Databases

Use when receiving feedback, before implementing suggestions, especially if feedback seems unclear or technically questionable - requires technical rigor and verification, not performative agreement or blind implementation

Executes database migrations using the postgres MCP server. Use when applying schema changes, running migrations, or updating database structure.

Technical workflow for implementing accessible React user interfaces with shadcn/ui, Tailwind CSS, and TanStack Query. Includes 6-phase process with mandatory Style Guide compliance, Context7 best practices consultation, Chrome DevTools validation, and WCAG 2.1 AA accessibility standards. Use after Test Agent, Implementer, and Supabase agents complete their work.

Use when building Python web APIs, database-backed applications, or backend services. Covers FastAPI, SQLAlchemy (async), PostgreSQL, Alembic migrations, and performance patterns. Triggers on API endpoint creation, database models, query optimization, or migration planning. Extends python-development skill.

Build web components using Custom Elements v1 API with Declarative Shadow DOM, attribute-driven state, handleEvent pattern, and zero DOM selection. Use when creating custom elements, extending built-in HTML elements, or implementing component-based architecture. NO querySelector, NO innerHTML, NO external libraries - pure web platform APIs only.

RLS policy testing patterns for Supabase - automated test cases for Row Level Security enforcement, user isolation verification, multi-tenant security, and comprehensive security audit scripts. Use when testing RLS policies, validating user isolation, auditing Supabase security, verifying tenant isolation, testing row level security, running security tests, or when user mentions RLS testing, security validation, policy testing, or data leak prevention.

Collaborate on documents with tracked changes, suggestions, and iterative refinement. Use for reviewing drafts, providing editorial feedback, and collaborative document development.

Implement authentication and authorization using @delon/auth. Use this skill when adding login/logout flows, JWT token management, role-based access control (RBAC), route guards, HTTP interceptors, and session management. Integrates with Firebase Auth and custom permission systems. Ensures secure token storage, automatic token refresh, and consistent authorization checks across components and services.

Detect N+1 queries, analyze slow queries with EXPLAIN, identify missing indexes, and ensure safe online index migrations. Use when optimizing query performance, preventing performance regressions, or debugging slow endpoints. Complements database-migrations skill which covers index creation syntax.

기존 GCP 리소스(BigQuery, GCS, IAM 등)를 gcloud/bq 명령어로 추출하여 문서화하고, 이를 Terraform(IaC) 코드로 변환하는 워크플로우 스킬입니다. Reverse Engineering Infrastructure.

Comprehensive SaaS planning system for solo developers using Next.js + Supabase + Stripe stack. Converts ideas into shippable subscription products with scope control, feature prioritization, billing architecture, technical roadmap, and anti-feature-creep mechanisms. Generates PRDs with subscription models, pricing strategies, and Claude Code starter prompts. Use when planning SaaS products, subscription apps, or when user mentions billing, payments, recurring revenue, or subscription models.

Comprehensive Supabase expert with access to 2,616 official documentation files covering PostgreSQL database, authentication, real-time subscriptions, storage, edge functions, vector embeddings, and all platform features. Invoke when user mentions Supabase, PostgreSQL, database, auth, real-time, storage, edge functions, backend-as-a-service, or pgvector.

Triage code review feedback and reflect follow-up tasks in pending-questions/context. Use when incorporating review results.

Complete knowledge domain for Cloudflare Vectorize - globally distributed vector database for buildingsemantic search, RAG (Retrieval Augmented Generation), and AI-powered applications.Use when: creating vector indexes, inserting embeddings, querying vectors, implementing semantic search,building RAG systems, configuring metadata filtering, working with Workers AI embeddings, integratingwith OpenAI embeddings, or encountering metadata index timing errors, dimension mismatches, filtersyntax issues, or insert vs upsert confusion.Keywords: vectorize, vector database, vector index, vector search, similarity search, semantic search,nearest neighbor, knn search, ann search, RAG, retrieval augmented generation, chat with data,document search, semantic Q&A, context retrieval, bge-base, @cf/baai/bge-base-en-v1.5,text-embedding-3-small, text-embedding-3-large, Workers AI embeddings, openai embeddings,insert vectors, upsert vectors, query vectors, delete vectors, metadata filtering, namespace filtering,topK

Project context from ChromaDB knowledge graph. Triggers on "how does this project work", "architecture", "where is X", "why was Y chosen", "project structure", "component relationships", "design decisions".

Next.js 16 migration guide (async request APIs, "use cache", Turbopack)

Enterprise Notion integration with MCP server architecture, database operations, and content management

SQL query patterns, optimization, and database best practices. Use when writing SQL queries, discussing database design, query optimization, or working with PostgreSQL, MySQL, SQLite. Triggers on mentions of SQL, SELECT, JOIN, INDEX, query optimization, database schema, PostgreSQL, MySQL.

This skill should be used when the user asks about "namespaces", "singleton", "TileManager", "GameManager", "TokenManager", "InputManager", "data flow", "class responsibilities", "layers", "folder structure", "code organization", "design patterns", "ScriptableObject", "databases", or discusses Zero-Day Attack codebase architecture and patterns.

Complete knowledge domain for Cloudflare D1 - serverless SQLite database on Cloudflare's edge network.Use when: creating D1 databases, writing SQL migrations, configuring D1 bindings, querying D1 from Workers,handling SQLite data, building relational data models, or encountering "D1_ERROR", "statement too long","too many requests queued", migration failures, or query performance issues.Keywords: d1, d1 database, cloudflare d1, wrangler d1, d1 migrations, d1 bindings, sqlite workers,serverless database, edge database, d1 queries, sql cloudflare, prepared statements, batch queries,d1 api, wrangler migrations, D1_ERROR, D1_EXEC_ERROR, statement too long, database bindings,sqlite cloudflare, sql workers api, d1 indexes, query optimization, d1 schema