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Found 6,190 Skills
Express/Hono with Supabase and Drizzle ORM
Invoke IMMEDIATELY via python script when user requests codebase understanding, architecture comprehension, or repository orientation. Do NOT explore first - the script orchestrates exploration.
Creates and manages ephemeral Neon databases for testing, CI/CD pipelines, and isolated development environments. Use when building temporary databases for automated tests or rapid prototyping.
Database access patterns for performance. Separate read/write models, avoid N+1 queries, use AsNoTracking, apply row limits, and never do application-side joins. Works with EF Core and Dapper.
Coordinates 9 specialized audit workers (security, build, architecture, code quality, dependencies, dead code, observability, concurrency, lifecycle). Researches best practices, delegates parallel audits, aggregates results into single Linear task in Epic 0.
This skill should be used when managing database schema, migrations, and seed data using Prisma ORM with Supabase PostgreSQL. Apply when setting up Prisma with Supabase, creating migrations, seeding data, configuring shadow database for migration preview, adding schema validation to CI, or managing database changes across environments.
Senior specialist in Supabase SSR, RLS Enforcement, and Next.js 16.1+ architecture. Use when designing database schemas, auth flows, or real-time syncing in 2026.
Comprehensive guide for database management patterns covering PostgreSQL and MongoDB including schema design, indexing, transactions, replication, and performance tuning
Database operations for Supabase: query/write/migration/logs/type generation. Triggers: query/statistics/export/insert/update/delete/fix/backfill/migrate/logs/alerts/type generation. Does not trigger for: pure architecture discussion or code planning. Write operations require confirmation; UPDATE/DELETE without WHERE is refused. MCP is optional — works with CLI/Console too.
Safe patterns for evolving database schemas in production with decision trees and troubleshooting guidance.
Instructions for using the DeepBase multi-driver persistence library. Use when a task requires data persistence, storage abstraction, multi-backend setups, data migration between drivers, or integrating DeepBase into a Node.js project.
Query and retrieve AI-predicted protein structures from DeepMind's AlphaFold database. Fetch structures via UniProt accession, interpret pLDDT/PAE confidence scores, and access bulk proteome data for structural biology workflows.