SQL & Databases Agent Skills

Design schemas, write TypeScript functions, and manage real-time data, auth, storage, scheduling, and deployment for Convex backends.

Provides astronomical data analysis capabilities including coordinate transformations, unit conversions, FITS file handling, cosmological calculations, time systems, and table operations.

Write, review, debug, test, and optimize Python Polars code with version-grounded object types, schemas, and execution boundaries.

Write, review, debug, test, or optimize Python code using PyArrow arrays, schemas, tables, compute kernels, datasets, Parquet, and Arrow IPC.

Guides the choice between DuckDB and Polars for each stage of an analytical pipeline, covering Arrow transfer, lazy versus eager execution, registration lifetime, schema conversion, and result ownership.

Query, inspect, and manage Redis databases from the command line using redis-cli, covering connection, data operations, scanning, and server diagnostics.

Audits Convex performance for reads, subscriptions, write contention, and function limits. Use for slow features, insights findings, OCC conflicts, or read amplification.

Query NFT and token data, browse drops, stream events, and search across Ethereum, Base, Arbitrum, Optimism, Polygon, and more using the official CLI, SDK, MCP server, or shell scripts.

Run SQL queries and psql meta-commands against PostgreSQL databases via the psql CLI, with options for file execution, tuples-only output, and timeouts.

Designs a points account system supporting multiple point types, independent expiration times, and FEFO (first-expired-first-out) consumption logic, including database schema, data flow, balance display, and partial consumption handling.

Streams MySQL or MariaDB row-level changes into Redpanda or Kafka via the mysql_cdc input, covering binlog setup, snapshots, checkpointing, per-table routing, AWS RDS IAM auth, and Enterprise lakehouse destinations.

Query external data from Oxla — Kafka topics via catalogs, Apache Iceberg tables, and S3/GCS/Azure parquet/ORC files — alongside native Oxla tables. Use when querying Kafka topics with CREATE KAFKA CATALOG or CREATE REDPANDA CATALOG, reading Apache Iceberg tables with the catalog=>path.table syntax, loading or.

Routes to the right Salesforce data skill package for data model, migration, bulk loads, query optimization, deduplication, and archival tasks.

Provides expert guidance on modern SQL, cloud-native databases, and query optimization, covering performance tuning, data modeling, and hybrid analytical systems.

Provides JPA/Hibernate patterns for Spring Boot data modeling, including entity design, relationships, query optimization, transactions, auditing, indexing, pagination, and connection pooling.

Provides ClickHouse schema design, query optimization, and data ingestion patterns for high-performance analytical workloads.

Provides MySQL and MariaDB schema, query, indexing, transaction, replication, and connection-pool patterns for production backends.

Production patterns and non-obvious traps for Prisma ORM in TypeScript backends, covering schema design, query optimization, transactions, pagination, and serverless connection handling.

Diagnoses and tunes PostgreSQL performance issues such as slow queries, missing indexes, bloat, locks, and connection problems, providing SQL commands and best practices.

Compacts and prunes LanceDB tables in StaticFlow databases to merge fragment files, reduce open file descriptors, and reclaim storage.

Guides database design and operations to avoid common scaling, reliability, and data integrity pitfalls.

Guides OLTP database schema design through six stages: domain and access patterns, entities and relationships, keys and constraints, normalization trade-offs, indexing and performance, and operations and evolution. Includes a final review checklist and tips for effective guidance.

Collects Chinese A-share stock data, fetching stock lists and daily, weekly, and monthly K-line history into a local SQLite database for quantitative analysis.

Performs astronomical data analysis with astropy: coordinate transformations, unit conversions, FITS file handling, cosmological calculations, time systems, tables, and WCS.

Guides database design, implementation, optimization, migration, pipeline development, quality, and operations across SQL and NoSQL platforms.

Generates a personalised nutrition report from consumer genetic data (23andMe, AncestryDNA, VCF) by interrogating nutritionally-relevant SNPs and producing actionable dietary guidance, all computed locally.

Computes phylogenetic distance matrices and trees from genomic VCF or FASTA data using the fastreeR hybrid Java/Python toolkit.

Performs HLA allele genotyping from WGS/WES VCF data, producing a structured markdown report and machine-readable JSON results.

Explains ACID transaction properties and provides Python implementations for atomic operations, consistency validation, isolation levels, and durable storage.

Explains MariaDB-specific SET syntax and behavior, including scope rules, the SET STATEMENT ... FOR extension, and persistence differences from MySQL.

Decodes and replays MariaDB binary logs with correct flags: commented pseudo-SQL vs. executable BINLOG blobs, ANNOTATE_ROWS events, flashback undo SQL, and safe replay via the mariadb client.

Explains MariaDB server-side prepared statements (PREPARE, EXECUTE, DEALLOCATE, EXECUTE IMMEDIATE), including syntax, allowed statements, placeholders, session scope, and restrictions. Use when writing or reviewing dynamic SQL for MariaDB.

Explains MariaDB-specific syntax and behavior for LOAD DATA [LOCAL] INFILE and LOAD XML, including LOCAL vs server-side file handling, security and privilege requirements, default tab/newline parsing, duplicate and strict-mode caveats, IGNORE n LINES, user-variable SET transforms, CHARACTER SET clause, and priority.

Explains MariaDB-specific view syntax and behavior, including CREATE OR REPLACE VIEW, ALGORITHM options, SQL SECURITY, updatability rules, and WITH CHECK OPTION, for writing or reviewing MariaDB view statements.

Documents MariaDB-specific transaction control syntax and behavior, including START TRANSACTION, COMMIT, ROLLBACK, SAVEPOINT, implicit commit rules, autocommit defaults, and idle transaction timeouts.

Explains MariaDB's three CREATE FUNCTION forms — stored functions, stored aggregate functions, and loadable UDFs — covering syntax, privileges, and behavior differences for writing or reviewing MariaDB SQL.