Databases

Guidance for data resharding tasks that involve reorganizing files across directory structures with constraints on file sizes and directory contents. This skill applies when redistributing datasets, splitting large files, or reorganizing data into shards while maintaining constraints like maximum files per directory or maximum file sizes. Use when tasks involve resharding, data partitioning, or directory-constrained file reorganization.

Fixes tasks in To Rework and returns them to To Review. Applies reviewer feedback only for the selected task.

Use when building NestJS applications requiring modular architecture, dependency injection, or TypeScript backend development. Invoke for modules, controllers, services, DTOs, guards, interceptors, TypeORM/Prisma. Keywords: NestJS, Nest, Node.js, TypeScript backend, dependency injection.

Use for Vite+React+TanStack Query frontends on Bun/Cloudflare Workers with shadcn/Tailwind—provides dev console bridge, tmux layout, dense/no-motion UI defaults, and Justfile/CI parity.

Use when building real-time communication systems with WebSockets or Socket.IO. Invoke for bidirectional messaging, horizontal scaling with Redis, presence tracking, room management. Keywords: WebSocket, Socket.IO, real-time, pub/sub, Redis.

Error recovery and failure handling patterns for distributed systems including rollback strategies, circuit breakers, retry logic with exponential backoff, graceful degradation, and compensating transactions. Activates when task execution fails, timeouts occur, external services fail, database transactions fail, or cascade failure risks are detected. Use when recovering from failures, preventing data corruption, implementing resilience patterns, or handling partial system failures.

Use when investigating slow queries, analyzing execution plans, or optimizing database performance. Invoke for index design, query rewrites, configuration tuning, partitioning strategies, lock contention resolution. Keywords: database optimization, slow query, EXPLAIN ANALYZE, index optimization, query performance.

Use when developing Rust projects in the tempoxyz org—standardizes fmt/clippy/nextest, sccache+mold, feature-powerset checks, MSRV builds, docsrs flags, and xtask patterns so local and CI behavior match.

Use when optimizing PostgreSQL queries, configuring replication, or implementing advanced database features. Invoke for EXPLAIN analysis, JSONB operations, extension usage, VACUUM tuning, performance monitoring. Keywords: PostgreSQL, EXPLAIN, replication, JSONB, pg_stat.

Use when querying Jira issues, searching Confluence pages, creating tickets, updating documentation, or integrating Atlassian tools via MCP protocol.

Use when designing GraphQL schemas, implementing Apollo Federation, or building real-time subscriptions. Invoke for schema design, resolvers with DataLoader, query optimization, federation directives. Keywords: GraphQL, Apollo, Federation, schema design, resolvers.

Database schema design and data modeling patterns including normalization principles (1NF-5NF), denormalization trade-offs, entity relationship design, indexing strategies, schema evolution, and domain-driven design patterns. Activates when designing new database schemas, refactoring data models, discussing normalization vs denormalization decisions, planning schema migrations, or modeling complex domain entities. Use when creating new tables/collections, redesigning existing schemas, evaluating relationship patterns, or making data integrity decisions.

SQL query optimization patterns including EXPLAIN plan analysis, index strategies, query rewriting, and N+1 query prevention. Use when optimizing slow database queries, analyzing query performance, designing indexes, or debugging database bottlenecks. Works with PostgreSQL, MySQL, SQLite, and other SQL databases. Typical improvements: 10x-1000x query speedup.

Use when building Apache Spark applications, distributed data processing pipelines, or optimizing big data workloads. Invoke for DataFrame API, Spark SQL, RDD operations, performance tuning, streaming analytics.

Use when building high-performance async Python APIs with FastAPI and Pydantic V2. Invoke for async SQLAlchemy, JWT authentication, WebSockets, OpenAPI documentation. Keywords: FastAPI, Pydantic, async, SQLAlchemy, JWT, OpenAPI.

Use when optimizing SQL queries, designing database schemas, or tuning database performance. Invoke for complex queries, window functions, CTEs, indexing strategies, query plan analysis. Keywords: SQL, PostgreSQL, MySQL, optimization, EXPLAIN, indexing.

Comprehensive guide to implementing RAG systems including vector database selection, chunking strategies, embedding models, and retrieval optimization. Use when building RAG systems, implementing semantic search, optimizing retrieval quality, or debugging RAG performance issues.

Use when building RAG systems, vector databases, or knowledge-grounded AI applications requiring semantic search, document retrieval, or context augmentation.

Use SQL (PostgreSQL) when:

Use when encountering unfamiliar import statements; when exploring a dependency's API; when user asks "what's import X?", "what does import X do?", or about package documentation. - Generates comprehensive API documentation for Swift package dependencies on-demand. This skill helps you quickly obtain documentation for packages used in Xcode projects when you encounter unfamiliar module imports. Automatically resolves modules to packages and caches documentation for reuse. This is the primary tool for understanding individual `import` statements.