# biliscribe

> Use this tool when you need to extract and structure video content from Bilibili for analysis or processing by large language models (LLMs). It solves the problem of unorganized video data by converting it into formatted text, making it easier to analyze and understand. The biliscribe tool takes Bilibili video content as input and outputs structured text, ideal for use cases involving LLM-based analysis or natural language processing.

Canonical page: https://skillsregistry.net/skills/43ever-biliscribe  
JSON: https://api.skillsregistry.net/v1/skills/43ever-biliscribe

## Description

Extracts and formats Bilibili video content into structured text, optimized for LLM processing and analysis.

## Trust

- **Trust score (0–1):** 0.69
- **Verification tier:** scanned
- **Last scanned:** 2026-09-01

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** media
- **Updated:** 2026-09-01

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/l74csifql1)
- **Repository:** <https://github.com/mcp-server-summary/biliscribe>

## 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": "43ever-biliscribe"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/43ever-biliscribe` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/43ever-biliscribe/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