# ai.backrow/backrow

> ai.backrow/backrow — ai-backrow-backrow. Use this tool when you need to convert unstructured recordings or documents into actionable notes, flashcards, and quizzes. It solves the problem of information overload by extracting key insights and making them easily digestible for AI agents. The tool takes in recordings or documents as input and outputs structured notes, flashcards, and quizzes that can be read and acted upon by agents.

Canonical page: https://skillsregistry.net/skills/ai-backrow-backrow  
JSON: https://api.skillsregistry.net/v1/skills/ai-backrow-backrow

## Description

Turn any recording or document into notes, flashcards and quizzes your agent can read and act on

## Trust

- **Trust score (0–1):** 0.70
- **Verification tier:** unverified

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Updated:** 2026-09-07

## Source

- **Source listing:** [MCP Registry](https://registry.modelcontextprotocol.io/v0/servers/ai.backrow%2Fbackrow)

## Use it

MCP endpoint published by the skill: `https://backrow.ai/mcp`

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": "ai-backrow-backrow"
    }
  }
}
```

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