Loading...
Loading...
Found 117 Skills
Apply Web Scraping with Python practices (Ryan Mitchell). Covers First Scrapers (Ch 1: urllib, BeautifulSoup), HTML Parsing (Ch 2: find, findAll, CSS selectors, regex, lambda), Crawling (Ch 3-4: single-domain, cross-site, crawl models), Scrapy (Ch 5: spiders, items, pipelines, rules), Storing Data (Ch 6: CSV, MySQL, files, email), Reading Documents (Ch 7: PDF, Word, encoding), Cleaning Data (Ch 8: normalization, OpenRefine), NLP (Ch 9: n-grams, Markov, NLTK), Forms & Logins (Ch 10: POST, sessions, cookies), JavaScript (Ch 11: Selenium, headless, Ajax), APIs (Ch 12: REST, undocumented), Image/OCR (Ch 13: Pillow, Tesseract), Avoiding Traps (Ch 14: headers, honeypots), Testing (Ch 15: unittest, Selenium), Parallel (Ch 16: threads, processes), Remote (Ch 17: Tor, proxies), Legalities (Ch 18: robots.txt, CFAA, ethics). Trigger on "web scraping", "BeautifulSoup", "Scrapy", "crawler", "spider", "scraper", "parse HTML", "Selenium scraping", "data extraction".
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 — type-safe, lightweight TypeScript ORM for SQL databases. Schema declaration, CRUD queries, joins, relations, migrations with Drizzle Kit, and database seeding. Use when defining database schemas, writing queries (select/insert/update/delete), setting up migrations, configuring drizzle.config.ts, establishing database connections, validating data with drizzle-zod/valibot, or working with PostgreSQL, MySQL, SQLite, Turso, Bun SQL, Neon, Supabase, PGlite, Expo SQLite, Cloudflare D1, PlanetScale, SingleStore, MSSQL, CockroachDB.
Use when deploying a database to Zeabur. Use when user needs MySQL, PostgreSQL, MongoDB, or Redis. Use when user says "I need a database", "add database", "deploy postgres", "set up MySQL", "add Redis", "add MongoDB", or "connect to database". Also use when user mentions data persistence issues like "data lost after restart", "data not saved", "data disappears", "need persistent storage for data", or "how to persist data". Also use when integrating a database with an existing service.
Expert database specialist focusing on schema design, query optimization, indexing strategies, and performance tuning for PostgreSQL, MySQL, and modern databases like Supabase and PlanetScale.
Expert-level SQL database design, querying, optimization, and administration across PostgreSQL, MySQL, and SQL Server
Better Auth — framework-agnostic TypeScript authentication & authorization library. Covers setup, email/password, social OAuth (40+ providers), passkeys, magic links, 2FA, organizations, sessions, plugins, admin, hooks, and security hardening. Use when implementing auth with Better Auth: configuring auth instances, adding providers, setting up database adapters (Prisma, Drizzle, PostgreSQL, MySQL, SQLite, MongoDB), integrating with frameworks (Next.js, Nuxt, SvelteKit, Astro, Hono, Express, Elysia, Fastify, Expo), managing sessions, or extending with plugins.
This skill should be used when the user asks to "connect to MySQL with PyMySQL", "use PyMySQL in Python", "query a MySQL database with Python", "set up PyMySQL", or needs guidance on PyMySQL best practices, transactions, parameterized queries, or cursor types.
Design partition schemes, select partition keys, create GSI, and write SQL for PolarDB-X 2.0 Enterprise Edition AUTO mode databases, handling PolarDB-X vs MySQL differences (partitioned tables, GSI, CCI, Sequence, table groups, TTL, pagination, etc.). Use when designing partition schemes, selecting partition keys, converting single tables to partitioned tables, creating GSI/CCI indexes, writing or migrating SQL for PolarDB-X, or diagnosing slow queries on PolarDB-X. Triggers: "PolarDB-X SQL", "PolarDB-X create table", "partitioned table", "partition design", "partition scheme", "partition key", "GSI", "CCI", "Sequence", "MySQL migrate to PolarDB-X", "PolarDB-X compatibility", "single table to partitioned table", "convert to partitioned table", "large table", "distributed table", "AUTO mode", "pagination query", "Keyset pagination", "Range partition", "auto add partition", "PolarDB-X slow query", "full-shard scan"
Add a Docker dev service to this project. Supported services: Redis, RabbitMQ, PostgreSQL, MySQL/MariaDB, MongoDB. Writes Docker Compose and Taskfile configs to .devtools/.
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.
Manage serverless MySQL databases and branches on PlanetScale