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Found 130 Skills
Comprehensive guide for implementing Syncfusion WPF Sparkline (SfSparkline) controls in Windows Presentation Foundation applications. Use this when working with sparklines, mini charts, or trend visualization. This skill covers sparkline types (line, column, area, WinLoss), markers, track ball, range bands, axis controls, and segment customization for compact data visualization in WPF applications.
Review inbox status across multiple email accounts with per-account breakdown and cross-account priorities.
Morning standup briefing: today's events, unread people and priority mail, and team assignment status.
Process pending calendar invitations: check availability and present a decision list with recommendations.
Find mutual availability with attendees and suggest meeting times.
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.
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.
Meeting manager persona for Spark. Meeting preparation, transcript review, follow-up drafts, and scheduling.
Use when the user wants to brainstorm an idea or design a feature/spec. Explores intent and requirements through dialogue, then writes a spec document to docs/spark/ and STOPS. Does not auto-chain to implementation planning or any other skill.
Analyze lakehouse data interactively using Fabric Livy sessions and PySpark/Spark SQL for advanced analytics, DataFrames, cross-lakehouse joins, Delta time-travel, and unstructured/JSON data. Use when the user explicitly asks for PySpark, Spark DataFrames, Livy sessions, or Python-based analysis — NOT for simple SQL queries. Triggers: "PySpark", "Spark SQL", "analyze with PySpark", "Spark DataFrame", "Livy session", "lakehouse with Python", "PySpark analysis", "PySpark data quality", "Delta time-travel with Spark".
Develop Microsoft Fabric Spark/data engineering workflows with intelligent routing to specialized resources. Provides core workspace/lakehouse management and routes to: data engineering patterns, development workflow, or infrastructure orchestration. Use when the user wants to: (1) manage Fabric workspaces and resources, (2) develop notebooks and PySpark applications, (3) design data pipelines and orchestration, (4) provision infrastructure as code. Triggers: "develop notebook", "data engineering", "workspace setup", "pipeline design", "infrastructure provisioning", "Delta Lake patterns", "Spark development", "lakehouse configuration", "organize lakehouse tables", "create Livy session", "notebook deployment".
Assign emails to teammates with context and track delegation status.