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Found 860 Skills
Guides efficient Haskell aligned with GHC practice -- laziness and strictness, purity, fusion, newtypes, pragmas, Core reading, and space-leak avoidance. Use when writing or reviewing Haskell, optimizing or profiling, debugging strictness or memory, or when the user mentions GHC, thunks, foldl vs foldl', list fusion, SPECIALIZE, or UNPACK.
Track and visualize ML training experiments with Trackio. Use when logging metrics during training (Python API), firing alerts for training diagnostics, or retrieving/analyzing logged metrics (CLI). Supports real-time dashboard visualization, alerts with webhooks, HF Space syncing, and JSON output for automation.
Query a running Apache Spark History Server from Copilot CLI. Use this whenever the user wants to inspect SHS applications, jobs, stages, executors, SQL executions, environment details, or event logs, especially when they mention Spark History Server, SHS, event log history, benchmark runs, or application IDs.
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.
Use when adding authentication to Vanilla JS, Svelte, or any framework-agnostic single-page applications - integrates @auth0/auth0-spa-js SDK for SPAs without framework-specific wrappers
Apache Spark, Hadoop, distributed computing, and large-scale data processing for petabyte-scale workloads
Run the SPARC Architecture and Implementation phases — design module boundaries, write pseudocode, implement code, and run tests
Process inbox in priority order by Spark's smart categories: priority first, then people, invites, notifications, newsletters.
Implement Syncfusion Blazor Sparkline Charts for compact, inline trend visualizations in Blazor applications. Use this when creating mini charts, KPI indicators, dashboard sparklines, or word-sized data visualizations. This skill covers line, area, column, WinLoss, and pie sparklines, including data labels, markers, special points (high/low/negative), range bands, tooltips, and appearance customization. Ideal for dashboards, data tables with inline trends, email reports, and mobile data visualization scenarios requiring compact trend indicators.
Implement Syncfusion React Sparkline components for compact, inline data visualization. Use this when working with sparklines, mini charts, or trend indicators in constrained spaces. This skill covers all 5 sparkline types (line, column, area, win-loss, pie), tooltips, markers, data labels, range bands, axis customization, and themes. Ideal for displaying data trends within grids, dashboards, or tables without full-sized charts.
Map scRNA-seq atlases onto spatial transcriptomics slides using omicverse's Single2Spatial workflow for deep-forest training, spot-level assessment, and marker visualisation.
State machines using Spatie Model States for complex state transitions. Use when working with complex state management, state transitions, or when user mentions state machines, Spatie Model States, state transitions, transition validation.