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Found 911 Skills
Create and configure WPF TileView controls for organizing and displaying content in tile layouts. Use this skill whenever users need to implement tile-based layouts, arrange tiles in matrix positions, add drag-drop functionality to tiles, maximize/minimize tile items, customize tile headers and appearance, bind data to tile views, or create responsive dashboard-like layouts. Essential for building WPF applications with interactive tiled interfaces.
Guide for implementing Syncfusion WinUI DropDown Color Picker control for interactive color selection with dropdown functionality. Use this skill when implementing color selection with dropdown, color editing modes (RGB/HSV/HSL/CMYK/Hex), customizable dropdown placement, split button modes, or color picker flyout customization in WinUI applications.
Guide implementation of the Syncfusion WinUI DropDown Color Palette control for color selection in Windows desktop applications. Use this skill when implementing color selection dropdowns, theme color support, custom color palettes, split-mode buttons, or the More Colors dialog. Covers dropdown customization, palette structure, and color-based UI interactions.
Guide implementation of the Syncfusion WinUI AutoComplete control (SfAutoComplete) for creating searchable dropdowns with single or multiple selection, filtering suggestions, and customizable token display. Use this skill when implementing search-as-you-type functionality, autocomplete dropdowns with multi-select, tagging systems with token/chip display, or filtered suggestion boxes in WinUI applications.
Implement Syncfusion WinForms GradientLabel control - an enhanced label with gradient backgrounds and custom borders. Use this when creating visually styled labels, colorful headers, or decorative text displays. Covers gradient effects, custom borders, shading configuration, and appearance customization for attractive label designs in Windows Forms applications.
Generate pixel-art self-portrait, profile card, emoji GIFs, and meme stickers. Use when: "生成形象"、"画头像"、"avatar"、"self-portrait"、"表情包"、"梗图"、"贴纸"、"sticker"、"换一个"、"重新生成"、"不喜欢"、"regenerate". Also use when: Cola wakes up — display existing avatar or prompt user to generate. Do NOT use when: discussing third-party platform avatar settings or searching for external stickers.
Guide for implementing Syncfusion Blazor ProgressBar components in Blazor applications. Use this when displaying progress indicators, loading states, task completion status, or file upload progress. This skill covers linear and circular progress bars, indeterminate loaders, buffer states, and progress tracking. Ideal for visual feedback during operations, showing completion percentages, and any scenario requiring visual progress indicators.
WireGuard VPN server setup, peer configuration, key generation, split tunneling vs full tunnel routing, and remote access to a home network from mobile and laptop clients.
API reference: Core Animation (QuartzCore). Query for CALayer, CAAnimation, CABasicAnimation, CAKeyframeAnimation, CASpringAnimation, CATransaction, CAShapeLayer, CAGradientLayer, CAEmitterLayer, CATransform3D, CADisplayLink.
Programmatic hunk selection for Jujutsu — split, commit, or squash specific hunks without interactive prompts. Use when making partial commits or selective squashes.
For use when students **have completed WG-12 to WG-21** (single-file consolidation blueprint) and are working on **WG-22 Code Splitting** (`agent_core.py` + `main.py`). **First message in a new session**: Display PEAS brand screen and confirm readiness first; after confirmation, **lay out the context** before proceeding to requirement clarification. If **`prompts/` or `templates/`** are missing, copy them from `references/project_assets/` to the project root. Process: Spec Alignment (2d′) → Six-column Contract → **In-session Handoff Implementation** → Acceptance. Starting point: starter_main_wg21.py; Standard reference: reference_agent_core.py + reference_main.py. Triggers: peas-workshop-advanced-coach, PEAS workshop advanced coach, WG-22, code splitting coach, Agent.chat.
Redis LangCache guidance for semantic caching of LLM responses on Redis Cloud — calling search/set via the SDK or REST API, tuning the similarity threshold, separating caches per task type, and filtering with custom attributes. Use when caching LLM completions or RAG answers to cut API cost and latency, building a cache-aside layer in front of OpenAI / Anthropic / etc., tuning hit rate vs precision, or splitting one app's LLM workloads into multiple LangCache caches.