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Found 709 Skills
Instrument an existing codebase with LaunchDarkly config tracking. Walks the four-tier ladder (managed runner → provider package → custom extractor + trackMetricsOf → raw manual) and picks the lowest-ceremony option that still captures duration, tokens, and success/error.
Use this skill when integrating, configuring, or extending Modern Admin (`@modern-admin/*`) in a host project — i.e. wiring `ModernAdminModule.forRoot`, adding admin resources, configuring Better Auth/Prisma/Redis, declaring properties or `@Action`/`@Before`/`@After` hooks, setting up role permissions (`MaRole.permissions`), or troubleshooting auth/SPA 404s. Triggers on tasks that mention `@AdminResource`, `AdminController`, `adminSource`, `BetterAuthProvider`, `ModernAdminStaticUiModule`, `setupPrismaSystem`, `MaRole`, `rolesResourceId`, the `ma_*` schema fragment, or scaffolding `bun create @modern-admin`.
Route generative media requests before any creative planning or provider execution. Use this when the user asks to generate, modify, dub, animate, or assemble image, video, audio, workflow, or analysis-derived media and the first decision is which generation controller should own the job.
Build, deploy, and maintain applications on Hugging Face Spaces — Gradio / Docker / Static SDKs, ZeroGPU and dedicated hardware, model loading, debugging, buckets, inference providers, community grants. Use whenever the user asks to create or host an app on Hugging Face, port code onto ZeroGPU, fix a Space that won't build or run, or otherwise work with `hf spaces …`, `@spaces.GPU`, Space README frontmatter, or the `spaces` Python package.
Design multi-cloud architectures using a decision framework to select and integrate services across AWS, Azure, and GCP. Use when building multi-cloud systems, avoiding vendor lock-in, or leveraging best-of-breed services from multiple providers.
Use when customizing gluestack-ui themes and design tokens. Covers theme provider setup, design tokens, dark mode, NativeWind integration, and extending themes.
Build and debug ARKit features for visionOS, including ARKitSession setup, authorization, data providers (world tracking, plane detection, scene reconstruction, hand tracking), anchor processing, and RealityKit integration. Use when implementing ARKit workflows in immersive spaces or troubleshooting ARKit data access and provider behavior on visionOS.
Guide developers integrating EUrouter into their applications. EUrouter is an OpenAI-compatible AI gateway for EU/GDPR compliance. Use when integrating EUrouter, switching from OpenRouter or OpenAI, configuring EU data residency, routing AI requests to EU providers, managing API keys, or asking about EUrouter's API for chat completions, embeddings, streaming, tool calling, vision, model routing, or GDPR compliance features.
React testing best practices using React Testing Library, Vitest, and Jest. Use when writing, reviewing, or generating tests for React components, hooks, context providers, async interactions, or form submissions. Triggers on tasks like "write a test for this component", "add unit tests", "test this hook", "mock this API call", "improve test coverage", or "set up Vitest".
Implement, review, or improve widgets, Live Activities, and controls using WidgetKit and ActivityKit. Use when building home screen, Lock Screen, or StandBy widgets with timeline providers; when creating interactive widgets with Button/Toggle and AppIntent actions; when adding Live Activities with Dynamic Island layouts (compact, minimal, expanded); when building Control Center widgets with ControlWidgetButton/ControlWidgetToggle; when configuring widget families, refresh budgets, deep links, push-based reloads, or Liquid Glass rendering; or when setting up widget extensions, App Groups, and entitlements.
Integrate and optimize Core ML models in iOS apps for on-device machine learning inference. Covers model loading (.mlmodelc, .mlpackage), predictions with auto-generated classes and MLFeatureProvider, compute unit configuration (CPU, GPU, Neural Engine), MLTensor, VNCoreMLRequest, MLComputePlan, multi-model pipelines, and deployment strategies. Use when loading Core ML models, making predictions, configuring compute units, or profiling model performance.
Multimodal UI understanding and single-step planning via OpenAI-compatible Responses APIs. Use when you need AIQuery/AIAssert and plan-next to extract UI element coordinates, validate UI assertions, summarize screenshots, or decide the next UI action from an image. External agents handle execution via adb/hdc and multi-step loops. Defaults to Doubao models but can be pointed at other multimodal providers via base URL, API key, and model name.