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Found 739 Skills
Diagnose, compare, and optimize Apache Spark applications and SQL queries using Spark History Server data. Use this skill whenever the user wants to understand why a Spark app is slow, compare two benchmark runs or TPC-DS results, find performance bottlenecks (skew, GC pressure, shuffle spill, straggler tasks), get tuning recommendations, or optimize Spark/Gluten configurations. Also trigger when the user mentions 'diagnose', 'compare runs', 'why is this query slow', 'tune my Spark job', 'benchmark comparison', 'performance regression', or asks about executor skew, shuffle overhead, AQE effectiveness, or Gluten offloading issues.
Guide for using Netlify DB (managed Neon Postgres). Use when the project needs a relational database, structured data storage, SQL queries, or data that will grow over time. Covers provisioning, raw SQL via @netlify/neon, Drizzle ORM integration, migrations, and deploy preview branching. Also covers when to use Netlify Blobs instead.
Expertise in generating clean, correct, and efficient Dataform pipeline code for BigQuery ELT. Use this when creating or modifying Dataform pipelines, actions, or source declarations, when Dataform, SQLX, or BigQuery are mentioned in a transformation, when data needs to be ingested from GCS into BigQuery via Dataform, or when setting up a new Dataform project or configuring workflow_settings.yaml.
Use these skills when you need to explore the database structure, discover schema objects like views or stored procedures, and execute custom SQL queries to interact with your data.
SQLite expert for WAL mode, query optimization, embedded patterns, and advanced features
Oracle Database skills for administration, SQL and PL/SQL development, performance tuning, security, ORDS, SQLcl, migrations, frameworks, Oracle Container Registry guidance, and agent-safe database workflows.
Analyzes and optimizes SQL queries for performance. Use for index design, query rewriting, EXPLAIN/EXPLAIN ANALYZE interpretation, PostgreSQL tuning, N+1 prevention, CTE and window function optimization, join strategies, and common SQL anti-patterns.
Diagnoses and optimises slow SQL queries using EXPLAIN ANALYZE. Covers identifying bottlenecks (sequential scans, bad estimates, heap fetches), index strategy, query rewrites, and verification. Invoked when the user asks to optimize a query, fix a slow database query, or improve database performance.
Connect SaaS data (HubSpot, Stripe, Salesforce, GitHub, Slack, etc.) to Wren Engine for SQL analysis. Guides the user through the full flow: install dlt, pick a SaaS source, set up credentials, run the data pipeline into DuckDB, then auto-generate a Wren semantic project from the loaded data. Use this skill whenever the user mentions: connecting SaaS data, importing data from an API, dlt pipelines, loading HubSpot/Stripe/Salesforce/GitHub/Slack data, querying SaaS data with SQL, or setting up a new data source from a REST API. Also trigger when the user already has a dlt-produced DuckDB file and wants to create a Wren project from it.
Translates natural language data intents into syntactically valid Perfetto SQL queries and executes them against a local trace file. Use this skill to extract slice, thread, or memory data from Android Perfetto traces using trace_processor.
PreToolUse security-anti-pattern hook for Claude Code. Catches 12 common security risks (command injection, XSS, SQL injection, unsafe deserialization, GitHub Actions workflow injection, eval/new Function code injection) BEFORE the Edit/Write/MultiEdit operation completes. Session-state caching prevents duplicate warnings on the same file+rule combo. Stdlib only — no dependencies. Use when you want a safety net during Claude Code sessions that touch security-sensitive code (auth, payments, user input handling, IaC). Disable with ENABLE_SECURITY_REMINDER=0 if you need to perform a verified-safe operation that would otherwise trip a pattern. Triggers — "add security hook", "block unsafe code", "detect command injection before write", "prevent SQL injection patterns", "security warning hook".
Build ETL pipelines and analytics dashboards for Harvard Art Museums API data using Python, SQL, and Streamlit