Browse skills

Converts Markdown text into clean, semantic HTML using JimLiu's baoyu engine for enhanced formatting and compatibility.

Optimizes vector indexes for enhanced semantic search speed and accuracy by adjusting parameters like quantization levels.

Dt Obs Log Semantic Mapping — provides AI agent assistance for software development workflows.

Nuxthub generates clean, semantic HTML from Markdown, streamlining content creation and ensuring accessible web pages.

Semantic Scholar — provides AI agent assistance for software development workflows.

Metabase Semantic Checker — provides AI agent assistance for software development workflows.

Efficiently searches Qdrant vector databases using davila7's tool for semantic similarity and fast retrieval.

Generates clean, semantic HTML & CSS architecture from descriptions, boosting front-end development efficiency and maintainability.

Pinecone enables efficient semantic search by indexing and querying vector embeddings, quickly finding similar content for applications like recommendation & knowledge retrieval.

Add Semantic Layer — provides AI agent assistance for software development workflows.

Qdrant enables seamless vector database integration for semantic search and retrieval, boosting AI applications with efficient similarity matching.

Provides data modeling guidance and assistance for software development workflows.

Generates clean, semantic HTML/CSS code snippets from product descriptions, streamlining frontend development workflows.

This skill uses Sentence Transformers to generate high-quality embeddings for text, enabling semantic search and similarity analysis.

C4 Architecture generates clean, semantic HTML and CSS from component descriptions – boosting front-end development speed & consistency.

Codex generates clean, semantic HTML from natural language descriptions, streamlining frontend development and boosting accessibility.

This skill automatically generates semantic version numbers (e.g., v1.2.3) for your projects, ensuring consistent and organized releases.

Generates high-quality embeddings from text using Grepai and LMStudio for semantic search, similarity analysis, and AI applications.

Generates clean, semantic, and responsive CSS code snippets based on design descriptions, leveraging modern best practices.

Generates clean, semantic HTML from natural language descriptions, improving accessibility and SEO for your content.

Find relevant data quickly using Timescale's pgvector semantic search powered by vector embeddings.

Automates Git commit messages and branching based on code changes' semantic meaning, improving clarity and workflow.

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

Quickly retrieve relevant information from your database using semantic vector search powered by ruvnet's agentdb.