Total 50,396 skills, AI & Machine Learning has 8470 skills
Showing 12 of 8470 skills
Create and modify NeMo AutoModel training and evaluation recipes, including YAML structure, builders, and execution flow.
After solving a non-trivial problem, detect generalizable learnings and propose skill updates. Always active — applies to every interaction.
Google Agent Development Kit (ADK) for Python. Capabilities: AI agent building, multi-agent systems, workflow agents (sequential/parallel/loop), tool integration (Google Search, Code Execution), Vertex AI deployment, agent evaluation, human-in-the-loop flows. Actions: build, create, deploy, evaluate, orchestrate AI agents. Keywords: Google ADK, Agent Development Kit, AI agent, multi-agent system, LlmAgent, SequentialAgent, ParallelAgent, LoopAgent, tool integration, Google Search, Code Execution, Vertex AI, Cloud Run, agent evaluation, human-in-the-loop, agent orchestration, workflow agent, hierarchical coordination. Use when: building AI agents, creating multi-agent systems, implementing workflow pipelines, integrating LLM agents with tools, deploying to Vertex AI, evaluating agent performance, implementing approval flows.
Expert in photo content recognition, intelligent curation, and quality filtering. Specializes in face/animal/place recognition, perceptual hashing for de-duplication, screenshot/meme detection, burst photo selection, and quick indexing strategies. Activate on 'face recognition', 'face clustering', 'perceptual hash', 'near-duplicate', 'burst photo', 'screenshot detection', 'photo curation', 'photo indexing', 'NSFW detection', 'pet recognition', 'DINOHash', 'HDBSCAN faces'. NOT for GPS-based location clustering (use event-detection-temporal-intelligence-expert), color palette extraction (use color-theory-palette-harmony-expert), semantic image-text matching (use clip-aware-embeddings), or video analysis/frame extraction.
Use this skill when building applications with Gemini models, Gemini API, working with multimodal content (text, images, audio, video), implementing function calling, using structured outputs, or needing current model specifications. Covers SDK usage (google-genai for Python, @google/genai for JavaScript/TypeScript), model selection, and API capabilities.
Mine ALL past Claude conversations to build a living 'User Manual About You'. Extract writing style, business context, goals, preferences, and patterns. Make all other skills smarter with context.
Create and edit videos using Google's Veo 2 and Veo 3 models. Supports Text-to-Video, Image-to-Video, Reference-to-Video, Inpainting, and Video Extension. Available parameters: prompt, image, mask, mode, duration, aspect-ratio. Always confirm parameters with the user or explicitly state defaults before running.
Xiaohongshu End-to-End Content Workflow: From data collection to AI analysis to content generation, using the Kimi K2 model. Supports web crawling, analysis, note generation, and AI image prompt generation.
Lab environment for Claude superpowers
Overview of the Blockbench MCP server tools, resources, and prompts. Use to understand the full MCP capability set, learn how tools work together, or when starting a new Blockbench project. Covers all domains (modeling, animation, texturing, PBR, UI, camera) and their MCP interfaces.
Skill converted from mcp-create-adaptive-cards.prompt.md
Generate a complete MCP server implementation optimized for Copilot Studio integration with proper schema constraints and streamable HTTP support