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Found 137 Skills
Essential CloudBase (TCB, Tencent CloudBase, 云开发, 微信云开发) development guidelines. MUST read when working with CloudBase projects, developing web apps, mini programs, backend services, fullstack development, static deployment, cloud functions, mysql/nosql database, authentication, cloud storage, web search or AI(LLM streaming) using CloudBase platform. Great supabase alternative.
Drop-in pandas replacement with ClickHouse performance. Use `import chdb.datastore as pd` (or `from datastore import DataStore`) and write standard pandas code — same API, 10-100x faster on large datasets. Supports 16+ data sources (MySQL, PostgreSQL, S3, MongoDB, ClickHouse, Iceberg, Delta Lake, etc.) and 10+ file formats (Parquet, CSV, JSON, Arrow, ORC, etc.) with cross-source joins. Use this skill when the user wants to analyze data with pandas-style syntax, speed up slow pandas code, query remote databases or cloud storage as DataFrames, or join data across different sources — even if they don't explicitly mention chdb or DataStore. Do NOT use for raw SQL queries, ClickHouse server administration, or non-Python languages.
Use when running commands inside a Zeabur service container. Use for one-off database operations like queries, data cleanup, or migrations (e.g. mongosh, psql, mysql, redis-cli). Use when user says "exec into container", "run command in service", "query database", "delete from database", "run mongo command", "run SQL", "check files in container", "debug inside service", or "shell into service". Use for container-level debugging like checking env vars, files, processes, or connectivity. NOT for deploying databases (use zeabur-template-deploy instead).
Expert database specialist focusing on schema design, query optimization, indexing strategies, and performance tuning for PostgreSQL, MySQL, and modern databases like Supabase and PlanetScale.
Guide the user through connecting a new data warehouse source — Postgres, MySQL, Stripe, Hubspot, MongoDB, Salesforce, BigQuery, Snowflake, and so on. Use when the user wants to "connect Stripe", "import data from Postgres", "add a new data source", "sync my warehouse tables", or wants to pick sync methods for each table. Walks through source-type discovery, credential validation, table discovery, per-table sync_type selection, and the final create call. Also covers picking a good prefix and what to do right after creation.
Workload-aware architecture design for Apache Doris. MUST USE when designing data architectures, choosing between data models, planning ingestion strategies, sizing clusters, or translating business requirements into Apache Doris system designs. Complements doris-best-practices with decision frameworks and sizing-first workflow. Use when user describes a workload involving: IoT, sensor data, telemetry, real-time analytics, dashboard, log analysis, log search, CDC sync, time-series, device monitoring, point query service, ad-hoc analytics, lakehouse federation, ETL/ELT pipeline, report analytics, clickstream, user behavior, observability, metrics, fleet tracking, or any OLAP workload requiring table design from scratch. Also triggers on prompts like: "design a table for...", "how should I store...", "build an architecture for...", "we have X devices sending data every Y seconds", "recommend a cluster size for...", "what data model should I use for...", "we need to ingest X GB/day", "migrate from MySQL/PostgreSQL to Apache Doris". Also use for legacy analytics/search/serving stack consolidation prompts even when Apache Doris is not named explicitly, including replacing or migrating from Impala, Kudu, Elasticsearch/ES, Greenplum, Presto, HBase, Hive, Hadoop, Redis, or Lambda-style multi-engine data platforms.
Database operations including querying, schema exploration, and data analysis. Activates for tasks involving PostgreSQL, MySQL, MariaDB, SQLite, MongoDB, Redis, Elasticsearch, or ClickHouse databases.
Analyzes and optimizes SQL/NoSQL queries for performance. Use when reviewing query performance, optimizing slow queries, analyzing EXPLAIN output, suggesting indexes, identifying N+1 problems, recommending query rewrites, or improving database access patterns. Supports PostgreSQL, MySQL, SQLite, MongoDB, Redis, DynamoDB, and Elasticsearch.
Drizzle ORM documentation covering queries, CRUD operations, schema definitions, migrations, caching (50 topics), custom types, and database connections. Includes integrations for PostgreSQL (Neon, Vercel, Supabase, AWS Data API, PlanetScale, Prisma), MySQL (AWS Data API, PlanetScale, TiDB), and SQLite (Bun, Cloudflare D1/Durable Objects, Expo, Turso, OP SQLite). Use when working with Drizzle queries, database schemas, migrations, type-safe SQL, ORM patterns, or connecting to supported databases.
Implementing Entity Framework Core repositories and migrations for PostgreSQL, MySQL, and SQLite at Bitwarden. Use when creating or modifying EF repositories, generating EF migrations, or working with non-MSSQL data access in the server repo.
Provides comprehensive Oracle Cloud Infrastructure (OCI) guidance including compute instances, networking (VCN, load balancers, VPN), storage (block, object, file), database services (Autonomous Database, MySQL, NoSQL), container orchestration (OKE), identity and access management (IAM), resource management, cost optimization, and infrastructure as code (Terraform OCI provider, Resource Manager). Produces infrastructure code, deployment scripts, configuration guides, and architectural diagrams. Use when designing OCI architecture, provisioning cloud resources, migrating to Oracle Cloud, implementing OCI security, setting up OCI databases, deploying containerized applications on OKE, managing OCI resources, or when users mention "Oracle Cloud", "OCI", "Autonomous Database", "VCN", "OKE", "OCI Terraform", "Resource Manager", "Oracle Cloud Infrastructure", or "OCI migration".
Drizzle ORM for type-safe SQL with PostgreSQL, MySQL, and SQLite. Use when defining schemas, writing queries, managing relations, running migrations, or using drizzle-kit. Use for drizzle, orm, schema, query, migration, pgTable, relations, drizzle-kit, drizzle-zod.