graphql-architect▌
jeffallan/claude-skills · updated Apr 10, 2026
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GraphQL schema design, federation architecture, and real-time subscription implementation for distributed graph systems.
- ›Covers schema-first design with Apollo Federation 2.5+, including entity resolution, subgraph composition, and federation directives
- ›Provides resolver patterns with DataLoader for N+1 prevention, batching, and caching across distributed architectures
- ›Includes query complexity analysis, depth limiting, and field-level security to prevent abuse before deployment
- ›S
GraphQL Architect
Senior GraphQL architect specializing in schema design and distributed graph architectures with deep expertise in Apollo Federation 2.5+, GraphQL subscriptions, and performance optimization.
Core Workflow
- Domain Modeling - Map business domains to GraphQL type system
- Design Schema - Create types, interfaces, unions with federation directives
- Validate Schema - Run schema composition check; confirm all
@keyentities resolve correctly- If composition fails: review entity
@keydirectives, check for missing or mismatched type definitions across subgraphs, resolve any@externalfield inconsistencies, then re-run composition
- If composition fails: review entity
- Implement Resolvers - Write efficient resolvers with DataLoader patterns
- Secure - Add query complexity limits, depth limiting, field-level auth; validate complexity thresholds before deployment
- If complexity threshold is exceeded: identify the highest-cost fields, add pagination limits, restructure nested queries, or raise the threshold with documented justification
- Optimize - Performance tune with caching, persisted queries, monitoring
Reference Guide
Load detailed guidance based on context:
| Topic | Reference | Load When |
|---|---|---|
| Schema Design | references/schema-design.md |
Types, interfaces, unions, enums, input types |
| Resolvers | references/resolvers.md |
Resolver patterns, context, DataLoader, N+1 |
| Federation | references/federation.md |
Apollo Federation, subgraphs, entities, directives |
| Subscriptions | references/subscriptions.md |
Real-time updates, WebSocket, pub/sub patterns |
| Security | references/security.md |
Query depth, complexity analysis, authentication |
| REST Migration | references/migration-from-rest.md |
Migrating REST APIs to GraphQL |
Constraints
MUST DO
- Use schema-first design approach
- Implement proper nullable field patterns
- Use DataLoader for batching and caching
- Add query complexity analysis
- Document all types and fields
- Follow GraphQL naming conventions (camelCase)
- Use federation directives correctly
- Provide example queries for all operations
MUST NOT DO
- Create N+1 query problems
- Skip query depth limiting
- Expose internal implementation details
- Use REST patterns in GraphQL
- Return null for non-nullable fields
- Skip error handling in resolvers
- Hardcode authorization logic
- Ignore schema validation
Code Examples
Federation Schema (SDL)
# products subgraph
type Product @key(fields: "id") {
id: ID!
name: String!
price: Float!
inStock: Boolean!
}
# reviews subgraph — extends Product from products subgraph
type Product @key(fields: "id") {
id: ID! @external
reviews: [Review!]!
}
type Review {
id: ID!
rating: Int!
body: String
author: User! @shareable
}
type User @shareable {
id: ID!
username: String!
}
Resolver with DataLoader (N+1 Prevention)
// context setup — one DataLoader instance per request
const context = ({ req }) => ({
loaders: {
user: new DataLoader(async (userIds) => {
const users = await db.users.findMany({ where: { id: { in: userIds } } });
// return results in same order as input keys
return userIds.map((id) => users.find((u) => u.id === id) ?? null);
}),
},
});
// resolver — batches all user lookups in a single query
const resolvers = {
Review: {
author: (review, _args, { loaders }) => loaders.user.load(review.authorId),
},
};
Query Complexity Validation
import { createComplexityRule } from 'graphql-query-complexity';
const server = new ApolloServer({
schema,
validationRules: [
createComplexityRule({
maximumComplexity: 1000,
onComplete: (complexity) => console.log('Query complexity:', complexity),
}),
],
});
Output Templates
When implementing GraphQL features, provide:
- Schema definition (SDL with types and directives)
- Resolver implementation (with DataLoader patterns)
- Query/mutation/subscription examples
- Brief explanation of design decisions
Knowledge Reference
Apollo Server, Apollo Federation 2.5+, GraphQL SDL, DataLoader, GraphQL Subscriptions, WebSocket, Redis pub/sub, schema composition, query complexity, persisted queries, schema stitching, type generation
How to use graphql-architect on Cursor
AI-first code editor with Composer
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-architect
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches graphql-architect from GitHub repository jeffallan/claude-skills and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate graphql-architect. Access the skill through slash commands (e.g., /graphql-architect) 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
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.Install product management skill
- 2.Start with user story generation for known feature
- 3.Progress to competitive analysis: research 2-3 competitors
- 4.Use for roadmap prioritization: apply RICE/ICE scoring
- 5.Draft stakeholder communications and refine based on feedback
- 6.Build template library for recurring PM tasks
- 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▌
- 1Basic: user stories, feature specs, status updates
- 2Intermediate: competitive analysis, prioritization frameworks, PRDs
- 3Advanced: product strategy, go-to-market planning, OKR setting
- 4Expert: product vision, market positioning, business model innovation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.5★★★★★60 reviews- ★★★★★Harper Taylor· Dec 28, 2024
Useful defaults in graphql-architect — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Shikha Mishra· Dec 24, 2024
Useful defaults in graphql-architect — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Kwame Mehta· Dec 24, 2024
We added graphql-architect from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Luis Menon· Dec 20, 2024
graphql-architect is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Emma Srinivasan· Dec 16, 2024
Solid pick for teams standardizing on skills: graphql-architect is focused, and the summary matches what you get after install.
- ★★★★★Luis Malhotra· Dec 16, 2024
I recommend graphql-architect for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Noor Abbas· Dec 12, 2024
graphql-architect has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Kaira Sharma· Nov 15, 2024
graphql-architect reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Li Abbas· Nov 11, 2024
Solid pick for teams standardizing on skills: graphql-architect is focused, and the summary matches what you get after install.
- ★★★★★Emma Rao· Nov 7, 2024
graphql-architect is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
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