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Found 312 Skills
Expert prompt engineering for Seedance 2.0. Use when the user wants to generate a video with multimodal assets (images, videos, audio) and needs the best possible prompt.
This skill should be used when working with single-cell omics data analysis using scvi-tools, including scRNA-seq, scATAC-seq, CITE-seq, spatial transcriptomics, and other single-cell modalities. Use this skill for probabilistic modeling, batch correction, dimensionality reduction, differential expression, cell type annotation, multimodal integration, and spatial analysis tasks.
Use the Gemini API (Nano Banana image generation, Veo video, Gemini TTS speech and audio understanding) to deliver end-to-end multimodal media workflows and code templates for "generation + understanding".
Google Gemini API with @google/genai SDK. Use for multimodal AI, thinking mode, function calling, or encountering SDK deprecation warnings, context errors, multimodal format errors.
Practical guidance for training MoE VLMs in Megatron Bridge. Compares FSDP and 3D-parallel approaches, using rounded lessons from Qwen3-VL, Qwen3-Next, and other multimodal experiments.
Use the mm CLI to index, explore, query, and extract content from multimodal directories containing images, videos, PDFs, code, and other files. Triggers: exploring a directory's contents, listing/finding files by type or size, extracting text from PDFs, getting image metadata, searching across file contents, counting tokens, viewing directory trees, extracting PDF page mosaics, video keyframe extraction, 'what files are in this folder', 'find all images', 'show me the PDFs', 'how much storage do videos use', 'extract text from this PDF', 'search documents for X', 'analyze this directory', 'how many tokens', 'show the tree'.
Vision-language pre-training framework bridging frozen image encoders and LLMs. Use when you need image captioning, visual question answering, image-text retrieval, or multimodal chat with state-of-the-art zero-shot performance.
Provider-agnostic, type-safe AI SDK for streaming, tool calling, structured output, and multimodal content.
Provides image recognition capabilities for non-multimodal models (such as pure text models like deepseek-v4-pro, GLM-5.1, mimo-v2.5-pro, etc.). This skill is automatically triggered when the main model cannot recognize images, when users send screenshots/design drafts/UI screenshots for analysis, or when users say 'Look at this image', 'Analyze this screenshot', 'What's wrong with this image'. It also applies to any scenario where users paste images but the current model does not support image input. Supports simultaneous recognition of multiple images, with primary-backup fallback achieved by configuring multiple image recognition models. It can also be manually triggered using the commands /skill:vision-support or /vision. Iron Rule: The models configured for this skill are only used for image content recognition and will never participate in main logical reasoning. Note: If the current model is itself a multimodal model (such as Claude Sonnet 4, GPT-4o, Gemini, etc. that can directly recognize images), do not use this skill; let the main model recognize directly.
The meta skill. Turn any raw feature into a properly-skilled, tested, resolvable unit of agent capability. Cross-modal eval is the recommended Phase 3 quality gate: 3 frontier models from different providers critique the output, you iterate to quality, THEN write tests that lock in the proven-good behavior.
Execute Google Gemini CLI for large-context code analysis, multimodal reasoning, and repository-scale reviews. Also use for delegating tasks requiring 1M token context windows or Gemini-specific capabilities.
Generate text content using Google Gemini models via scripts/. Use for text generation, multimodal prompts with images, thinking mode for complex reasoning, JSON-formatted outputs, and Google Search grounding for real-time information. Triggers on "generate with gemini", "use gemini for text", "AI text generation", "multimodal prompt", "gemini thinking mode", "grounded response".