Discover research llm ai skills, compare source repositories and read the instructions for each workflow.
Performs comprehensive data analysis including statistical analysis, visualization, pattern detection, and report generation. Use when the user asks to analyze data, find patterns, generate insights, create vis...
Analyzes customer behavior, needs, pain points, and sentiment through review mining, social listening, buyer persona development, and jobs-to-be-done framework. Use when the user requests customer analysis, voi...
NVIDIA NeMo framework for building and training conversational AI models. Use for NeMo Retriever models, RAG (Retrieval-Augmented Generation), embedding models, enterprise search, and multilingual retrieval sys...
World-class prompt engineering skill for LLM optimization, prompt patterns, structured outputs, and AI product development. Expertise in Claude, GPT-4, prompt design patterns, few-shot learning, chain-of-though...
A comprehensive, long-horizon skill for designing, coding, debugging, and scaling AI-integrated systems — including Python backends, React frontends, RAG pipelines, vector databases, and tool orchestration. Ens...
Comprehensive LLM model evaluation and ranking system. Use when users ask to compare language models, find the best model for a specific task, understand model capabilities, get pricing information, or need hel...
Use this skill when coordinating multiple AI models (Claude, GPT, Gemini, DeepSeek) for competitive trading analysis, running parallel model execution, aggregating decisions, or managing model performance track...
NVIDIA NIM (NVIDIA Inference Microservices) for deploying and managing AI models. Use for NIM microservices, model inference, API integration, and building AI applications with NVIDIA's inference infrastructure...
World-class computer vision skill for image/video processing, object detection, segmentation, and visual AI systems. Expertise in PyTorch, OpenCV, YOLO, SAM, diffusion models, and vision transformers. Includes...
World-class ML engineering skill for productionizing ML models, MLOps, and building scalable ML systems. Expertise in PyTorch, TensorFlow, model deployment, feature stores, model monitoring, and ML infrastructu...
Amazon SageMaker for building, training, and deploying machine learning models. Use for SageMaker AI endpoints, model training, inference, MLOps, and AWS machine learning services.
NVIDIA API documentation for integrating NVIDIA services. Use for NVIDIA NIM (NVIDIA Inference Microservices), LLM APIs, visual models, multimodal APIs, retrieval APIs, healthcare APIs, and CUDA-X microservices...
Transform vague ideas into concrete, validated project concepts. Clarifies problem statements, identifies target users, ruthlessly scopes MVPs, challenges assumptions, and documents vision in PLANNING.md, TASK....
Production monitoring and observability for LLM applications with AgentOps session tracking, Google Cloud Observability integration, and Dynatrace monitoring. Provides real-time performance metrics, error track...
OpenAI Codex CLIを使用したコードレビュー、分析、コードベースへの質問を実行する。使用場面: (1) コードレビュー依頼時、(2) コードベース全体の分析、(3) 実装に関する質問、(4) バグの調査、(5) リファクタリング提案、(6...
CodeRabbit CLIでAIコードレビューを実行。「レビュー」「coderabbit」「CodeRabbit」「コードレビュー」時に使用。必ず--prompt-onlyオプションを使用すること。
Enforces privacy protection patterns: anonymization, no PII in logs, secure data handling, GDPR compliance. Use when handling user data, implementing AI2AI, or ensuring privacy compliance.
Comprehensive research combining web search, quantum analysis, and persistent memory. Use when researching topics that need current information plus deep cognitive analysis.
Use this skill when creating, optimizing, or improving prompts for large language models. Applies when users need help designing effective prompts, selecting appropriate prompting techniques, or troubleshooting...
Mine AI research insights and generate professional LaTeX reports for creta.mx (Center for Research on Economics and Technology Applications). Triggers on "CRETA", "research insights", "LaTeX report", or econom...
search-optimization for learning content management and knowledge systems.
Orchestrate lightweight parallel internet research (2-4 dimensions). Spawns light-research-researcher workers for each subtopic dimension, coordinates findings, synthesizes final reports. Use for standard resea...
This skill should be used when users request research on topics with compiled results saved to a file. It handles web searches, fetching authoritative sources, synthesizing information, and generating structure...
Adapt learning content for cultural contexts, replacing culturally-specific examples with local equivalents, identifying cultural sensitivities, and recommending culturally appropriate teaching methods. Use whe...
The default order uses GitHub repository stars from our indexed data. Stars belong to the source repository and may be shared by multiple skills. They indicate repository interest, not skill installs or an independent quality score.