# kagaz

> kagaz — getkagaz-kagaz. Use this tool when you need to manage and organize local documents on macOS without relying on cloud services or proprietary formats. Kagaz solves the problem of document clutter by providing a convention-based naming and tagging system, with outputs in JSON format and integration with git for version control. It is ideal for users who require a self-contained, agent-legible document management solution.

Canonical page: https://skillsregistry.net/skills/getkagaz-kagaz  
JSON: https://api.skillsregistry.net/v1/skills/getkagaz-kagaz

## Description

Local-first document vault manager for macOS. Names, files and tags your documents by convention — no database, no cloud, no proprietary format. Agent-legible: --json everywhere, plus an MCP server.

## Trust

- **Trust score (0–1):** 0.51
- **Verification tier:** scanned
- **Last scanned:** 2026-09-28

## Facts

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

## Source

- **Source listing:** [GitHub](https://github.com/getkagaz/kagaz)

## 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": "getkagaz-kagaz"
    }
  }
}
```

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