

    Registry listing for graphql matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Shikha Mishra· Dec 16, 2024

    We added graphql from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Jin Johnson· Dec 4, 2024

    Keeps context tight: graphql is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Kaira Lopez· Nov 15, 2024

    graphql reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Rahul Santra· Nov 7, 2024

    Useful defaults in graphql — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Pratham Ware· Oct 26, 2024

    Registry listing for graphql matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Carlos Shah· Oct 6, 2024

    We added graphql from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Sofia Sharma· Sep 21, 2024

    graphql has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Aisha Kim· Aug 12, 2024

    graphql fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Yash Thakker· Jul 23, 2024

    Keeps context tight: graphql is the kind of skill you can hand to a new teammate without a long onboarding doc.

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