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Found 244 Skills
Master metaphysics and ontology - the study of being, existence, and fundamental reality. Use for: existence, being, substance, identity, causation, modality, time, universals. Triggers: 'ontological', 'metaphysical', 'what exists', 'substance', 'essence', 'existence', 'being', 'identity', 'persistence', 'causation', 'modality', 'possible worlds', 'universals', 'particulars', 'properties', 'abstract objects', 'time', 'change', 'composition'.
When the user wants to add, optimize, or audit popups or modals for lead capture or offers. Also use when the user mentions "popup," "modal," "lightbox," "overlay," "exit-intent," "popup form," "modal design," "lead popup," "popup timing," or "popup triggers."
Use Transformers.js to run state-of-the-art machine learning models directly in JavaScript/TypeScript. Supports NLP (text classification, translation, summarization), computer vision (image classification, object detection), audio (speech recognition, audio classification), and multimodal tasks. Works in Node.js and browsers (with WebGPU/WASM) using pre-trained models from Hugging Face Hub.
Use TRIBE v2, Meta's multimodal foundation model for predicting fMRI brain responses to video, audio, and text stimuli
Use when connecting to a self-hosted memory backend, searching, storing, or managing memories, importing connection tokens, or troubleshooting retrieval issues. Use this skill whenever the user mentions memory search, RAG retrieval, embedding, memory storage, multimodal document upload, knowledge queries, or wants to connect to a memory service, even if they do not explicitly say "transcendence-memory".
Build a chat list page with search, rename, and delete functionality. Uses nuqs for URL-synced filters and deep-linkable modal dialogs.
Loading and using pretrained models with Hugging Face Transformers. Use when working with pretrained models from the Hub, running inference with Pipeline API, fine-tuning models with Trainer, or handling text, vision, audio, and multimodal tasks.
Official skill for integrating Firebase AI Logic (Gemini API) into web applications. Covers setup, multimodal inference, structured output, and security.
Invokes Google Gemini models for structured outputs, multi-modal tasks, and Google-specific features. Use when users request Gemini, structured JSON output, Google API integration, or cost-effective parallel processing.
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.
Provider-agnostic, type-safe AI SDK for streaming, tool calling, structured output, and multimodal content.
Expert skill for using HY-World 2.0, Tencent's multi-modal world model for reconstructing, generating, and simulating 3D worlds from text, images, and video.