smart-collect

分析和总结URL链接内容，并保存到obsidian中，同时定期提醒复习

Security Scan

The skill's code and instructions are consistent with its stated purpose (fetch URL content, generate summaries, save Markdown into an Obsidian-like folder, and run scheduled reviews); it contains no obvious exfiltration or hidden endpoints, but you should review config and scheduling before enabling it because it will write files and make network requests.

Purpose & Capability

Name/description (collect URLs, summarize, save to Obsidian, schedule reviews) match the included code: fetcher, LLM wrapper, markdown store, and review engine. The skill expects an LLM/feishu configuration in config.json.example (documented in SKILL.md) which is coherent with the LLM and notifier code. Minor note: the published metadata lists no required env vars but the code can use a DeepSeek API key (process.env.DEEPSEEK_API_KEY) and accepts feishu config — this is optional in practice but is not reflected in the registry metadata.

Instruction Scope

SKILL.md instructs adding a cron job to run the review script; scripts read/write Markdown files under a user-specified storagePath (defaults to ~/Desktop/Obsidian/Star). The fetcher fetches arbitrary user-provided URLs (outbound HTTP(S) calls) and can call an LLM endpoint. The browser-based scraping path references a local snapshot endpoint (http://127.0.0.1:18800/snapshot?url=...) — this is not external but will attempt to use a local service if available. Overall the instructions stay within purpose, but you should be aware scheduled runs will perform network requests and create/update files in your home directory.

Install Mechanism

No install spec; this is instruction + code only and does not pull executables from external URLs. That minimizes install-time risk. The code uses Node standard libs and child_process is referenced but not used to execute arbitrary external binaries.

Credentials

The skill does not declare required env vars in the registry, but the code supports using a DeepSeek API key (process.env.DEEPSEEK_API_KEY) and expects an LLM/Feishu configuration in config.json. Requesting an LLM API key or notifier config is proportionate to the stated functionality; however, the metadata could be clearer about optional credentials so users know to provide them before use.

Persistence & Privilege

always:false (normal). The skill will create files in the specified storage path (default in the user's home directory) and SKILL.md suggests adding a scheduled job to OpenClaw's jobs.json to run the review script daily — that requires editing OpenClaw configuration but the skill itself does not force-enable itself or modify other skills. Scheduled execution means network fetches and file writes will occur unattended when the job runs; review config carefully before enabling scheduling.

Assessment

This skill appears to do what it says, but before installing or enabling scheduled runs: 1) open config.json.example and verify storagePath (change it if you don't want files written to the default ~/Desktop/Obsidian/Star); 2) if you provide an LLM API key, understand LLM calls will go to the configured service (DeepSeek by default) — only provide keys for services you trust; 3) the reviewer/cron suggestion will cause the review script to run automatically and fetch user-provided URLs (outbound network activity) — only schedule it if you trust the skill and the URLs it will fetch; 4) the fetcher may try to use a local snapshot service at 127.0.0.1:18800 for dynamic pages — ensure that local service is trusted; 5) review or run the scripts manually first (node scripts/shoucang-add.js, node scripts/shoucang-review.js) to confirm behavior before adding to OpenClaw cron. If you want higher assurance, inspect config.json you create and run the scripts in a contained environment before enabling automation.

Smart Collect - 智能收藏回顾系统

基于艾宾浩斯遗忘曲线的智能收藏系统，支持自动抓取、摘要生成、定时复习提醒。

目录结构

smart-collect/
├── SKILL.md                 # 本文件
├── lib/
│   ├── reviewEngine.js      # 艾宾浩斯复习引擎
│   ├── markdownStore.js     # Markdown 存储模块
│   ├── nlpParser.js        # 自然语言解析模块
│   └── fetcher.js          # 网页抓取模块
├── scripts/
│   ├── shoucang-add.js     # 添加收藏脚本
│   ├── shoucang-review.js  # 复习回顾脚本
│   └── smart-collect.js    # 主入口
└── config.json.example      # 配置示例

功能

1. 自动抓取

• 支持 GitHub/微信公众号/小红书/普通网页
• Readability 算法提取正文
• LLM 生成摘要、标签、分类

2. 艾宾浩斯复习

• 间隔：1天 → 2天 → 4天 → 7天 → 15天
• 超过5次自动归档

3. 自然语言管理

• 推迟X天
• 已看完归档
• 添加/删除标签
• 标记已回顾

配置

复制 config.json.example 为 config.json 并填入：

• 收藏存储路径
• 飞书配置
• LLM API 配置

OpenClaw Cron 配置

定时规则

每天 09:30 触发复习

cron 表达式

30 9 * * *

OpenClaw jobs.json 配置

{
  "jobs": [
    {
      "id": "smart-collect-review",
      "name": "智能收藏每日复习",
      "description": "基于艾宾浩斯曲线触发收藏复习提醒",
      "enabled": true,
      "schedule": {
        "kind": "cron",
        "expr": "30 9 * * *"
      },
      "sessionTarget": "isolated",
      "wakeMode": "now",
      "payload": {
        "kind": "agentTurn",
        "message": "请执行智能收藏的每日复习任务，运行命令：cd ~/.openclaw/skills/smart-collect && node scripts/shoucang-review.js"
      },
      "delivery": {
        "mode": "announce",
        "channel": "feishu",
        "to": "ou_你的飞书ID"
      }
    }
  ]
}

部署步骤

1. 复制配置到 OpenClaw cron 目录：

cp config.json.example config.json
# 编辑 config.json 填入你的配置

2. 添加 cron 任务：

# 编辑 ~/.openclaw/cron/jobs.json 添加上述配置

3. 重启 Gateway：

openclaw gateway restart

---

文件结构

smart-collect/
├── SKILL.md                 # 本文件
├── lib/
│   ├── reviewEngine.js      # 艾宾浩斯复习引擎
│   ├── markdownStore.js     # Markdown 存储模块
│   ├── nlpParser.js         # 自然语言解析模块
│   └── fetcher.js           # 网页抓取模块
├── scripts/
│   ├── shoucang-add.js      # 添加收藏脚本
│   ├── shoucang-review.js    # 复习回顾脚本
│   └── smart-collect.js     # 主入口
└── config.json.example      # 配置示例