# veyra-bookmarks

> veyra-bookmarks — aquariosan-veyra-bookmarks. Use this tool when you need to manage and organize bookmarks across multiple sources, solving problems of information overload and disorganization. It provides a simple interface for inputting bookmarks and outputs a structured repository, utilizing git for version control. Ideal for AI agents requiring efficient knowledge management and recall.

Canonical page: https://skillsregistry.net/skills/aquariosan-veyra-bookmarks  
JSON: https://api.skillsregistry.net/v1/skills/aquariosan-veyra-bookmarks

## Description

Bookmark manager for AI agents. Read freely, save with Veyra commit mode.

## Trust

- **Trust score (0–1):** 0.94
- **Verification tier:** scanned
- **Last scanned:** 2026-09-28

## Facts

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

## Source

- **Source listing:** [GitHub](https://github.com/Aquariosan/veyra-bookmarks)

## 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": "aquariosan-veyra-bookmarks"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/aquariosan-veyra-bookmarks` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/aquariosan-veyra-bookmarks/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