# tasogare

> tasogare — enhydrink-tasogare. Use this tool when you need to collaboratively read and annotate books with an AI companion. It solves problems of solo reading and analysis by allowing AI-assisted markup and commentary, with features like text-anchored two-color highlights. It takes in book text and user input, and outputs a shared reading experience with AI-generated comments and annotations.

Canonical page: https://skillsregistry.net/skills/enhydrink-tasogare  
JSON: https://api.skillsregistry.net/v1/skills/enhydrink-tasogare

## Description

Read the same book with your AI. A collaborative reader with text-anchored two-color highlights and an MCP server so an AI companion can flip through, mark up, and comment alongside you.

## Trust

- **Trust score (0–1):** 0.70
- **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/EnhydrInk/tasogare)

## 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": "enhydrink-tasogare"
    }
  }
}
```

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