Embeddings
Generates vector representations (embeddings) of text, enabling semantic similarity searches and powerful AI applications like clustering & recommendation.
Install on your platform
We auto-selected Claude Code based on this skill’s supported platforms.
Run in terminal (recommended)
claude mcp add embeddings npx -- -y @trustedskills/embeddings
Or manually add to ~/.claude/settings.json
{
"mcpServers": {
"embeddings": {
"command": "npx",
"args": [
"-y",
"@trustedskills/embeddings"
]
}
}
}Requires Claude Code (claude CLI). Run claude --version to verify your install.
About This Skill
What it does
This skill generates vector embeddings from text. Embeddings represent the semantic meaning of text as numerical vectors, allowing for tasks like similarity comparisons and information retrieval. It's particularly useful when you need to understand relationships between pieces of text beyond simple keyword matching.
When to use it
- Semantic Search: Find documents or passages similar in meaning to a user query.
- Clustering: Group related documents together based on their content.
- Recommendation Systems: Suggest relevant items (e.g., articles, products) based on the semantic similarity of descriptions.
- Anomaly Detection: Identify unusual text entries that deviate significantly from the norm in a dataset.
Key capabilities
- Generates vector embeddings for textual input.
- Represents text as numerical vectors.
- Facilitates semantic comparison between texts.
Example prompts
- "Generate an embedding for this sentence: 'The quick brown fox jumps over the lazy dog.'"
- "Create embeddings for these three paragraphs and tell me which are most similar."
- “What is the embedding of this product description?”
Tips & gotchas
This skill requires a text input. The quality of the generated embeddings depends on the clarity and context of the provided text.
Tags
TrustedSkills Verification
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Security Audits
| Gen Agent Trust Hub | Pass |
| Socket | Pass |
| Snyk | Pass |
🌐 Community
Passed automated security scans.