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CloudBase Run backend development rules (Function mode/Container mode). Use this skill when deploying backend services that require long connections, multi-language support, custom environments, AI agent development, or migrating existing/GitHub apps that need VPC access to MySQL/PostgreSQL/Redis. Also use when diagnosing CloudRun container deploy failures (deploy_failed, readiness/probe failed, image won't start, docker.io pull loops) or a deploy stuck behind a running deploy task. For stateless HTTP services, prefer HTTP cloud functions.

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CloudBase CLI (tcb, 云开发CLI, Tencent CloudBase命令行) resource management skill. Use when deploying cloud functions, CloudRun, storage, NoSQL/MySQL, static hosting, permissions, CORS/domains via tcb; for CI/CD and batch ops; when the user prefers CLI; or as the first-session fallback when CloudBase MCP tools are not loaded yet (after install/config, before IDE restart). Also covers tcb login and site switching (国内站/国际站 via --intl or config isIntl), environment lifecycle (env create/modify/renew/delete/apikey/login/domain), tcb config and cloudbaserc.json sync, log search (logs search, CLS), metric monitoring (monitor), data model and PostgreSQL migrations (db model, db pg migration), sandbox/agent/integration management — do not default to tcb deploy.

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Use this skill when you develop, design, build, deploy, debug, migrate, or troubleshoot CloudBase (腾讯云开发, 云开发, TCB, 微信云开发) projects — Web, 微信小程序, 小程序, uni-app, mobile (iOS, Android, Flutter, React Native). Covers UI (页面, 界面, 表单, dashboard, prototype, 原型); auth (登录, 注册, OAuth, publishable key); databases (NoSQL 文档数据库, MySQL 关系型数据库, PostgreSQL/CloudBase PG, app.rdb(), queryPgDatabase/managePgDatabase, CRUD, security rules); 云函数/cloud functions (serverless, scf_bootstrap); CloudRun (云托管, Dockerfile); 云存储; built-in AI (内置大模型, AI 对话, streaming, 流式输出, 图片生成, generateText, streamText, createModel, generateImage, TokenHub, Hunyuan, DeepSeek, GLM, Kimi, Token Credits 资源包, 小程序成长计划); third-party/custom model onboarding (第三方大模型接入, 大模型调用, LLM API); AI agent (智能体, AG-UI, LangGraph); ops troubleshooting (巡检, 诊断, 日志); spec workflow (需求文档, 技术方案, requirements, tasks.md). Do NOT use for non-CloudBase projects, pure frontend without CloudBase, or self-hosted backends without CloudBase.

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Unified CloudBase execution guide for all-in-one skill installs. Use this first for CloudBase app tasks, especially existing apps with TODOs, fixed pages, or active handlers. Routes PostgreSQL / CloudBase PG / app.rdb() / queryPgDatabase / managePgDatabase work away from legacy NoSQL and old auth patterns.

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Backend development with Node.js/Express/Fastify and PostgreSQL. Use when designing REST or GraphQL APIs, optimizing database queries, implementing authentication, building microservices, handling migrations, or reviewing backend code.

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Database design with schema analysis, index optimization, and migration generation for PostgreSQL, MySQL, MongoDB, and DynamoDB. Use when designing schemas, optimizing queries, planning migrations, or analyzing database performance.

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Design relational schemas from requirements with normalization, migrations, ERDs, RLS policies, and indexes for PostgreSQL, MySQL, and SQLite. Use when designing new features, reviewing schemas, or adding multi-tenancy.

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Optimizes PostgreSQL queries, configures replication, implements advanced features including EXPLAIN analysis, JSONB operations, extension usage, and VACUUM tuning.

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Optimizes database queries and improves performance across PostgreSQL and MySQL systems including index design, query rewrites, configuration tuning, and partitioning strategies.

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Expert knowledge for Azure Database Migration Service development including troubleshooting, decision making, limits & quotas, security, integrations & coding patterns, and deployment. Use when planning Azure DMS migrations for MySQL, PostgreSQL, MongoDB, SSIS-to-Azure SQL, or hybrid workloads, and other Azure Database Migration Service related development tasks. Not for Azure Migrate (use azure-migrate), Azure SQL Database (use azure-sql-database), Azure SQL Managed Instance (use azure-sql-managed-instance), SQL Server on Azure Virtual Machines (use azure-sql-virtual-machines).

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Expert knowledge for Azure Cosmos DB development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when using Cosmos DB NoSQL/Mongo/Cassandra APIs, change feed, multi-region HA, vector search, or Cosmos DB for PostgreSQL, and other Azure Cosmos DB related development tasks. Not for Azure Table Storage (use azure-table-storage), Azure SQL Database (use azure-sql-database), Azure SQL Managed Instance (use azure-sql-managed-instance), Azure Virtual Machines (use azure-virtual-machines).

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Use for authorized database security assessment covering PostgreSQL/MySQL/MSSQL/Mongo/Redis exposure, authz, UDF/command paths, and misconfiguration review.

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PostgreSQL database patterns for query optimization, schema design, indexing, and security. Based on Supabase best practices.

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Optimize SQL query performance through EXPLAIN analysis, indexing strategies, and query rewriting for PostgreSQL, MySQL, and SQL Server. Use when debugging slow queries, analyzing execution plans, or improving database performance.

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Time-series database implementation for metrics, IoT, financial data, and observability backends. Use when building dashboards, monitoring systems, IoT platforms, or financial applications. Covers TimescaleDB (PostgreSQL), InfluxDB, ClickHouse, QuestDB, continuous aggregates, downsampling (LTTB), and retention policies.

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Relational database implementation across Python, Rust, Go, and TypeScript. Use when building CRUD applications, transactional systems, or structured data storage. Covers PostgreSQL (primary), MySQL, SQLite, ORMs (SQLAlchemy, Prisma, SeaORM, GORM), query builders (Drizzle, sqlc, SQLx), migrations, connection pooling, and serverless databases (Neon, PlanetScale, Turso).

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SQL query optimization and database performance specialist. Use when optimizing slow queries, fixing N+1 problems, designing indexes, implementing caching, or improving database performance. Works with PostgreSQL, MySQL, and other databases.

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TimescaleDB - PostgreSQL extension for high-performance time-series and event data analytics, hypertables, continuous aggregates, compression, and real-time analytics

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Comprehensive guide to PostgreSQL migrations - common errors, generated columns, full-text search, indexes, idempotent migrations, and best practices for database schema changes

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Consult PostgreSQL's pg_dump implementation for guidance on system catalog queries and schema extraction when implementing pgschema features

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Comprehensive guide for migrating PostgreSQL tables to TimescaleDB hypertables with optimal configuration and performance validation

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Analyze an existing PostgreSQL database to identify tables that would benefit from conversion to TimescaleDB hypertables

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Work with MongoDB (document database, BSON documents, aggregation pipelines, Atlas cloud) and PostgreSQL (relational database, SQL queries, psql CLI, pgAdmin). Use when designing database schemas, writing queries and aggregations, optimizing indexes for performance, performing database migrations, configuring replication and sharding, implementing backup and restore strategies, managing database users and permissions, analyzing query performance, or administering production databases.

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Comprehensive backend development guide for Langfuse's Next.js 14/tRPC/Express/TypeScript monorepo. Use when creating tRPC routers, public API endpoints, BullMQ queue processors, services, or working with tRPC procedures, Next.js API routes, Prisma database access, ClickHouse analytics queries, Redis queues, OpenTelemetry instrumentation, Zod v4 validation, env.mjs configuration, tenant isolation patterns, or async patterns. Covers layered architecture (tRPC procedures → services, queue processors → services), dual database system (PostgreSQL + ClickHouse), projectId filtering for multi-tenant isolation, traceException error handling, observability patterns, and testing strategies (Jest for web, vitest for worker).

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