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Found 1,138 Skills
Manage the full lifecycle of Alibaba Cloud EMR Serverless Spark workspaces—create workspaces, submit jobs, Kyuubi interactive queries, resource queue scaling, and status queries. Use this Skill when users want to create Spark workspaces, submit Spark jobs, view job status and logs, execute SQL via Kyuubi, scale resource queues, or view workspace status. Also applicable when users say "create a Spark workspace", "submit Spark job", "run PySpark", "execute SQL via Kyuubi", "scale resource queue", "view job logs", etc.
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.
Reading coach: guides users through books systematically with knowledge compilation, mastery testing, spaced repetition, and knowledge querying. Use when user says 'read this book with me', 'book study', 'start studying X', 'reading plan', 'ingest this chapter', 'review what I read', 'quiz me on the book', 'what did the book say about X', or invokes /book-study. Supports sub-commands: ingest, query, review, compare, status. Triggers: book, study, read, chapter, ingest, review, quiz, reading plan, book notes.
Migrate Databricks workloads from classic compute to serverless compute. Scans code for serverless compatibility issues, provides concrete fixes for the serverless Spark Connect architecture, and guides the full migration to serverless environments. Use for classic-to-serverless migrations, serverless code compatibility checks, or writing new serverless-compatible notebooks and jobs. Not for classic DBR version upgrades or cluster configuration changes within classic compute.
Run the SPARC Refinement and Completion phases — review code, improve test coverage, validate against specification, and generate documentation
Process inbox in priority order by Spark's smart categories: priority first, then people, invites, notifications, newsletters.
Implement Syncfusion Angular Sparkline component for compact data visualization. Use this skill whenever the user needs to create sparkline charts, visualize small datasets inline, add markers or data labels, implement different sparkline types (Line, Column, Area, Pie, Win-Loss), or handle sparkline customization like tooltips, axis settings, and theme styling. Covers installation, basic rendering, type selection, marker configuration, data label formatting, advanced features, accessibility, and migration from EJ1.
Sales rep / account manager persona for Spark. Client relationship tracking, pipeline review, follow-up cadence, and deal context.
Use when an SPA or SSR app flashes the wrong UI before client-side data resolves — an app-shell skeleton shown to visitors who get bounced to login, a results skeleton before "no results found", a light-theme flash before dark mode, a generic placeholder that swaps to something jarringly different. Covers resolving state at the edge/server, optimistic hint cookies, redirect-back (returnTo) flows, and how to test the loading window.
SOTA Computer Vision Expert (2026). Specialized in YOLO26, Segment Anything 3 (SAM 3), Vision Language Models, and real-time spatial analysis.
Generates Anki flashcards in TSV format from source material using spaced repetition best practices. Supports Basic, Reversed (bidirectional), and Cloze card types with configurable quantity and difficulty. Use when generating flashcards, creating Anki cards, making study cards, converting notes to flashcards, turning a transcript into flashcards, or building a spaced repetition deck.
Comprehensive guide to Spark Structured Streaming for production workloads. Use when building streaming pipelines, implementing real-time data processing, handling stateful operations, or optimizing streaming performance.