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Found 280 Skills
Analyze disk images and file systems for forensic investigation. Use when investigating data theft, insider threats, malware persistence, deleted file recovery, or any incident requiring analysis of storage media. Supports NTFS, FAT, EXT, HFS+, and APFS file systems.
This skill provides expert-level guidance for implementing VS Code WebView features. Use when creating WebView panels, implementing secure CSP policies, handling Extension-WebView communication, managing WebView state persistence, optimizing WebView performance, or debugging WebView rendering issues. Covers security best practices, message protocols, and VS Code-specific WebView patterns.
Writes Pest feature tests for Laravel HTTP controllers using repeatable controller-test patterns across web/session and API/JSON flows. Activates when creating or updating controller tests, nested resource route tests at any depth, CRUD action tests (create, destroy, edit, index, show, store, update), authorization and route-binding scope checks, validation datasets, transport-specific response assertions, and database persistence assertions.
Create, read, and manage Feishu tasks with automatic user authorization. Use when you need to create tasks that your user can directly edit, read task lists, manage task details, or check calendar events. Supports automatic token refresh and persistence across sessions. All operations are performed with user identity, ensuring proper permissions.
Advanced window and view management patterns for Electrobun desktop applications. This skill covers multi-window architectures, BrowserView for embedded webviews, window lifecycle management, window orchestration, tab systems, and complex window hierarchies. Use this skill when building applications with multiple windows, implementing browser-like tab interfaces, managing parent-child window relationships, creating floating panels or toolbars, implementing picture-in-picture modes, managing window state persistence across sessions, or building applications that require sophisticated window coordination. Triggers include "multiple windows", "tab system", "BrowserView", "window orchestration", "floating window", "child window", "window state", "window manager", "multi-window app", or discussions about complex window management in Electrobun desktop applications.
Creates repository following Clean Architecture with Protocol in domain layer and Implementation in infrastructure layer. Use when adding new data access layer, creating database interaction, implementing persistence, or need to store/retrieve domain models. Enforces Protocol/ABC pattern with ServiceResult, ManagedResource lifecycle, and proper layer separation. Triggers on "create repository for X", "implement data access for Y", "add persistence layer", or "store/retrieve domain model".
SwiftUI fundamentals for all Apple platforms. Use when building views, navigation, data persistence, or state management with SwiftUI across iOS, macOS, iPadOS, watchOS, visionOS.
Expert blueprint for roguelikes including procedural generation (Walker method, BSP rooms), permadeath with meta-progression (unlock persistence), run state vs meta state separation, seeded RNG (shareable runs), loot/relic systems (hook-based modifiers), and difficulty scaling (floor-based progression). Use for dungeon crawlers, action roguelikes, or roguelites. Trigger keywords: roguelike, procedural_generation, permadeath, meta_progression, seeded_RNG, relic_system, run_state.
Analyze candidate algorithms for time/space complexity, scalability limits, and resource-budget fit (CPU, memory, I/O, concurrency). Use when feasibility depends on input growth or latency/memory constraints and quantitative bounds are required before implementation; do not use for persistence schema or deployment topology decisions.
Build resilient, long-running, multi-step applications with AWS Lambda durable functions with automatic state persistence, retry logic, and orchestration for long-running executions. Covers the critical replay model, step operations, wait/callback patterns, error handling with saga pattern, testing with LocalDurableTestRunner. Triggers on phrases like: lambda durable functions, workflow orchestration, state machines, retry/checkpoint patterns, long-running stateful Lambda functions, saga pattern, human-in-the-loop callbacks, and reliable serverless applications.
Trains and fine-tunes vision models for object detection (D-FINE, RT-DETR v2, DETR, YOLOS), image classification (timm models — MobileNetV3, MobileViT, ResNet, ViT/DINOv3 — plus any Transformers classifier), and SAM/SAM2 segmentation using Hugging Face Transformers on Hugging Face Jobs cloud GPUs. Covers COCO-format dataset preparation, Albumentations augmentation, mAP/mAR evaluation, accuracy metrics, SAM segmentation with bbox/point prompts, DiceCE loss, hardware selection, cost estimation, Trackio monitoring, and Hub persistence. Use when users mention training object detection, image classification, SAM, SAM2, segmentation, image matting, DETR, D-FINE, RT-DETR, ViT, timm, MobileNet, ResNet, bounding box models, or fine-tuning vision models on Hugging Face Jobs.
Use when a migration is already known to stay on the LangGraph orchestration side, including stages, routing, checkpoints, interrupts, persistence, streaming, and subgraph boundaries.