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NowPlaying XHS

作者 Seagle · GitHub ↗ · v1.1.0 · MIT-0
cross-platform ⚠ suspicious
65
总下载
0
收藏
0
当前安装
2
版本数
在 OpenClaw 中安装
/install nowplaying-xhs
功能描述
当前院线推荐 - 实时检索公映影片 + 多维度评分 + 附近影院排片
安全使用建议
This package has inconsistent documentation vs code. Before installing or supplying credentials: (1) Ask the author to clarify and update the registry metadata to declare required env vars (BOCHA_API_KEY, TAVILY_API_KEY) and any binaries (agent-browser, node). (2) Confirm whether the skill will actually call Bocha/Tavily/猫眼/淘票票 and whether you must install agent-browser globally (npm install -g) — global npm installs modify your system. (3) If you must provide API keys, only provide scoped keys with minimal permissions and rotate them if you later uninstall. (4) Be aware SKILL.md instructs accessing user location and starting a local HTTP server/screenshot flow; ensure you trust the skill and understand where data (including location) will be sent. (5) If you only want the functionality implemented by the included nowplaying.py (Rotten Tomatoes/Variety scraping), prefer running that script in an isolated environment; if you need the Chinese real-time functionality, request a code update that implements it and explicitly declares required env vars and install steps. If the author cannot reconcile these mismatches, treat the skill as untrusted.
功能分析
Type: OpenClaw Skill Name: nowplaying-xhs Version: 1.1.0 The skill bundle contains high-risk instructions in SKILL.md that direct the AI agent to execute shell commands, install global NPM packages, and launch a background HTTP server (python3 -m http.server) on the host. While these actions are intended to facilitate chart rendering via browser screenshots, they introduce significant security risks such as unauthorized local network exposure and arbitrary command execution. The Python script (nowplaying.py) is a benign scraper, but the operational instructions for the agent involve excessive system-level permissions.
能力标签
requires-sensitive-credentials
能力评估
Purpose & Capability
SKILL.md and CONFIG.md describe heavy reliance on Bocha API, Tavily, and agent-browser for real-time Maoyan/淘票票 data and mention BOCHA_API_KEY and TAVILY_API_KEY; the public registry metadata lists no required env vars. The included Python script (nowplaying.py) only fetches Rotten Tomatoes and Variety and does not implement Bocha/Tavily/猫眼/淘票票 scraping or agent-browser integration. This is a substantive mismatch between claimed capabilities and actual code/declared requirements.
Instruction Scope
The runtime instructions direct the agent to: check for user location (city/coordinates) from system context, run external tools (agent-browser, node tavily-search script), call remote APIs with API keys, spin up a local HTTP server, and take browser-rendered screenshots. Those actions access system context, start local servers, and invoke external tools — yet none of those env vars/binaries are declared in the skill manifest. The SKILL.md also mandates strict output structure and real-time scraping of third‑party Chinese sites (猫眼/淘票票) which can require more privileges or tooling than the provided code uses.
Install Mechanism
There is no install spec in the skill package (instruction-only install). However the docs instruct installing agent-browser globally via npm and using an external node script (tavily-search). Because installation steps are only in prose and not declared in metadata, an agent following SKILL.md could attempt to run npm install -g, which modifies the system environment. That action is not pre-declared and increases operational risk. The included code itself has no package install step and only uses Python stdlib HTTP calls.
Credentials
CONFIG.md and SKILL.md expect BOCHA_API_KEY and TAVILY_API_KEY (and implicitly possible BRAVE_API_KEY / SEARXNG_URL), but the skill's manifest lists no required environment variables or primary credential. The mismatch means a user might need to supply sensitive API keys not signaled by the registry metadata. Additionally SKILL.md tells the agent to probe for user location/context without declaring how that data is accessed or authorized.
Persistence & Privilege
The skill is not marked always:true and does not request system-wide persistence. It does not modify other skills' configs in the provided files. The package will not be force-included in every agent run based on metadata.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install nowplaying-xhs
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /nowplaying-xhs 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.1.0
添加完整执行脚本 nowplaying.py 和 run.sh,支持实时获取院线电影信息
v1.0.0
nowplaying-xhs 1.0.0 - Initial release: Recommends currently showing movies in cinemas based on real-time data. - Provides movie lists with multi-source ratings (Maoyan, Douban, IMDb, Rotten Tomatoes) and scores. - Supports localized (city/area-based) cinema screening times within next 2 hours, using Maoyan/Taopiaopiao data. - Outputs a summary report: top 10 recommendations ranked with detailed info, plus visual comparison charts and rating explanations. - Features fallback strategies for missing data and emphasizes data transparency, user location, and up-to-date results.
元数据
Slug nowplaying-xhs
版本 1.1.0
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 2
常见问题

NowPlaying XHS 是什么?

当前院线推荐 - 实时检索公映影片 + 多维度评分 + 附近影院排片. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 65 次。

如何安装 NowPlaying XHS?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install nowplaying-xhs」即可一键安装,无需额外配置。

NowPlaying XHS 是免费的吗?

是的,NowPlaying XHS 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

NowPlaying XHS 支持哪些平台?

NowPlaying XHS 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 NowPlaying XHS?

由 Seagle(@seeu1688)开发并维护,当前版本 v1.1.0。

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