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Route code changes and SQL analysis to isolated Kortix work sessions with clear requirements and workspace details. Coordinate parallel investigations or independent pull request reviews, then summarize deliverables, verification results, and differences between findings.
Design or extend DataFusion benchmarks using SQL where practical. Select representative workload variations, keep unrelated processing lightweight, and integrate runs with bench.sh so measurements reflect useful execution paths and remain practical to run.
Advises on Amazon RDS open-source engines (MySQL, MariaDB, PostgreSQL) for instance creation, upgrade planning, commitment pricing, proxy evaluation, and Blue/Green deployments. Handles any RDS MySQL, MariaDB, or PostgreSQL question, including create a production-ready RDS MySQL instance, provision an RDS PostgreSQL database, run the RDS upgrade advisor for my RDS MySQL instance, what are my upgrade options, upgrade RDS MariaDB from 10.6 to the latest version, should I buy reserved instances or a savings plan for db.r7g.2xlarge RDS MySQL, change a VARCHAR to INT column on RDS MySQL 8.0 with Blue/Green, and does RDS Proxy help when PgBouncer already runs in transaction mode. Covers instance creation with production best practices, describe-db-instances and describe-db-engine-versions upgrade-target workflow, live prechecks via SSM or direct connection, RI versus DSP commitment pricing, RDS Proxy versus PgBouncer, and Blue/Green lifecycle with binlog replay compatibility.
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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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Use when the user wants to run SQL - especially analytical SQL - on local files (parquet/csv/json), URLs, S3 paths, or remote databases (Postgres, MySQL, MongoDB, ClickHouse Cloud, Iceberg, Delta Lake) without setting up a server. Provides chDB - embedded ClickHouse SQL in Python with 1000+ functions, Session for stateful multi-step pipelines, parametrized queries, and cross-source joins via `s3()`, `mysql()`, `postgresql()`, `iceberg()`, `deltaLake()`, `remoteSecure()` table functions. TRIGGER when: user wants SQL on parquet/csv/files or across remote analytical sources; uses ClickHouse SQL features (window functions, windowFunnel, geoToH3, JSON path ops, Session, parametrized queries); imports `chdb` or calls `chdb.query()`. SKIP this skill for pandas-style DataFrame method-chaining (use chdb-datastore instead) or ClickHouse server administration.
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Detect and exploit SQL injection vulnerabilities using both manual techniques and automated tools. Use this skill when testing web applications for database injection flaws including UNION-based, error-based, blind boolean, blind time-based, and out-of-band SQL injection. Covers WAF bypass, second-order SQLi, authentication bypass, and full database extraction with sqlmap.
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Create a MySQL CDC capture using flowctl with binlog replication. Use when setting up streaming from MySQL, Amazon RDS MySQL, or Aurora MySQL. Use when user says "capture MySQL", "stream from MySQL", "MySQL CDC", "binlog replication", or "connect MySQL to Estuary".
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Handle system backups and restore data from backup files while managing a SQLite database. The skill also covers data export, import, and incremental snapshots, which capture changes since an earlier saved state.
Turn defects found during Oracle-to-PostgreSQL migration into structured bug reports. Document expected and actual behavior, reproduction steps, severity, root causes, proposed changes, and validation on both databases so teams can act on the findings.
Work with BigQuery to create datasets and tables, run SQL queries, ingest data, and manage processing jobs. The skill also covers connections to BigQuery ML and Gemini for machine learning and AI analysis.
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.
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.
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.
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.
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, DTU/capacity limits, Key Vault/MI security, or Blob backups, 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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Review Perl code that handles user input, files, external commands, databases, and web output. Use concrete examples and a security checklist to identify unsafe patterns and apply input validation, parameterized queries, and appropriate output encoding.