“sql”的搜索结果

Design and build backend services with API scaffolding, database migrations, authentication reviews, and load testing. Generate route handlers from OpenAPI specifications, identify PostgreSQL optimization opportunities, and compare architecture choices against traffic, data sensitivity, and reliability requirements.

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• Generating API route handlers from OpenAPI
• Investigating slow PostgreSQL queries
• Reviewing authentication and input validation

Design an enterprise search system that answers questions using retrieved company content, an approach called RAG. Gather requirements and produce architecture diagrams, deployment guidance, and validation plans using GKE, AlloyDB, and open models.

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• Designing conversational search for internal documents
• Planning RAG with a vector-enabled SQL database
• Hosting open models on GKE

Convert Snowflake dbt SQL models to BigQuery through a bulk migration workflow. Preserve Jinja template logic while adapting configuration, explicit type conversions, JSON access, and deduplication patterns, with translated files saved in their directory structure.

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• Migrating Snowflake dbt models to BigQuery in bulk
• Preserving dbt references and incremental processing logic
• Adapting JSON, array, and STRUCT access during migration

Answer business data questions with Wren CLI by checking model definitions, reusing past queries, and executing SQL or predefined aggregations. The workflow also covers query verification, error diagnosis, and saving successful queries for future use.

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• Analyze monthly revenue trends
• Rank customers by purchase value
• Compare metrics across plans or regions

Use Quicknode to connect applications to blockchains, retrieve wallet and asset data, and monitor activity. Covers event notifications, live data streams, historical backfills, and SQL queries, with guidance for choosing suitable services and access methods.

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• Connecting an app to blockchain data
• Setting up transaction and event notifications
• Recovering missing historical stream data

Amazon Aurora PostgreSQL — creates, modifies, and advises on Aurora PostgreSQL clusters specifically (PostgreSQL-compatible engine, Aurora serverless, express configuration, pgvector, Babelfish). Trigger for Aurora PostgreSQL cluster operations, express-configuration quick-start, ACU sizing, I/O-Optimized storage, commitment pricing, or PostgreSQL upgrade planning. For Aurora MySQL, use amazon-aurora-mysql instead. Contains safety guardrails, express-first routing, and response templates that override defaults.

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SQL database migrations with zero-downtime strategies for PostgreSQL, MySQL, SQL Server

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Manages a Fabric SQL database item, the OLTP SQL Server engine, including running T-SQL through sqlcmd, temporal and vector similarity search, schema and sys.tables inspection, dacpac deployment, and Query Store, blocked sessions and regressed-plan investigation. Use for any query or change against a SQL database item. Warehouse, lakehouse SQL endpoint and mirrored items belong to sqldw-cli.

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Expert knowledge for SQL Server on Azure Virtual Machines development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when planning SQL VM vs Managed Instance, Always On/FCI HADR, Azure storage/backups, Key Vault/Entra auth, or KQL telemetry, and other SQL Server on Azure Virtual Machines related development tasks. Not for Azure SQL Database (use azure-sql-database), Azure SQL Managed Instance (use azure-sql-managed-instance), Azure Virtual Machines (use azure-virtual-machines), Azure Data Science Virtual Machines (use azure-data-science-vm).

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SQL injection occurs when untrusted user input is interpolated directly into database queries, allowing attackers to alter query logic. Detect via single-quote errors, boolean-based blind responses (AND 1=1 vs AND 1=2), time-delay payloads (SLEEP, WAITFOR), UNION column enumeration, and error messages from MySQL, Oracle, MSSQL, PostgreSQL. Tools: sqlmap, sqlbftools, Burp Suite, wfuzz with SQLi fuzz strings.

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使用 AACT (Aggregate Analysis of ClinicalTrials.gov) PostgreSQL 数据仓库进行批量、历史、聚合性临床试验数据挖掘。Use this skill when the user requests bulk SQL analysis over the full clinical trials data warehouse — historical trial trends, disease landscapes, similar-design matching, or multi-year aggregations across hundreds of thousands of NCT records. 触发场景包括：AACT 查询、临床试验批量分析、PostgreSQL 试验数据、全量 NCT 检索、试验数据挖掘、历史试验分析、clinical trials data warehouse、SQL trials、bulk trial analysis、disease landscape、试验设计相似性匹配、跨年度聚合、sponsor/phase/country 多维统计。**与 clinical-trials-v2 差异**：本 skill 走批量 SQL · 离线大数据（PostgreSQL）；v2 走实时 API · 单查询。两者互补：单条 NCT 实时状态用 v2，百万级历史挖掘用本 skill。支持云端公共 PostgreSQL（aact-db.ctti-clinicaltrials.org · 零部署）和每日 dump 本地还原（高性能 · 离线）两种连接方式，自动检测优先用本地。跨平台（macOS/Linux/Windows）参数化 SQL 防注入，read-only 强制保护。

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PostgreSQL-specific development assistant focusing on unique PostgreSQL features, advanced data types, and PostgreSQL-exclusive capabilities. Covers JSONB operations, array types, custom types, range/geometric types, full-text search, window functions, and PostgreSQL extensions ecosystem. Use when writing or tuning PostgreSQL-specific SQL or choosing PostgreSQL features for a design.

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Next.js + Better Auth + PostgreSQL を Docker で構築し、Cloud Run へデプロイするスキル。ローカル開発環境のセットアップから Docker Compose、Dockerfile 作成、Cloud Run + Cloud SQL + Secret Manager を使った本番デプロイまでをカバーする。「Next.js と Better Auth でアプリを作りたい」「Docker で PostgreSQL を使いたい」「Docker で構築したい」「Docker Compose を使いたい」「アプリを Docker 化したい」「Dockerfile を書きたい」「Cloud Run にデプロイしたい」「Cloud SQL や Secret Manager を使いたい」ときに使う。

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Specialized skill for containerized database testing using Testcontainers. Use when testing real database behavior, using SQL Server/PostgreSQL/MySQL containers, testing EF Core/Dapper. Covers container startup, database migrations, test isolation, container sharing. Keywords: testcontainers, container testing, database testing, MsSqlContainer, PostgreSqlContainer, MySqlContainer, EF Core testing, Dapper testing, Testcontainers.MsSql, Testcontainers.PostgreSql, GetConnectionString, IAsyncLifetime, CollectionFixture

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通过操作次数与实测数据排查OpenClaw启动、聊天和界面显示缓慢的原因，优先减少不必要的处理，并支持性能改进PR的编写与审查。

• 排查启动或聊天响应缓慢
• 减少重复SQL查询与文件读取
• 根据实测数据审查性能改进PR

使用 Flox 将开发工具、数据库、版本及配置集中到文件中，建立可在 macOS 和 Linux 上复现的开发环境，并与团队共享或为智能体添加项目工具。

• 统一团队的开发环境
• 管理语言工具与系统依赖
• 在本地启动 PostgreSQL 和 Redis

将API、数据库和文件处理实现为AI代理可调用的MCP服务器，支持用Python定义工具、本地验证、客户端注册及通过HTTP对外提供服务。

• 让AI代理调用现有API
• 提供SQLite只读查询
• 将文本文件检查与搜索封装为工具

Plan and implement a unified AgentDB memory backend for agents. Migrate SQLite and Markdown data, add HNSW indexing for similarity search, and support shared memory and SONA learning patterns while preserving compatibility with existing systems.

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• Consolidating separate agent memory systems
• Migrating SQLite and Markdown data to AgentDB
• Finding stored information with similar meaning

Plan and implement a unified AgentDB memory backend for agents. Migrate SQLite and Markdown data, add HNSW indexing for similarity search, and support shared memory and SONA learning patterns while preserving compatibility with existing systems.

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• Consolidating separate agent memory systems
• Migrating SQLite and Markdown data to AgentDB
• Finding stored information with similar meaning

Plan a former employee register covering previous roles, departure dates, rehire eligibility, and future contact dates. Receive a simple workflow recommendation, with empty CSV templates, SQL table definitions, JSON Schema, or Notion mappings available on request.

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• Planning a former employee register
• Preparing a template for rehire candidates
• Organizing fields for future contact dates

Plan a 360-degree or peer feedback process and create empty response templates from confirmed requirements. Produces consistent CSV, SQL, JSON Schema, or Notion property mappings while keeping visibility choices and scoring configuration separate.

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• Plan an anonymous peer feedback process
• Create a CSV template for feedback responses
• Align feedback fields across SQL and JSON Schema

Define a practical KPI dashboard, a view of key business measures, by organizing metric definitions, sources, formulas, periods, targets, and owners. Produces empty CSV, SQL, JSON Schema, or Notion import mappings when requested.

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• Choose metrics for a business decision
• Review an overcrowded KPI dashboard
• Create a CSV register of metric definitions

Create integration tests for .NET database access before migrating from Oracle to PostgreSQL. The tests record expected Oracle behavior with controlled test data and portable checks, providing a baseline for later migration validation.

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• Recording Oracle behavior before migration
• Testing repository methods and stored procedure calls
• Checking empty strings, NULL inputs, and datetime precision

Review every project in a .NET solution for Oracle dependencies, classify its migration status, and create a saved PostgreSQL migration plan with a project inventory and an order that prioritizes shared libraries.

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• Planning an Oracle-to-PostgreSQL migration across multiple projects
• Identifying Oracle dependencies in a .NET solution
• Deciding migration order based on project dependencies