Ark Embedding
Ark Embedding generates vector embeddings for your data, enabling semantic search and similarity analysis across diverse text formats.
Install on your platform
We auto-selected Claude Code based on this skill’s supported platforms.
Run in terminal (recommended)
claude mcp add ark-embedding npx -- -y @trustedskills/ark-embedding
Or manually add to ~/.claude/settings.json
{
"mcpServers": {
"ark-embedding": {
"command": "npx",
"args": [
"-y",
"@trustedskills/ark-embedding"
]
}
}
}Requires Claude Code (claude CLI). Run claude --version to verify your install.
About This Skill
What it does
The ark-embedding skill provides vector embeddings of text. These embeddings represent the semantic meaning of text, allowing for tasks like similarity comparisons and information retrieval. It's designed to be a foundational component for building more complex AI agent capabilities that require understanding textual context.
When to use it
- Semantic Search: Find documents or passages most relevant to a user’s query by comparing embedding vectors.
- Clustering: Group similar text entries together based on their embedding proximity.
- Recommendation Systems: Suggest related content or items based on the semantic similarity of their descriptions.
- Anomaly Detection: Identify unusual or outlier text entries that have significantly different embeddings compared to the norm.
Key capabilities
- Generates vector embeddings from text input.
- Provides a foundational component for semantic understanding.
Example prompts
- "Generate an embedding for this sentence: 'The quick brown fox jumps over the lazy dog.'"
- "What is the embedding of this product description?"
- “Create an embedding to compare against other documents.”
Tips & gotchas
- The quality of the embeddings depends on the underlying model used. Consider experimenting with different models for optimal results in your specific use case.
Tags
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