# VectorCode

> VectorCode — davidyz-vectorcode. Use this tool when you need to efficiently index and manage your code repositories to enhance your Large Language Model (LLM) experience. VectorCode solves problems related to code organization, search, and discovery, allowing for seamless integration with git. It takes in code repositories as input and outputs indexed code, making it ideal for use cases where quick code retrieval and analysis are crucial.

Canonical page: https://skillsregistry.net/skills/davidyz-vectorcode  
JSON: https://api.skillsregistry.net/v1/skills/davidyz-vectorcode

## Description

A code repository indexing tool to supercharge your LLM experience.

## Trust

- **Trust score (0–1):** 0.34
- **Verification tier:** scanned
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **Updated:** 2026-09-28

## Source

- **Source listing:** [GitHub](https://github.com/Davidyz/VectorCode)

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "davidyz-vectorcode"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/davidyz-vectorcode` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/davidyz-vectorcode/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt