Skill UI

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.

This skill provides a structured approach to systematically identify security threats by applying the STRIDE methodology (Spoofing, Tampering, Repudiation, Information Disclosure, Denial of Service, Elevation of Privilege). It is crucial for conducting thorough threat modeling sessions, analyzing system architectures, reviewing security design decisions, and creating robust security documentation for compliance and auditing purposes.

A comprehensive guide for structured incident response when a Supabase-backed application fails. This runbook guides users through triaging issues, verifying platform status, inspecting connection pools, debugging stuck queries using pg_stat_activity, and analyzing Edge Function logs. Essential for root cause analysis and escalating issues to support.

This comprehensive guide provides systematic methods to optimize Supabase query and database performance. Techniques cover PostgreSQL indexing (basic, composite, partial), using EXPLAIN ANALYZE for query plan analysis, optimizing client calls (column selection, pagination), and managing infrastructure resources like connection pooling. Use this when facing slow queries, high latency, or preparing a project for production-scale traffic.

This expert skill specializes in guiding comprehensive GitHub issue resolution. It covers systematic bug investigation, feature implementation, and collaborative development workflows. Expertise includes issue triage, root cause analysis, test-driven development, and professional pull request management, ensuring vague reports are transformed into production-ready code following modern CI/CD practices.

A comprehensive skill to identify, analyze, prioritize, and track technical debt across large codebases. It provides three interconnected tools: a Debt Scanner, a Debt Prioritizer (using cost-of-delay frameworks), and a Debt Dashboard. This system helps engineering teams make data-driven decisions to balance new features with necessary maintenance and refactoring work, ensuring the long-term sustainability of software systems.

A specialized skill designed to ensure robust software quality by covering the entire testing lifecycle. This includes defining test strategies, writing unit, integration, and E2E tests, and implementing advanced testing types like performance (k6), security (OWASP), and functional testing. It guides users through coverage analysis, debugging flaky tests, and generating detailed defect and quality reports.

This tool rigorously validates API schemas against industry standards, including OpenAPI 3.0/3.1, JSON Schema, and GraphQL SDL. It performs structural analysis to detect incomplete schemas, inconsistent naming, undocumented endpoints, and critical breaking changes. Use it within your CI/CD pipeline to ensure API contracts are robust, compliant, and maintainable before release.

Performs pattern-driven searches for similar vulnerabilities across repositories after a known issue is found, guiding analysts through precise generalization, triage, and tool choices (ripgrep, Semgrep, CodeQL) to audit and prioritize true positives.

This comprehensive runbook provides rapid, structured procedures for incident response on Vast.ai cloud GPU instances. It covers common failure scenarios like spot preemption, training job crashes, and GPU hardware issues. Users can follow the steps for triage, mitigation, recovery, and postmortem analysis to minimize downtime and ensure computational continuity.

This deep dive guides users through migrating complex GPU workloads, such as deep learning training pipelines, from major hyperscalers (AWS, GCP, Azure) or other cloud platforms to Vast.ai. It covers critical steps including cost comparison analysis, adapting Docker images for new environments, securely handling cloud credentials via environment variables, and implementing robust validation and rollback procedures to ensure a smooth transition.

A comprehensive guide for diagnosing difficult and intermittent Vercel deployment issues. Covers advanced topics such as cold start analysis, edge function crashes, region-specific behavior isolation, function bundle optimization, and concurrency throttling. Use this when standard logging fails and systematic, deep-dive debugging is required for production stability.