Skill UI

Automates Sequelize model creation for backend development, offering step-by-step guidance, best practices, and production-ready code/config validation when working with Node.js, Python, Go, databases, caching, messaging, and microservices.

Automates Snowflake data warehouse workflows via the Composio MCP, letting you list databases, schemas, and tables, run SQL (SELECT, DDL, DML), and integrate those operations into cross-app pipelines for faster data ops.

Execute systematic SQL injection vulnerability assessments on web applications using reconnaissance, payload tuning, and exploitation workflows to uncover database flaws, capture evidence, and validate remediation recommendations for authorized security testing.

This skill provides systematic patterns and best practices for transforming slow database queries into high-performance operations. It covers techniques like proper indexing, query plan analysis (e.g., using EXPLAIN), schema design improvements, and resolving common issues like N+1 query problems. Use it to debug performance bottlenecks, reduce database load, and ensure scalable application backends.

A comprehensive skill for optimizing complex SQL queries, designing robust database schemas, and troubleshooting performance bottlenecks across various dialects (PostgreSQL, MySQL, etc.). Use this when queries are slow, complex set-based logic is needed (CTEs, Window Functions), or when structuring/migrating a database schema. It provides detailed query plan analysis, advanced indexing strategies, and industry best practices.

Guides using SQLMap to automate SQL injection discovery, enumerate databases/tables/columns, dump data, and collect hashes across MySQL/PostgreSQL/MSSQL/Oracle during authorized penetration tests.

Guides analysts through automated SQL injection discovery and exploitation with SQLMap, covering enumeration, table/column mapping, data dumping, and advanced targeting across MySQL, PostgreSQL, MSSQL, Oracle, and other databases during authorized penetration tests.

Automate the entire Supabase development lifecycle within CI/CD pipelines using GitHub Actions. This tool links projects, validates database migrations, deploys Edge Functions, generates TypeScript types, and runs comprehensive tests against local Supabase instances. Essential for maintaining robust code quality and ensuring schema consistency before deployment.

This guide provides comprehensive, actionable methods to audit and significantly reduce Supabase operational costs. It covers advanced database tuning (vacuuming, index cleanup, bloat management), efficient storage lifecycle management, connection pooling strategies, and optimal plan selection. Use this when analyzing high billing reports, identifying resource waste, or implementing robust cost-saving measures in a cloud environment.

This comprehensive skill guides the full lifecycle management of Supabase projects in a production environment. It covers essential DevOps practices, including running database migrations, deploying Edge Functions, managing secrets, implementing zero-downtime blue/green rollouts, and executing robust rollback procedures and post-deployment health checks. Ideal for ensuring stable and reliable production deployments.

This guide demonstrates the fundamental "Hello World" query using the Supabase JS/Python client. It covers creating a structured table, enabling Row Level Security (RLS), inserting a record, and successfully selecting it back. This is essential for verifying project connectivity, understanding the basic data round-trip pattern, and mastering initial database interactions in a new Supabase environment.

Master advanced techniques for scaling Supabase projects to handle high production load. This skill covers six critical layers: implementing read replicas for analytics, optimizing connectivity using connection pooling (Supavisor), upgrading compute resources, utilizing CDN caching for Storage, deploying Edge Functions regionally, and performing database table partitioning. Ideal for engineers preparing for traffic spikes or optimizing large-scale database architectures.