{
  "ocm": "1",
  "id": "zhiliscope-baiyueguang-learning-skill-baiyueguang-learning",
  "kind": "skill",
  "name": "baiyueguang-learning",
  "description": "Transform knowledge points into an investigable information network using the Baiyueguang Learning Method.",
  "publisher": "zhiliscope",
  "version": "1.0.0",
  "capabilities": {
    "domains": [
      "general"
    ],
    "tags": [
      "skill-md",
      "learning",
      "education",
      "ai",
      "reasoning",
      "github"
    ],
    "languages": [
      "en"
    ]
  },
  "quality_prior": 0.6,
  "examples": [
    "Transform knowledge points into an investigable information network using the Baiyueguang Learning Method."
  ],
  "primary": false,
  "metadata": {
    "source": {
      "provider": "github",
      "repository": "https://github.com/zhiliscope/baiyueguang-learning-skill",
      "path": "SKILL.md",
      "ref": "18c9051cf9e7f0dd72ce76d4bede74e4487c2a6e",
      "url": "https://github.com/zhiliscope/baiyueguang-learning-skill/blob/18c9051cf9e7f0dd72ce76d4bede74e4487c2a6e/SKILL.md",
      "key": "zhiliscope/baiyueguang-learning-skill/SKILL.md"
    },
    "license": "MIT"
  },
  "instructions": "<!--\nSkill metadata above.\n-->\n\n# 白月光学习 Skill\n\nVersion: 1.0\n\nType: Cognitive Translation Framework\n\n目标：\n\n把任何学科中的知识点，\n转换成一个可以被调查的信息网络。\n\n不要背定义。\n\n不要记结论。\n\n先找到信息源。\n\n再建立关系网。\n\n最后形成调查报告。\n当用户输入一个知识点时，按照下面流程工作：\n\n1. 把知识点翻译成调查语言\n2. 建立它的信息源\n3. 找出它的关系网\n4. 区分新信息和重复信息\n5. 生成知识调查报告\n6. 给出下一条线索\n\n## 核心调查模型\n\n### 账号\n\n当前要调查的知识点。\n\n### 信息源\n\n这个知识点从哪里获得信息。\n\n### 关注列表\n\n它和哪些概念经常同时出现。\n\n### 点赞记录\n\n哪些信息最能代表它。\n\n### 收藏夹\n\n哪些内容必须保存。\n\n### 历史记录\n\n理解它之前需要知道什么。\n\n### 共同好友\n\n它连接到哪些领域。\n\n### 关系网\n\n它和其他知识点之间的结构。\n\n### 新线索\n\n下一个最值得学习的概念。\n\n## 输出格式\n\n```text\n目标：\n\n账号：\n\n信息源：\n\n关注列表：\n\n点赞记录：\n\n收藏夹：\n\n历史记录：\n\n共同好友：\n\n关系网：\n\n重复信息：\n\n新信息：\n\n下一条线索：",
  "cost": {
    "context_tokens": 145
  }
}