Browse skills

Leverage proven prompt engineering techniques from wshobson to optimize AI model outputs and achieve desired results.

This skill provides a robust RAG (Retrieval-Augmented Generation) implementation for enhanced AI responses by retrieving relevant context.

Rag Retrieval — provides AI agent assistance for software development workflows.

Gepetto helps you generate high-quality, diverse creative content like stories and poems by leveraging advanced AI models – boosting your writing workflow!

Official google skill for management — helps with software development workflows.

Implement robust Retrieval Augmented Generation (RAG) pipelines using langchain4j patterns for enhanced AI knowledge access.

Retrieval-Augmented Generation (RAG) enhances LLMs by retrieving relevant context from external data sources, boosting accuracy and knowledge.

The Rag Engineer skill automatically constructs high-quality retrieval augmented generation (RAG) pipelines for seamless knowledge integration and improved AI responses.

This Rag implementation facilitates Retrieval-Augmented Generation by providing a structured framework for integrating external knowledge into AI responses, boosting accuracy and context.

This skill leverages powerful Transformer models for advanced text generation, offering nuanced responses and creative content creation.

Leverages ceeon's vast knowledge base to synthesize expert opinions and generate comprehensive, nuanced solutions.

Generates optimal AI skill prompts & training data leveraging best practices for improved model performance.

Leverages Anthropic's Claude to generate, debug, and refine code snippets and development workflows efficiently.

Evaluates Retrieval-Augmented Generation (RAG) responses for accuracy and relevance, boosting RAG system quality & reliability.

Build custom RAG agents quickly using Qodex AI's tool, defining data sources, prompts, and actions for tailored knowledge retrieval.

This skill leverages vector databases to efficiently store and search semantic similarity between data points, enabling powerful retrieval-based AI applications.

Automates building Retrieval-Augmented Generation (RAG) pipelines for knowledge retrieval and AI application development.

Claude MD Authoring assists in crafting polished markdown content by leveraging Claude's powerful language capabilities for improved writing and formatting.

Automates vector database creation and configuration, streamlining data storage and similarity search workflows.

Identifies and suggests fixes for TensorFlow code errors, leveraging snakeo's expertise in debugging deep learning models.

Provides search guidance and assistance for software development workflows.

This tool rapidly constructs Retrieval-Augmented Generation (RAG) systems by automating data sourcing and prompt engineering for enhanced AI responses.

Rag Infrastructure — provides AI agent assistance for software development workflows.

Leverage proven prompt engineering patterns from rmynhdaris to optimize AI model outputs for clarity, accuracy, and desired results.