Browse skills

Fine-tunes embedding models to improve semantic search relevance and similarity matching accuracy across diverse datasets.

Automatically generates semantic release tags (e.g., v1.2.3) based on commit messages for streamlined deployments.

Automates semantic versioning, changelog generation, and package publishing using Git commits and conventional commits.

This skill generates diverse embedding strategies for your data, optimizing retrieval and semantic understanding across various AI models.

Rapidly generates clean, semantic CSS code from natural language descriptions or design mockups.

Helps with testing, JSON as part of working with databases and data persistence workflows.

Rapidly generates clean, semantic HTML structure from design mockups or textual descriptions using optimized code patterns.

Generates clean, semantic HTML/CSS/JS code snippets based on design specifications and user prompts.

Semtools analyzes text for semantic consistency, ensuring clarity and reducing ambiguity in generated content – vital for polished outputs.

This skill compares embeddings to find similar concepts or identify anomalies by measuring semantic similarity.

This skill generates diverse embedding strategies for your data, optimizing semantic understanding and improving AI model performance.

Automates Git tag creation, release branch management, and version bumping based on semantic versioning rules.

This skill automatically generates semantic version numbers for your projects, ensuring consistent and organized releases for better tracking & collaboration.

This skill generates dense vector embeddings from text modules for semantic similarity searches and enhanced retrieval within RAG systems.

Generates clean, semantic CSS code from natural language descriptions or design mockups, streamlining web development workflows.

Automatically generates accessible ARIA attributes and semantic HTML for astronomy visualizations and data displays.

This tool creates vector embeddings from text, enabling semantic search and understanding within AI applications.

Generates clean, semantic HTML/CSS/JS code snippets based on design specifications and user requirements.

This skill adds custom entity types to your knowledge base, improving semantic search and data understanding for more precise results.

This skill generates vector embeddings of text, enabling semantic similarity searches and powerful AI applications like clustering & recommendation.

Automates semantic versioning (SemVer) of releases, ensuring consistent and predictable software updates for improved stability and tracking.

This skill creates complex, named relationships between tokens, streamlining data organization and enhancing semantic understanding for your AI projects.

Generates clean, semantic CSS code from natural language descriptions, optimizing for readability and maintainability.

Swiftdata generates clean, semantic HTML from React components, streamlining frontend development and improving maintainability.