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Nihaisha Learner
作者
Xzhenxing666
· GitHub ↗
· v2.0.0
· MIT-0
112
总下载
0
收藏
0
当前安装
8
版本数
在 OpenClaw 中安装
/install nihaisha-learner
功能描述
Provides expert explanations and analysis of Traditional Chinese Medicine theory, herbal formulas, acupuncture, and clinical pattern differentiation from Mas...
安全使用建议
This skill is instruction-only and appears coherent for providing TCM knowledge. Before installing, note that: (1) the skill has no source or homepage and the SKILL.md author/version metadata differ from the registry version—lack of provenance reduces trust; (2) it offers clinical pattern differentiation and health guidance, which can affect real-world medical decisions—verify advice with a licensed practitioner; (3) because there is no code to inspect, the platform scan had nothing to analyze—trust depends on the publisher. If you need higher assurance, ask the publisher for a source repository, licensing, or references for the curriculum and confirm any clinical recommendations with a qualified professional.
功能分析
Type: OpenClaw Skill
Name: nihaisha-learner
Version: 2.0.0
The skill bundle consists solely of metadata and a descriptive markdown file (SKILL.md) outlining a Traditional Chinese Medicine (TCM) knowledge base. There is no executable code, network activity, or evidence of prompt injection; it serves purely as an informational guide for an AI agent.
能力评估
Purpose & Capability
The name, description, and SKILL.md all describe Traditional Chinese Medicine (theory, herbs, formulas, acupuncture). There are no unexpected required binaries, credentials, or config paths that would be unrelated to a knowledge/QA skill.
Instruction Scope
SKILL.md contains only content and guidance for answering TCM questions; it does not instruct the agent to read local files, access system state, call unknown external endpoints, or exfiltrate data. The runtime instructions are self-contained and limited to providing TCM expertise.
Install Mechanism
There is no install spec and no code files—this is an instruction-only skill. That minimizes on-disk execution risk because nothing is downloaded or installed by the skill itself.
Credentials
The skill declares no environment variables, credentials, or config paths. It does not request access to unrelated services or secrets.
Persistence & Privilege
always:false and default invocation settings are used. The skill does not request forced or permanent presence and does not modify other skills or system-wide settings.
如何使用
- 确保已安装 OpenClaw（本地或 Docker 部署）
- 在对话框中输入安装命令：
/install nihaisha-learner - 安装完成后，直接呼叫该 Skill 的名称或使用
/nihaisha-learner触发 - 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
v2.0.0
Version 2.0.0 of nihaisha-learner introduces a major update focused on TCM expertise based on Master Ni Haixia's curriculum.
- Comprehensive TCM knowledge system covering theory, herbs, formulas, acupuncture, and clinical applications from "Ren Ji" and "Tian Ji" series.
- Expanded capabilities including theory explanation, formula analysis, herb identification, acupoint knowledge, pattern diagnosis, and seasonal health guidance.
- Clear categorization of classical TCM texts, formulas, and herbal grades.
- Practical use cases for learners, practitioners, and enthusiasts highlighted.
- Noted alignment with Master Ni Haixia's interpretations, which may differ from traditional texts.
v1.0.6
- Updated SKILL.md to include an English version of the skill description and knowledge system.
- Clarified and standardized section headers and terminology.
- Expanded explanations for TCM theoretical frameworks, classical courses, and formulas.
- Highlighted capabilities and applicable scenarios for users.
- Updated author, version, and date information.
v1.0.5
No changes detected in this version.
- No file changes were made.
- SKILL.md and all content remain identical to the previous version.
v1.0.4
- Refined and expanded the skill description for better clarity and detail.
- Organized knowledge and capabilities into clearer categories:基础理论, 经典课程, 核心方剂, and 中药学.
- Added “功能特性”, outlining key abilities such as理论解答, 方剂分析, 药材鉴别, 穴位定位, 辨证论治, and养生建议.
- Included a new “适用场景” section describing ideal user groups and use cases.
- Updated and standardized notes on usage and reference basis.
- Improved formatting for better readability.
v1.0.3
- 技能名称由“倪海厦中医课程学习技能”更改为“中医专家”。
- 其余内容、核心能力和用法示例保持不变。
v1.0.2
- Revamped skill description for clarity, focusing on advanced TCM expertise and core contents of Nihaisha’s courses.
- Reorganized and detailed sections on acupuncture, herbal medicine, Shanghan Lun, Jin Kui Yao Lue, and related TCM concepts.
- Expanded usage examples for diverse TCM question types.
- Shifted emphasis from file/document scanning abilities to knowledge answering capability.
- Added clear outline of mastered knowledge areas and coverage of Nihaisha Renji series.
- Notes now clarify scope: knowledge answering based on Nihaisha’s system; learning new material requires separate file tools.
v1.0.1
- 精简技能定位，仅专注于倪海厦中医课程学习，移除QMT量化交易相关内容。
- 优化说明结构，细化文档扫描、内容读取、学习功能等核心能力描述。
- 新增OCR功能（可选），支持识别图片版PDF。
- 更新Python依赖，移除不相关依赖，增加pdf2image和pytesseract（OCR用）。
- 补充更具体的使用举例和操作说明。
- 作者和说明信息更新。
v1.0.0
nihaisha-learner 1.0.0
- Initial release combining two major abilities: 倪海厦中医课程学习 and QMT量化交易。
- Supports scanning and extracting key points from F盘中医PDF/Word documents.
- Automates QMT软件 startup and basic operations using pyautogui.
- Guides QMT量化交易 strategy writing, backtesting, and management via Python API.
- Organizes learning notes and supports classified course review.
元数据
常见问题
Nihaisha Learner 是什么？
Provides expert explanations and analysis of Traditional Chinese Medicine theory, herbal formulas, acupuncture, and clinical pattern differentiation from Mas... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 112 次。
如何安装 Nihaisha Learner？
在 OpenClaw 或 Claude Code 对话框中运行命令「/install nihaisha-learner」即可一键安装，无需额外配置。
Nihaisha Learner 是免费的吗？
是的，Nihaisha Learner 完全免费，采用 MIT-0 许可证，可自由下载、安装和使用。
Nihaisha Learner 支持哪些平台？
Nihaisha Learner 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 Nihaisha Learner？
由 Xzhenxing666（@xzhenxing666）开发并维护，当前版本 v2.0.0。
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