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Douban Movie Review

agentbay-ai/agentbay-skills
136 installs40 stars
Summary

This is a browser automation skill that scrapes movie reviews from Douban, China's popular film rating platform. It's useful when you need to pull user sentiment and hot comments for Chinese movies, since Douban has one of the most active film communities in that market. The skill uses the wuying-agentbay-sdk to automate a browser session that navigates to Douban, searches for a movie, and extracts the top reviews with usernames and like counts. Processing takes one to two minutes per request, and you get a visualization URL to watch the automation run. If you're building anything that needs Chinese movie sentiment data or competitive analysis on film reception in China, this handles the tedious scraping work for you.

Install to Claude Code

npx -y skills add agentbay-ai/agentbay-skills --skill douban-movie-review --agent claude-code

Installs into .claude/skills of the current project.

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One time payment $9 →
Context.devContext.dev
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Integrate web data into your AI product. One API to scrape website & brand data.
Get API Key Now →
Make your agent a DeFi expert
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Agent, run crypto. Access onchain data & trade routes via 1inch.
Install now →
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On Capafy, your Skill runs online 24/7 as an agent product, and you get paid every time someone uses it.
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Files
SKILL.mdView on GitHub

豆瓣电影影评查询

依赖

python3 -m pip install wuying-agentbay-sdk

安装步骤

在使用此技能之前,请确保已安装必要的依赖包:

python3 -m pip install wuying-agentbay-sdk

使用场景

  • 用户询问某部电影的豆瓣影评
  • 用户想了解电影的用户评价
  • 用户想查看电影的热门短评

使用方法

python3 scripts/browser-use.py "<任务执行步骤>"

快速示例

python3 scripts/browser-use.py " \

  1. 前往豆瓣网站https://www.douban.com/ \
  2. 搜索电影盗梦空间 \
  3. 点击盗梦空间进入详情界面,下滑到短评部分 \
  4. 提取前5条热门评论 \
  5. 以markdown格式返回 "

输出格式

## 《电影名称》豆瓣影评

### 热门短评

1. 用户名 点赞数 评论内容
2. 用户名 点赞数 评论内容

注意事项

  • 始终注明信息来源为豆瓣
  • 不需要创建新的脚本,用skill目录下的browser-use.py
  • 任务需要执行1~2分钟,不要杀进程,请耐心等待和观察任务,也不要重试
  • skill调用后,控制台会打印出asp流化链接(可视化的url),可告知用户查看
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Categories
Git & Pull RequestsCode Review & Quality
First SeenJun 3, 2026
View on GitHub

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