Embeddings
This skill generates vector embeddings of text, enabling semantic similarity searches and powering advanced AI applications like recommendation systems.
Install on your platform
We auto-selected Claude Code based on this skill’s supported platforms.
Run in terminal (recommended)
claude mcp add ruvnet-embeddings npx -- -y @trustedskills/ruvnet-embeddings
Or manually add to ~/.claude/settings.json
{
"mcpServers": {
"ruvnet-embeddings": {
"command": "npx",
"args": [
"-y",
"@trustedskills/ruvnet-embeddings"
]
}
}
}Requires Claude Code (claude CLI). Run claude --version to verify your install.
About This Skill
What it does
This skill, authored by ruvnet, provides embedding generation capabilities. Embeddings are numerical representations of text that capture semantic meaning, allowing for tasks like similarity comparisons and information retrieval. It is specifically associated with the ruflo project.
When to use it
- Semantic Search: Find documents or passages similar in meaning to a given query.
- Clustering: Group related pieces of text together based on their semantic content.
- Recommendation Systems: Suggest relevant items (e.g., articles, products) based on user preferences represented as embeddings.
- Knowledge Base Indexing: Create an efficient index for retrieving information from a large knowledge base.
Key capabilities
- Generates text embeddings
- Associated with the
rufloproject
Example prompts
- "Generate an embedding for this sentence: 'The quick brown fox jumps over the lazy dog.'"
- "Create embeddings for these documents and tell me which are most similar."
- "Embed this product description so I can find related products."
Tips & gotchas
This skill requires familiarity with the ruflo project to function correctly. The specific embedding model used is not specified in the provided documentation, so results may vary depending on the context and application.
Tags
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Security Audits
| Gen Agent Trust Hub | Pass |
| Socket | Pass |
| Snyk | Pass |
🌐 Community
Passed automated security scans.