Total 43,803 skills, AI & Machine Learning has 6989 skills
Showing 12 of 6989 skills
Coordinate parallel feature development with file ownership strategies, conflict avoidance rules, and integration patterns for multi-agent implementation. Use this skill when decomposing features for parallel development, establishing file ownership boundaries, or managing integration between parallel work streams.
SPARC (Specification, Pseudocode, Architecture, Refinement, Completion) comprehensive development methodology with multi-agent orchestration
Upscale and enhance image resolution using AI. Use when the user requests "Upscale image", "Enhance resolution", "Make image bigger", "Increase quality", or similar upscaling tasks.
US Stock Investment Research Assistant. Supports Gemini Deep Research or Claude Native Deep Research (7-Phase + GoT). Use when analyzing 10-K/10-Q reports or generating investment research reports.
Expert-level manufacturing systems, Industry 4.0, production optimization, quality control, and smart factory solutions
Retrieval-augmented generation (RAG) skill for the D&D 5e System Reference Document (SRD). Use when answering questions about D&D 5e core rules, spells, combat, equipment, conditions, monsters, and other SRD content. This skill provides agentic search-based access to the SRD split into page-range markdown files.
McKinsey Consultant-style Problem Solving System. Starting from business problems, it generates McKinsey-style research reports and PPTs through hypothesis-driven structured analysis methods. It integrates Problem Solving methodology, MECE principles, Issue Tree decomposition, Hypotheses formulation, Dummy Page design, intelligent data collection, and professional PPT generation capabilities.
MiniMax TTS API - Text-to-Speech, Voice Cloning, Voice Design
Analyze product screenshots to extract feature lists and generate development task checklists. Use when: (1) Analyzing competitor product screenshots for feature extraction, (2) Generating PRD/task lists from UI designs, (3) Batch analyzing multiple app screens, (4) Conducting competitive analysis from visual references.
Model Context Protocol (MCP) server implementation patterns with LangChain4j. Use when building MCP servers to extend AI capabilities with custom tools, resources, and prompt templates.
Model Context Protocol (MCP) server implementation patterns with Spring AI. Use when building MCP servers to extend AI capabilities with custom tools, resources, and prompt templates using Spring's official AI framework.
Amazon Bedrock patterns using AWS SDK for Java 2.x. Use when working with foundation models (listing, invoking), text generation, image generation, embeddings, streaming responses, or integrating generative AI with Spring Boot applications.