🎬 观影小管家

整合TMDB与Emby/Plex，提供电影查询、媒体库管理、观影记录和个性化推荐服务。

Security Scan

The skill's description matches its purpose, but the package contains hard-coded API keys, inconsistent metadata about required credentials, and code that loads an outer .env path (potentially reading unrelated secrets) — these mismatches and a detected prompt-injection marker make the package suspicious.

Purpose & Capability

Registry metadata claims no required environment variables, but package.json, SKILL.md and index.js clearly expect TMDB, Emby (URL/API key/user id) and optional Plex credentials. The code also embeds default API keys and local Emby URLs. This is an internal inconsistency: either the registry metadata is wrong or the skill is asking for secrets it didn't declare.

Instruction Scope

SKILL.md instructs storing credentials in a specific absolute path (C:\Users\yz207\.openclaw\.env) and index.js/feishu-card.js use dotenv to load ../../../.env. The runtime instructions and code read/write the local movie-memory.md file and call TMDB/OMDb/Emby/Plex APIs (expected), but loading an outer .env path can cause the skill to read unrelated environment values. SKILL.md also contains a detected unicode-control-chars prompt-injection pattern.

Install Mechanism

No install spec (instruction-only) and no external downloads — that's lower risk. However the package includes executable JS files (index.js, feishu-card.js) that will be present on disk and executed; there is no build/install step declared, so execution will rely on these included files.

Credentials

The code legitimately needs TMDB and Emby/Plex credentials for its features, but: (1) the registry metadata advertised 'none' for required env vars while package.json lists required env; (2) multiple API keys (TMDB, several OMDb keys) are hard-coded as defaults in index.js and SKILL.md, which is poor practice and may indicate leaked or reused keys; (3) the practice of pointing to a user-specific absolute .env path and loading ../../../.env is disproportionate because it may expose other environment secrets on the host.

Persistence & Privilege

The skill is not marked always:true and does not claim elevated platform privileges, which is good. However the code intentionally loads an .env file from a relative path that climbs directories (../../../.env) and writes/updates movie-memory.md. Loading an outer .env can access secrets belonging to the host or other skills; combined with autonomous invocation this increases blast radius.

Scan Findings in Context

[unicode-control-chars] unexpected: A prompt-injection pattern was detected in SKILL.md (unicode control characters). This is not expected for a movie-recommendation README and may indicate an attempt to manipulate prompt processing or the evaluator. Treat with caution.

What to consider before installing

What you should consider before installing: - Inconsistency: The registry advertises no required env vars but the package and README expect TMDB, Emby (URL/API key/user id) and optionally Plex. Confirm with the author which credentials are actually needed. - Hard-coded keys: index.js and SKILL.md include default API keys (TMDB and several OMDb keys). These may be placeholders or leaked keys — they are poor practice and could be abused. Do not rely on embedded keys; prefer to put your own API keys in a controlled location. - .env path risk: The code uses dotenv with path.join(__dirname, '../../../.env') and SKILL.md instructs putting credentials in a user-specific .env path. That can cause the skill to load environment variables outside the skill folder (potentially other secrets). Before running, edit the code to point to a safe, explicit config path you control, or run the skill in a sandboxed environment. - Prompt-injection marker: A unicode-control-chars pattern was found in SKILL.md. Treat documentation and prompts carefully; validate that runtime prompts and instructions haven't been tampered with. - Practical mitigations: (1) Review and remove any hard-coded keys; replace with explicit required env variables and clear docs. (2) Modify dotenv path to an approved, explicit file (not '../../../.env'). (3) Run the code in an isolated VM/container and monitor network calls to confirm only TMDB/Emby/Plex endpoints are contacted. (4) If you don't trust the source, don't provide any real API keys or sensitive service tokens until code is audited or the author provides a signed/official release. If you want, I can: point to the exact lines with hard-coded keys and dotenv usage, suggest a safe code change to use process.env only (no default keys), or produce a checklist to audit network behavior before trusting this skill.

🎬 Movie Butler - 观影小管家

杜老师的专属观影助手，整合 TMDB + Emby/Plex，提供电影查询、媒体库管理、个性化推荐等服务。

📋 功能列表

1. 🌐 电影查询（全网 + 服务器）

• TMDB 全网查询 - 简介、评分、演员、导演、类型、海报
• Emby 服务器查询 - 检查是否有该片、画质信息
• 智能下载建议 - 服务器没有时，提供下载提示
• 一键对比 - 同时显示全网信息和服务器状态

2. 📺 Emby 媒体库管理

• 查询服务器上的电影/剧集
• 获取媒体库统计
• 搜索特定影片
• 查看最近添加/最近播放

3. Plex 媒体库管理

• 查询 Plex 服务器内容
• 获取播放列表
• 媒体库统计

4. 观影记录与偏好

• 记录看过的电影和感受
• 记录评分
• 分析观影偏好
• 个性化推荐

5. 🎯 每周一部电影

• 自动生成每周推荐
• 智能分析您的喜好
• 结合 Emby 服务器内容
• 给出详细推荐理由
• 记录每周观影计划

6. 背景感知推荐

• 根据心情推荐（累→轻松，开心→刺激）
• 根据工作状态推荐（忙→犒劳，闲→深度）
• 根据最近关注推荐
• 周末/工作日不同策略

🔧 使用方法

查询电影信息

查询《肖申克的救赎》
《星际穿越》的详细信息

查询服务器内容

Emby 上有哪些科幻电影？
我的服务器有多少部电影？
Emby 有诺兰的电影吗？
最近添加了什么电影？

搜索特定影片

服务器上有《盗梦空间》吗？
Emby 搜索《阿凡达》

记录观影感受

刚看了《星际穿越》，很震撼，诺兰的叙事手法太厉害了，评分 9/10

🎯 每周一部电影

本周推荐什么电影？
这周有什么好电影推荐
周末了，推荐部电影
最近工作很累，推荐部轻松的

背景记录（让推荐更精准）

今天心情很好
最近工作很忙
最近对科幻题材感兴趣

个性化推荐

推荐几部科幻电影
推荐类似《星际穿越》的电影
Emby 上有什么高分电影推荐？
我还没看过的科幻片有哪些？

查看观影历史

我看过哪些电影？
我的观影记录

📁 文件结构

• SKILL.md - 本说明文档
• index.js - 主程序
• movie-memory.md - 观影记录和偏好（自动创建）

🔑 API 配置

在 C:\Users\yz207\.openclaw\.env 中配置：

# TMDB
TMDB_API_KEY=bd1ba3aa647fbaa7b35e93db5164a53f
TMDB_BEARER_TOKEN=xxx

# Emby
EMBY_URL=http://192.168.0.151:8096
EMBY_USERNAME=喜悦影音
EMBY_PASSWORD=
EMBY_API_KEY=xxx (需要生成)

# Plex (可选)
PLEX_URL=http://xxx:32400
PLEX_TOKEN=xxx

📝 观影记忆格式

## 2026-03-03

### 《肖申克的救赎》
- **评分**: 10/10
- **感受**: 经典中的经典，希望与绝望的对比太震撼了
- **类型偏好**: +剧情，+励志

### 累计偏好
- 最爱类型：科幻、剧情、悬疑
- 最爱导演：诺兰、斯皮尔伯格
- 平均评分：8.5/10
- 已观影：15 部