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Found 2,259 Skills
Write, explain, and debug Metal GPU code including shaders (vertex, fragment, compute), render pipelines, compute pipelines, buffer/texture management, and Metal 4 APIs. Use this skill whenever the user mentions Metal, GPU programming, shaders, MSL (Metal Shading Language), render passes, compute kernels, MTLDevice, MTLCommandBuffer, MTLRenderPipelineState, or any Apple GPU/graphics programming topic. Also trigger when the user wants to do parallel computation on Apple devices, write GPU-accelerated code, or work with Metal Performance Shaders, MetalFX, MetalKit, or Compositor Services. Covers iOS, macOS, iPadOS, tvOS, and visionOS.
Optimize Supabase API performance with caching, batching, and connection pooling. Use when experiencing slow API responses, implementing caching strategies, or optimizing request throughput for Supabase integrations. Trigger with phrases like "supabase performance", "optimize supabase", "supabase latency", "supabase caching", "supabase slow", "supabase batch".
Optimize deep learning models using Adam, SGD, and learning rate scheduling to improve accuracy and reduce training time. Use when asked to "optimize deep learning model" or "improve model performance". Trigger with phrases like 'optimize', 'performance', or 'speed up'.
Generate, optimize, and explain SQL queries with best practices. Use when writing database queries or optimizing SQL performance.
This skill analyzes code for design quality improvements across 8 dimensions: Naming, Object Calisthenics, Coupling & Cohesion, Immutability, Domain Integrity, Type System, Simplicity, and Performance. Ensures rigorous, evidence-based analysis by: (1) Understanding code flow first via implementation-analysis protocol, (2) Systematically evaluating each dimension with specific criteria, (3) Providing actionable findings with file:line references. Triggers when users request: code analysis, design review, refactoring opportunities, code quality assessment, architecture evaluation.
Build React components, responsive layouts, and handle state management. Use for UI development, styling, or frontend performance.
Validate production readiness of Vertex AI Agent Engine deployments across security, monitoring, performance, compliance, and best practices. Generates weighted scores (0-100%) with actionable recommendations. Use when asked to "validate deploymen... Trigger with phrases like 'validate', 'check', or 'verify'.
Implement drag and drop using @atlaskit/pragmatic-drag-and-drop. Use when implementing sortable lists, reorderable items, kanban boards, or any drag-drop interactions. Covers draggable setup, drop targets, edge detection, drag previews, and critical state management patterns to avoid performance issues.
C++ Reinforcement Learning best practices using libtorch (PyTorch C++ frontend) and modern C++17/20. Use when: - Implementing RL algorithms in C++ for performance-critical applications - Building production RL systems with libtorch - Creating replay buffers and experience storage - Optimizing RL training with GPU acceleration - Deploying RL models with ONNX Runtime
Provides AWS Lambda integration patterns for TypeScript with cold start optimization. Use when deploying TypeScript functions to AWS Lambda, choosing between NestJS framework and raw TypeScript approaches, optimizing cold starts, configuring API Gateway or ALB integration, or implementing serverless TypeScript applications. Triggers include "create lambda typescript", "deploy typescript lambda", "nestjs lambda aws", "raw typescript lambda", "aws lambda typescript performance".
Build Progressive Web Apps with Next.js: service workers, offline support, caching strategies, push notifications, install prompts, and web app manifest. Use when creating PWAs, adding offline capability, configuring service workers, implementing push notifications, handling install prompts, or optimizing PWA performance. Triggers: PWA, progressive web app, service worker, offline, cache strategy, web manifest, push notification, installable app, Serwist, next-pwa, workbox, background sync.
Generate realistic KPI benchmarks for an influencer campaign before launch based on industry, platform, creator tier, and budget. This skill should be used when setting performance expectations for a creator campaign, estimating reach engagement and conversion benchmarks before launch, building KPI targets for an influencer program, forecasting campaign performance by creator tier and platform, setting EMV and ROAS targets for a campaign brief, defining what good looks like for an upcoming creator activation, calibrating expectations for a gifting or paid campaign across Instagram TikTok or YouTube, or creating a benchmark framework to measure campaign success against. For calculating ROI after a campaign ends, see campaign-roi-calculator. For calculating engagement rates from actual post data, see engagement-rate-calculator-benchmarker. For building a full KPI framework tied to business objectives, see campaign-goal-to-kpi-framework-builder.