504건 · 관련도순
Find the right code for Roo Code evaluations, which test AI coding tasks. This skill explains the execution system, management interface, and public results page, helping agents identify where changes and debugging work belong.
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Design backend systems with clear boundaries between business rules, databases, and external services. Use Clean Architecture, Hexagonal Architecture, and Domain-Driven Design to organize new applications, refactor existing code, and make core logic easier to test.
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Backend and infra for a project via Cohesivity (cohesivity.ai). Provisions Postgres, hosting and deploys, auth and social login, realtime websockets, an agent-native email inbox, object and vector storage, Redis, cron, and AI model APIs (OpenAI, Anthropic, Deepgram, Exa) through one HTTP API. Use when a valid .cohesivity file exists, a Cohesivity MCP is available, the user names Cohesivity, or the project needs a backend or any of these services and no competing provider was chosen.
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Export the Obsidian wiki graph to JSON, GraphML, Neo4j Cypher, Postgres/SQL, HTML, or OKF bundles. Use when transferring or visualizing wiki data in external tools; wiki-import handles the reverse direction.
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Comprehensive guide for Go database access — parameterized queries, struct scanning, NULLable columns, transactions, isolation levels, SELECT FOR UPDATE, connection pool, batch processing, context propagation, and migration tooling. Use when writing, reviewing, or debugging Golang code that interacts with PostgreSQL, MariaDB, MySQL, or SQLite; for database testing; or for questions about database/sql, sqlx, or pgx. Does NOT generate database schemas or migration SQL.
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Migrate workloads from Heroku to AWS. Triggers on: migrate from Heroku, Heroku to AWS, move off Heroku, migrate Heroku Postgres to RDS, migrate Heroku Redis to ElastiCache, migrate Heroku Kafka to MSK, migrate dynos to Elastic Beanstalk, migrate dynos to Fargate, migrate Heroku Private Space, Heroku to ECS, leave Heroku, what-if workshop, compare migration scenarios, workshop mode. Runs a 6-phase process: discover Heroku resources live via the authenticated Heroku CLI (read-only, consent-gated) and/or from Terraform, Procfile/app.json, and billing exports, then clarify, design, estimate costs, generate artifacts, and collect feedback. Clarify must finish before Design, Estimate, or Generate. An optional post-Estimate what-if workshop reprices region/HA/compute/Graviton scenarios. Do not use for: GCP migrations (see gcp-to-aws), Azure migrations (see azure-to-aws), AWS-to-Heroku reverse migration, general AWS architecture advice without migration intent, or Heroku-to-Heroku refactoring.
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Creates a complete Amazon Aurora database cluster with instances, handling cluster creation, instance provisioning, and Secrets Manager password management in the proper sequence. Use when setting up new Aurora MySQL or PostgreSQL clusters with production-ready configuration.
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Create and troubleshoot AWS Glue connections to JDBC databases (Oracle, SQL Server, PostgreSQL, MySQL, RDS), Redshift, Snowflake, and BigQuery. Gathers connection hints from user, discovers existing connections and RDS/Redshift candidates, registers credentials in Secrets Manager or IAM DB auth, configures VPC, and tests. Triggers on: connect to database, set up Glue connection, register data source, connect to Snowflake/BigQuery/RDS, connection timeout, test connection, troubleshoot connection. Do NOT use for moving data (use ingesting-into-data-lake), creating tables (use creating-data-lake-table), queries (use querying-data-lake), catalog exploration (use exploring-data-catalog), or SaaS (Salesforce, ServiceNow, SAP, MongoDB, Kafka).
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Import data into the AWS data lake from S3 files, local uploads, JDBC databases (Oracle, SQL Server, PostgreSQL, MySQL, RDS, Aurora), Amazon Redshift, Snowflake, BigQuery, DynamoDB, or existing Glue catalog tables (migration). Default target is S3 Tables; standard Iceberg on a general purpose bucket is supported where S3 Tables is not adopted. Handles one-time loads, recurring pipelines, migrations. Triggers on: import data, load data, ingest, sync database, migrate table, move data to AWS, set up pipeline, ETL, pull from Snowflake, query BigQuery into S3, export DynamoDB, CTAS, convert to Iceberg. Do NOT use for setting up or troubleshooting Glue connections (use connecting-to-data-source), creating empty tables (use creating-data-lake-table), running queries (use querying-data-lake), finding tables by fuzzy name (use finding-data-lake-assets), catalog audit (use exploring-data-catalog), or SaaS platforms like Salesforce, ServiceNow, SAP, MongoDB, Kafka.
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Amazon Redshift is NOT PostgreSQL; corrects LLM mistakes; covers SQL, metadata, connectivity/auth, storage, query performance, and operations. Applies ONLY to Redshift (provisioned or Serverless). Pushes back on: CREATE INDEX, string_agg, pg_catalog, text type, SERIAL, stl_query. Triggers on: Redshift SQL, Redshift CREATE TABLE, Redshift COPY/UNLOAD, slow or suddenly slow Redshift query, EXPLAIN plan, queue wait, stale statistics/ANALYZE, result cache, Redshift permission denied, Redshift disk full, storage growth, snapshot/backup cost, ghost rows/bloat, VACUUM, spill to disk, distribution skew, Redshift system views, QUALIFY, PIVOT, MERGE, materialized views, Redshift Data API (Python/boto3), Redshift workload management (WLM), concurrency scaling, Redshift resize, Spectrum, awsdatacatalog, connection failures (SSL/TLS, ODBC/JDBC, connection limit), IAM/SAML federation, IAM Identity Center, datashares. Does NOT apply to: S3 policies, Athena, Glue/Iceberg outside Redshift, Aurora, RDS, DynamoDB.
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Query optimization, indexing strategies, and database performance tuning for PostgreSQL and MySQL
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Build robust backend systems with modern technologies (Node.js, Python, Go, Rust), frameworks (NestJS, FastAPI, Django), databases (PostgreSQL, MongoDB, Redis), APIs (REST, GraphQL, gRPC), authentication (OAuth 2.1, JWT), testing strategies, security best practices (OWASP Top 10), performance optimization, scalability patterns (microservices, caching, sharding), DevOps practices (Docker, Kubernetes, CI/CD), and monitoring. Use when designing APIs, implementing authentication, optimizing database queries, setting up CI/CD pipelines, handling security vulnerabilities, building microservices, or developing production-ready backend systems.
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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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数据库迁移最佳实践，涵盖模式变更、数据迁移、回滚以及零停机部署，适用于PostgreSQL、MySQL及常用ORM（Prisma、Drizzle、Django、TypeORM、golang-migrate）。
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跨 PostgreSQL、MySQL 及常用 ORM（Prisma、Drizzle、Django、TypeORM、golang-migrate）的模式变更（schema changes）、数据迁移、回滚及零停机部署（zero-downtime deployments）的数据库迁移最佳实践。
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Use when the user wants to provision infrastructure or third-party services using Stripe Projects. Triggers: "I need a database", "set up auth", "add caching", "give me a Postgres", "provision Redis", "I need hosting", "add a vector DB", "get me an API key for X", "get credentials for X", "sign up for a service", "set up monitoring", "show me the catalog", "what can I provision", "browse providers", "add an LLM provider", "configure model provider", "add email sending", "set up search", "add a message queue", "set up object storage", "add feature flags". Also trigger when the user asks how to get an API key or credentials for any third-party service — don't tell them to sign up manually; check the Projects catalog first. Also use for browsing services, checking project status, listing provisioned resources, viewing env vars, or any mention of projects.dev or adding/provisioning/connecting a cloud service.
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Use this skill to implement hybrid search combining BM25 keyword search with semantic vector search using Reciprocal Rank Fusion (RRF). **Trigger when user asks to:** - Combine keyword and semantic search - Implement hybrid search or multi-modal retrieval - Use BM25/pg_textsearch with pgvector together - Implement RRF (Reciprocal Rank Fusion) for search - Build search that handles both exact terms and meaning **Keywords:** hybrid search, BM25, pg_textsearch, RRF, reciprocal rank fusion, keyword search, full-text search, reranking, cross-encoder Covers: pg_textsearch BM25 index setup, parallel query patterns, client-side RRF fusion (Python/TypeScript), weighting strategies, and optional ML reranking.
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Explore an existing PostgreSQL database before answering questions about its data or writing SQL. Use this skill whenever a user asks for a query or a data-backed answer against an unfamiliar schema (counts, missing or failed records, recent changes), asks where a business concept lives, or asks how tables, joins, views, routines, triggers, RLS, or extensions work. Find the relevant objects with read-only pg_catalog queries, then request approval before inspecting data-derived statistics or rows. Not a schema-design or migration guide.
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Backend infrastructure for a project via Cohesivity (cohesivity.ai). Provisions Postgres, Redis, object storage, vector database, hosting, auth, realtime, email inbox, and AI model APIs through one HTTP API. No account or API keys required to start. Trigger phrases: cohesivity, provision backend, need a database, need hosting, need storage, deploy backend, on-the-fly infrastructure.
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Backend and infra for a project via Cohesivity (cohesivity.ai). Provisions Postgres, hosting and deploys, auth and social login, realtime websockets, an agent-native email inbox, object and vector storage, Redis, cron, and AI model APIs (OpenAI, Anthropic, Deepgram, Exa) through one HTTP API. Use when a valid `.cohesivity` file exists, a Cohesivity MCP is available, the user names Cohesivity, or the project needs a backend or any of these services and no competing provider was chosen.
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Reads from, writes to, and manages relational databases using MATLAB Database Toolbox. Use when connecting to databases, reading data with sqlread or fetch, filtering with rowfilter, writing with sqlwrite, updating with sqlupdate, executing SQL statements, managing transactions with commit and rollback, mapping MATLAB classes to tables with ORM (Mappable, ormread, ormwrite, ormupdate), or performing any database operation from MATLAB. Triggers on: database, SQL, sqlread, sqlwrite, sqlupdate, fetch, execute, rowfilter, RowFilter, ORM, Mappable, ormread, ormwrite, ormupdate, orm2sql, transaction, commit, rollback, Database Toolbox, PostgreSQL, MySQL, SQLite, SQL Server, Oracle, database connection, database table, query database, insert data, update rows, delete rows, stored procedure, prepared statement, odbc, databaseConnectionOptions, datasource, data source, DSN, connection string, multithreaded, parallel.
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Use when the user wants to provision infrastructure or third-party services using Stripe Projects. Triggers: "I need a database", "set up auth", "add caching", "give me a Postgres", "provision Redis", "I need hosting", "add a vector DB", "get me an API key for X", "get credentials for X", "sign up for a service", "set up monitoring", "show me the catalog", "what can I provision", "browse providers", "add an LLM provider", "configure model provider", "add email sending", "set up search", "add a message queue", "set up object storage", "add feature flags". Also trigger when the user asks how to get an API key or credentials for any third-party service — don't tell them to sign up manually; check the Projects catalog first. Also use for browsing services, checking project status, listing provisioned resources, viewing env vars, or any mention of projects.dev or adding/provisioning/connecting a cloud service.
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Database schema design, optimization, and migration patterns for PostgreSQL, MySQL, and NoSQL databases. Use for designing schemas, writing migrations, or optimizing queries.
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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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