How does it handle large projects with many files?

The skill implements automatic batching and rate limiting (3 requests per minute) to ensure it stays within Voyage AI's free and paid tier limits while processing content.

What is the primary purpose of the embed-content skill?

It indexes your local project's skills, agents, and tools using vector embeddings so Claude can discover and use them via semantic search rather than just keyword matching.

Can I use these embeddings with an MCP server?

Yes, the skill includes an --export flag that generates a .claude/tool_embeddings.json file specifically designed for consumption by semantic MCP servers.

Does this skill require an external API?

Yes, this skill requires a Voyage AI API key (set as VOYAGE_API_KEY) to compute the high-quality embeddings used for semantic discovery.

Will it use my API credits every time I run it?

No, it performs incremental updates by comparing content hashes and only embeds items that are new or have been modified since the last run.

Project Embedding Manager

Name: Project Embedding Manager
Author: jrc1883

byjrc1883

개발자 도구

Manages project-specific embeddings to enable semantic discovery of skills, agents, and tools within Claude Code.

소개

The Project Embedding Manager skill provides a robust framework for indexing local project content—including custom skills, agents, and MCP tools—into a vector database. By utilizing Voyage AI for high-quality embeddings, it transforms static project files into semantically searchable assets, allowing Claude to intelligently locate and invoke the most relevant tools for a given task. It features built-in rate limiting to respect API constraints, incremental updates to save on processing time, and export capabilities for seamless integration with Model Context Protocol (MCP) servers.

주요 기능

0 GitHub stars
JSON export for MCP tool embedding integration
Automated Voyage AI embedding generation
Built-in rate limiting and batching logic
Incremental updates with status reporting
Semantic search discovery for project assets

사용 사례

Maintaining a semantic map of project-specific commands and agents
Indexing custom project skills for improved AI retrieval
Generating searchable embeddings for local MCP tool definitions

소개

주요 기능

0 GitHub stars
JSON export for MCP tool embedding integration
Automated Voyage AI embedding generation
Built-in rate limiting and batching logic
Incremental updates with status reporting
Semantic search discovery for project assets

사용 사례

Maintaining a semantic map of project-specific commands and agents
Indexing custom project skills for improved AI retrieval
Generating searchable embeddings for local MCP tool definitions