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Apple's approach to interface design and fluid, physical motion, translated for the web. Use when building or reviewing gesture-driven UI, spring animations, drag/swipe/sheet interactions, momentum and interruptible transitions, translucent materials and depth, typography (optical sizing, tracking, leading), reduced-motion, or the design foundations (feedback, spatial consistency, restraint) behind Apple-style interfaces.

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Use when a study's materials, data, code, or preprint need an open-science release: license choice, a persistent DOI (Zenodo/OSF), README and metadata, and an access-and-embargo decision that respects ethics constraints.

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Full exploit development course roadmap and syllabus: weekly topics, recommended reading, lab setup, and learning path from vulnerability classes through advanced exploitation. Use to structure exploit dev training or onboard new researchers.

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AI/LLM security offensive checklist: prompt injection, jailbreaking, model extraction, training data poisoning, adversarial inputs, LLM-assisted attack automation, and AI system reconnaissance. Use when assessing AI/ML systems, red-teaming LLMs, or researching AI attack vectors.

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Knowledge and utilities for creating animated GIFs optimized for Slack. Provides constraints, validation tools, and animation concepts. Use when users request animated GIFs for Slack like "make me a GIF of X doing Y for Slack."

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Hugging Face Hub CLI (`hf`) for downloading, uploading, and managing models, datasets, spaces, buckets, repos, papers, jobs, and more on the Hugging Face Hub. Use when: handling authentication; managing local cache; managing Hugging Face Buckets; running or scheduling jobs on Hugging Face infrastructure; managing Hugging Face repos; discussions and pull requests; browsing models, datasets and spaces; reading, searching, or browsing academic papers; managing collections; querying datasets; configuring spaces; setting up webhooks; or deploying and managing HF Inference Endpoints. Make sure to use this skill whenever the user mentions 'hf', 'huggingface', 'Hugging Face', 'huggingface-cli', or 'hugging face cli', or wants to do anything related to the Hugging Face ecosystem and to AI and ML in general. Also use for cloud storage needs like training checkpoints, data pipelines, or agent traces. Use even if the user doesn't explicitly ask for a CLI command. Replaces the deprecated `huggingface-cli`.

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Requires OFOX_API_KEY — create one at https://app.ofox.ai. Generate a realistic-human, dialogue-driven short-drama clip — one shot, or a few hard-cut shots inside one job — from a script or scene description using the Ofox video API (Seedance 2.5). Runs a short creative brief when the input leaves beat, aspect ratio, emotional arc or camera register open (one held take, a travelling take, or a multi-shot cut list) ("Let the AI decide" is offered on the taste questions, never on a must-ask one, and never as the default), writes a structured prompt (header manifest, timestamped shots, quoted dialogue with delivery notes, consistency lock), shows a cost estimate, then calls ofox-video-core to submit, poll, download, and report the real cost. Use when a user asks to turn a script beat into video, e.g. "generate scene 3 of this script, two characters talking, 15 seconds", "make a vertical short-drama clip of these two arguing in a kitchen", "turn this dialogue into a 12-second video", or "give me a realistic short-drama shot of a couple breaking up at a train station". Do not use for silent product/brand shots (see seedance-ad-creative), for anime- or manga-styled scenes (see seedance-anime-drama), for one person addressing the viewer rather than another character — a script read from a supplied portrait is talking-head, an idea pulled out of an article is explainer — or for anything not involving people/dialogue.

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