Total 50,503 skills, AI & Machine Learning has 8478 skills
Showing 12 of 8478 skills
Comprehensive research and synthesis agent specializing in multi-source information gathering, critical analysis, and integrated knowledge synthesis. Excels at complex research projects requiring systematic investigation across domains, evidence evaluation, and coherent narrative construction.
Analyze the current session and propose improvements to skills. **Proactively invoke this skill** when you notice user corrections after skill usage, or at the end of skill-heavy sessions. Also use when user says "reflect", "improve skill", or "learn from this".
Creates professional AI image/video prompts with photographer's and cinematographer's eye. Specializes in composition, lighting, color grading, and storytelling. Use when generating AI images/videos with artistic vision, working with models like Nano Banana Pro, Qwen, Sora2, Wan 2.2. For graphic design work (thumbnails, banners, layouts), use /graphic-designer instead.
After the task execution is completed, prompt the user to open a new Agent to review the uncommitted git code. Athletes should not act as referees; proceed with the wrap-up only after the review is approved.
LLM observability platform for tracing, evaluation, prompt management, and cost tracking. Use when setting up Langfuse, monitoring LLM costs, tracking token usage, or implementing prompt versioning.
Expert prompt engineering for LLM applications including prompt design, optimization, RAG systems, agent architectures, and AI product development.
Expert ML engineering covering model development, MLOps, feature engineering, model deployment, and production ML systems.
This skill provides reusable implementation patterns extracted from the better-chatbot project for custom AI chatbot deployments. Use this skill when building AI chatbots with server action validators, tool abstraction systems, workflow execution, or multi-AI provider integration in your own projects (not contributing to better-chatbot itself). Use when: building AI chatbot features, implementing server action validators, creating tool abstraction layers, setting up multi-AI provider support, building workflow execution systems, adapting better-chatbot patterns to custom projects Keywords: AI chatbot patterns, server action validators, tool abstraction, multi-AI providers, workflow execution, MCP integration, validated actions, tool type checking, Vercel AI SDK patterns, chatbot architecture
Use to maintain context across sessions - integrates episodic-memory for conversation recall and mcp__memory knowledge graph for persistent facts
Amazon Bedrock AgentCore multi-agent orchestration with Agent-to-Agent (A2A) protocol. Supervisor-worker patterns, agent collaboration, and hierarchical delegation. Use when building multi-agent systems, orchestrating specialized agents, or implementing complex workflows.
Deep analysis and investigation
Token-efficient model routing modifier