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Found 196 Skills
Xcode project setup, SwiftData persistence, testing, debugging, profiling, and app distribution for iOS development. This skill should be used when setting up Xcode projects, working with SwiftData models and queries, writing Swift tests, debugging with breakpoints, profiling with Instruments, distributing via TestFlight, or building for visionOS and ML features.
Process textual and multimedia files with various LLM providers using the llm CLI. Supports both non-interactive and interactive modes with model selection, config persistence, and file input handling.
INVOKE THIS SKILL when your LangGraph needs to persist state, remember conversations, travel through history, or configure subgraph checkpointer scoping. Covers checkpointers, thread_id, time travel, Store, and subgraph persistence modes.
Build durable workflows with Cloudflare Workflows (GA April 2025). Features step.do, step.sleep, waitForEvent, Vitest testing, automatic retries, and state persistence for long-running tasks. Prevents 12 documented errors. Use when: creating workflows, implementing retries, or troubleshooting NonRetryableError, I/O context, serialization errors, waitForEvent timeouts, getPlatformProxy failures.
Use when working with SwiftData - @Model definitions, @Query in SwiftUI, @Relationship macros, ModelContext patterns, CloudKit integration, iOS 26+ features, and Swift 6 concurrency with @MainActor — Apple's native persistence framework
Vector embeddings with HNSW indexing, sql.js persistence, and hyperbolic support. 75x faster with agentic-flow integration. Use when: semantic search, pattern matching, similarity queries, knowledge retrieval. Skip when: exact text matching, simple lookups, no semantic understanding needed.
This skill should be used when users want to train or fine-tune language models using TRL (Transformer Reinforcement Learning) on Hugging Face Jobs infrastructure. Covers SFT, DPO, GRPO and reward modeling training methods, plus GGUF conversion for local deployment. Includes guidance on the TRL Jobs package, UV scripts with PEP 723 format, dataset preparation and validation, hardware selection, cost estimation, Trackio monitoring, Hub authentication, and model persistence. Should be invoked for tasks involving cloud GPU training, GGUF conversion, or when users mention training on Hugging Face Jobs without local GPU setup.
Code generator skills that produce production-ready Swift code for common app components. Use when user wants to add logging, analytics, onboarding, review prompts, networking, authentication, paywalls, settings, persistence, error monitoring, CI/CD pipelines, localization, push notifications, deep linking, testing, accessibility, widgets, or feature flags.
Creates complete single-file HTML/CSS/JS web apps with localStorage persistence, ADHD-optimized UI (60px+ buttons), dark mode, and offline functionality. Use when user says "create app", "build tool", "make dashboard", or requests any browser-based interface.
Build and maintain assistant-ui based React chat apps with reliable setup, runtime selection, LangGraph wiring, tool UI integration, and upgrade workflows. Use when tasks explicitly involve `assistant-ui` dependencies or APIs, including `assistant-ui` CLI commands (`create/init/add/update/upgrade/codemod`), `@assistant-ui/*` providers/runtimes, `AssistantRuntimeProvider`, Thread/Composer primitives, cloud persistence, or tool rendering behavior. Do not use for generic React chat work, backend-only LangGraph tasks, or non-assistant-ui UI work. If the prompt explicitly says without/no/not assistant-ui, do not trigger this skill.
Develop native iOS apps with Swift. Covers MVVM architecture, SwiftUI, URLSession for networking, Combine for reactive programming, and Core Data persistence.
This skill should be used when users want to run any workload on Hugging Face Jobs infrastructure. Covers UV scripts, Docker-based jobs, hardware selection, cost estimation, authentication with tokens, secrets management, timeout configuration, and result persistence. Designed for general-purpose compute workloads including data processing, inference, experiments, batch jobs, and any Python-based tasks. Should be invoked for tasks involving cloud compute, GPU workloads, or when users mention running jobs on Hugging Face infrastructure without local setup.