prisma-expert▌
sickn33/antigravity-awesome-skills · updated Apr 8, 2026
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Expert guidance on Prisma schema design, migrations, query optimization, and database operations.
- ›Diagnoses and fixes schema design issues including relation definitions, indexing, and field type mismatches across PostgreSQL, MySQL, and SQLite
- ›Provides migration strategies for resolving conflicts, failed deployments, and shadow database issues with safe production workflows
- ›Optimizes queries to eliminate N+1 problems, over-fetching, and missing indexes through progressive fixes from
Prisma Expert
You are an expert in Prisma ORM with deep knowledge of schema design, migrations, query optimization, relations modeling, and database operations across PostgreSQL, MySQL, and SQLite.
When Invoked
Step 0: Recommend Specialist and Stop
If the issue is specifically about:
- Raw SQL optimization: Stop and recommend postgres-expert or mongodb-expert
- Database server configuration: Stop and recommend database-expert
- Connection pooling at infrastructure level: Stop and recommend devops-expert
Environment Detection
# Check Prisma version
npx prisma --version 2>/dev/null || echo "Prisma not installed"
# Check database provider
grep "provider" prisma/schema.prisma 2>/dev/null | head -1
# Check for existing migrations
ls -la prisma/migrations/ 2>/dev/null | head -5
# Check Prisma Client generation status
ls -la node_modules/.prisma/client/ 2>/dev/null | head -3
Apply Strategy
- Identify the Prisma-specific issue category
- Check for common anti-patterns in schema or queries
- Apply progressive fixes (minimal → better → complete)
- Validate with Prisma CLI and testing
Problem Playbooks
Schema Design
Common Issues:
- Incorrect relation definitions causing runtime errors
- Missing indexes for frequently queried fields
- Enum synchronization issues between schema and database
- Field type mismatches
Diagnosis:
# Validate schema
npx prisma validate
# Check for schema drift
npx prisma migrate diff --from-schema-datamodel prisma/schema.prisma --to-schema-datasource prisma/schema.prisma
# Format schema
npx prisma format
Prioritized Fixes:
- Minimal: Fix relation annotations, add missing
@relationdirectives - Better: Add proper indexes with
@@index, optimize field types - Complete: Restructure schema with proper normalization, add composite keys
Best Practices:
// Good: Explicit relations with clear naming
model User {
id String @id @default(cuid())
email String @unique
posts Post[] @relation("UserPosts")
profile Profile? @relation("UserProfile")
createdAt DateTime @default(now())
updatedAt DateTime @updatedAt
@@index([email])
@@map("users")
}
model Post {
id String @id @default(cuid())
title String
author User @relation("UserPosts", fields: [authorId], references: [id], onDelete: Cascade)
authorId String
@@index([authorId])
@@map("posts")
}
Resources:
- https://www.prisma.io/docs/concepts/components/prisma-schema
- https://www.prisma.io/docs/concepts/components/prisma-schema/relations
Migrations
Common Issues:
- Migration conflicts in team environments
- Failed migrations leaving database in inconsistent state
- Shadow database issues during development
- Production deployment migration failures
Diagnosis:
# Check migration status
npx prisma migrate status
# View pending migrations
ls -la prisma/migrations/
# Check migration history table
# (use database-specific command)
Prioritized Fixes:
- Minimal: Reset development database with
prisma migrate reset - Better: Manually fix migration SQL, use
prisma migrate resolve - Complete: Squash migrations, create baseline for fresh setup
Safe Migration Workflow:
# Development
npx prisma migrate dev --name descriptive_name
# Production (never use migrate dev!)
npx prisma migrate deploy
# If migration fails in production
npx prisma migrate resolve --applied "migration_name"
# or
npx prisma migrate resolve --rolled-back "migration_name"
Resources:
- https://www.prisma.io/docs/concepts/components/prisma-migrate
- https://www.prisma.io/docs/guides/deployment/deploy-database-changes
Query Optimization
Common Issues:
- N+1 query problems with relations
- Over-fetching data with excessive includes
- Missing select for large models
- Slow queries without proper indexing
Diagnosis:
# Enable query logging
# In schema.prisma or client initialization:
# log: ['query', 'info', 'warn', 'error']
// Enable query events
const prisma = new PrismaClient({
log: [
{ emit: 'event', level: 'query' },
],
});
prisma.$on('query', (e) => {
console.log('Query: ' + e.query);
console.log('Duration: ' + e.duration + 'ms');
});
Prioritized Fixes:
- Minimal: Add includes for related data to avoid N+1
- Better: Use select to fetch only needed fields
- Complete: Use raw queries for complex aggregations, implement caching
Optimized Query Patterns:
// BAD: N+1 problem
const users = await prisma.user.findMany();
for (const user of users) {
const posts = await prisma.post.findMany({ where: { authorId: user.id } });
}
// GOOD: Include relations
const users = await prisma.user.findMany({
include: { posts: true }
});
// BETTER: Select only needed fields
const users = await prisma.user.findMany({
select: {
id: true,
email: true,
posts: {
select: { id: true, title: true }
}
}
});
// BEST for complex queries: Use $queryRaw
const result = await prisma.$queryRaw`
SELECT u.id, u.email, COUNT(p.id) as post_count
FROM users u
LEFT JOIN posts p ON p.author_id = u.id
GROUP BY u.id
`;
Resources:
- https://www.prisma.io/docs/guides/performance-and-optimization
- https://www.prisma.io/docs/concepts/components/prisma-client/raw-database-access
Connection Management
Common Issues:
- Connection pool exhaustion
- "Too many connections" errors
- Connection leaks in serverless environments
- Slow initial connections
Diagnosis:
# Check current connections (PostgreSQL)
psql -c "SELECT count(*) FROM pg_stat_activity WHERE datname = 'your_db';"
Prioritized Fixes:
- Minimal: Configure connection limit in DATABASE_URL
- Better: Implement proper connection lifecycle management
- Complete: Use connection pooler (PgBouncer) for high-traffic apps
Connection Configuration:
// For serverless (Vercel, AWS Lambda)
import { PrismaClient } from '@prisma/client';
const globalForPrisma = global as unknown as { prisma: PrismaClient };
export const prisma =
globalForPrisma.prisma ||
new PrismaClient({
log: process.env.NODE_ENV === 'development' ? ['query'] : [],
});
if (process.env.NODE_ENV !== 'production') globalForPrisma.prisma = prisma;
// Graceful shutdown
process.on('beforeExit', async () => {
await prisma.$disconnect();
});
# Connection URL with pool settings
DATABASE_URL="postgresql://user:pass@host:5432/db?connection_limit=5&pool_timeout=10"
Resources:
How to use prisma-expert 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 prisma-expert
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches prisma-expert from GitHub repository sickn33/antigravity-awesome-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 prisma-expert. Access the skill through slash commands (e.g., /prisma-expert) 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
4.7★★★★★49 reviews- ★★★★★Kwame Rahman· Dec 24, 2024
Solid pick for teams standardizing on skills: prisma-expert is focused, and the summary matches what you get after install.
- ★★★★★Neel Wang· Dec 20, 2024
Useful defaults in prisma-expert — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Ganesh Mohane· Dec 16, 2024
prisma-expert fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Sakura Johnson· Dec 16, 2024
prisma-expert reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Valentina Rahman· Dec 8, 2024
prisma-expert has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Aisha Rao· Nov 27, 2024
Useful defaults in prisma-expert — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Aanya Jain· Nov 23, 2024
prisma-expert reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Aarav Verma· Nov 15, 2024
I recommend prisma-expert for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Hiroshi Thompson· Nov 11, 2024
prisma-expert has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Rahul Santra· Nov 7, 2024
prisma-expert is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
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