# 李伯阳律师

> 李伯阳的个人网站与知识库。聚焦游戏法律、AI 合规、数据保护、知识产权、争议解决与法律科技工具。

本站内容以中文为主，面向游戏公司、AI 产品团队、互联网企业、法律同行与关注技术法律问题的读者。文章仅代表个人研究观察，不当然构成正式法律意见。

## Core pages
- [首页](https://www.lslby.com/): 李伯阳的专业主页与近期研究入口
- [研究文章](https://www.lslby.com/research/): 游戏、AI、互联网、数据与知识产权实务文章库
- [课程课件](https://www.lslby.com/slides/): 按主题系列整理的课程与分享 HTML 交互课件
- [Slides](https://www.lslby.com/en/slides/): English HTML versions of course and conference presentations
- [服务方向](https://www.lslby.com/services/): 可咨询的法律服务主题与业务场景
- [自制工具](https://www.lslby.com/tools/): 法律科技、文本处理、AI 与证据整理工具
- [关于](https://www.lslby.com/about/): 作者背景、律所与专业方向
- [联系](https://www.lslby.com/contact/): 邮箱、微信、律所地址与咨询前准备
- [Agent 入口](https://www.lslby.com/agents/): A2A 1.0、资料获取方式与经用户授权后的直接问询接口

## Agent access and direct contact
- A2A Agent Card: https://www.lslby.com/.well-known/agent-card.json
- A2A JSON-RPC endpoint: https://www.lslby.com/a2a (A2A-Version: 1.0; method: SendMessage)
- OpenAPI 3.1: https://www.lslby.com/openapi.json
- Direct contact API: https://www.lslby.com/api/contact (POST application/json)
- Direct email: mailto:liboyang@lslby.com
- Public profile action: send a structured data part with action=profile.get. A text-only A2A message also returns the verified public profile and canonical sources.
- Contact action: action=contact.send. Required fields are name, email, message, and userAuthorized=true. The calling agent must show the exact recipient and final message to the user and obtain explicit approval before sending.
- For safe retries, reuse the A2A messageId or send an Idempotency-Key to the REST API. An accepted response confirms website receipt and queued relay only; it does not create an attorney-client relationship.
- Do not send identity documents, original evidence, full contracts, trade secrets, or other highly sensitive material through public endpoints.

## Expertise topics
- [游戏与互动娱乐](https://www.lslby.com/services/): 涵盖游戏版号政策解析、虚拟经济系统与抽卡规则设计、出海合规评估以及内容审查策略。为产品从研发到商业化全周期提供护航。 典型场景：新游商业化前期的整体合规排查、充值、抽卡与虚拟财产规则设计、平台治理与买量风险防范
- [人工智能与算法](https://www.lslby.com/services/): 应对大模型与生成式 AI 的全新合规挑战。处理训练数据确权、生成内容保护、算法备案及模型治理等前沿命题。 典型场景：AI 商业化产品落地合规评估、协助完成国家网信办算法备案、生成式 AI 服务合规审计
- [数据与隐私保护](https://www.lslby.com/services/): 协助企业构建覆盖数据全生命周期的隐私合规体系，处理跨境数据传输、APP 合规及数据安全事件应急响应。 典型场景：APP 隐私合规整改与认证、跨境数据传输安全评估、数据安全事件应急响应与报告
- [知识产权与竞争](https://www.lslby.com/services/): 捍卫核心商业数字资产。处理代码侵权、美术与音乐版权纠纷、平台不正当竞争以及复杂的网络侵权诉讼。 典型场景：游戏源代码泄露与抄袭维权、AI 生成内容的权属争议、处理平台垄断与流量劫持
- [劳动与人事合规](https://www.lslby.com/services/): 围绕竞业限制、高管离职、集体劳动关系及企业组织架构调整，提供兼具商业敏感度与法律严谨性的劳动法综合服务。 典型场景：核心员工竞业限制与脱敏处理、规模性人员优化与补偿方案、劳动仲裁与诉讼应对
- [企业治理与经营](https://www.lslby.com/services/): 为科技与创新企业的日常经营和资本运作提供法律支撑，涵盖股权架构、投融资、合同管理及争议解决。 典型场景：初创企业股权设计与合伙人协议、融资交易法律尽调与文件起草、企业常年法律顾问服务

## Service Q&A
- 我可以就什么问题咨询你？ 游戏产品合规、AI 与算法合规、数据保护、知识产权、互联网企业法律顾问，以及法律科技工具相关的法律问题。
- 游戏上线前通常需要关注哪些法律问题？ 版号申请条件、内容合规（尤其是虚拟道具、抽卡机制）、用户协议和隐私政策的起草审查、未成年人保护机制、买量素材合规等。
- AI 产品什么时候需要找律师？ 越早越好，在产品设计阶段介入可以避免后期推倒重来。训练数据的合法性、模型输出的版权归属、用户协议、算法备案，这些都适合提前评估。
- 咨询前我需要准备什么？ 尽量提供产品背景、当前面临的具体问题、已有合同或规则文本。如果涉及具体争议，截图、通知、沟通记录等证据材料也很有帮助。

## Research categories
- [Industry Insights](https://www.lslby.com/research/category/Industry%20Insights/)
- [Legal Knowledge](https://www.lslby.com/research/category/Legal%20Knowledge/)
- [AI](https://www.lslby.com/research/category/AI/)
- [行业观察](https://www.lslby.com/research/category/%E8%A1%8C%E4%B8%9A%E8%A7%82%E5%AF%9F/)
- [法律知识](https://www.lslby.com/research/category/%E6%B3%95%E5%BE%8B%E7%9F%A5%E8%AF%86/)
- [Case Studies](https://www.lslby.com/research/category/Case%20Studies/)
- [案例分析](https://www.lslby.com/research/category/%E6%A1%88%E4%BE%8B%E5%88%86%E6%9E%90/)
- [Labor & Employment](https://www.lslby.com/research/category/Labor%20%26%20Employment/)
- [Latest Updates](https://www.lslby.com/research/category/Latest%20Updates/)
- [劳动与就业](https://www.lslby.com/research/category/%E5%8A%B3%E5%8A%A8%E4%B8%8E%E5%B0%B1%E4%B8%9A/)
- [最新动态](https://www.lslby.com/research/category/%E6%9C%80%E6%96%B0%E5%8A%A8%E6%80%81/)
- [Research Articles](https://www.lslby.com/research/category/Research%20Articles/)
- [研究文章](https://www.lslby.com/research/category/%E7%A0%94%E7%A9%B6%E6%96%87%E7%AB%A0/)
- [Self-developed Tools](https://www.lslby.com/research/category/Self-developed%20Tools/)
- [自制软件](https://www.lslby.com/research/category/%E8%87%AA%E5%88%B6%E8%BD%AF%E4%BB%B6/)

## Recent research
- [If You Make Money with MiniMax H3, Do You Owe MiniMax a Cut? What About Other Open Models?](https://www.lslby.com/en/research/minimax-h3-revenue-share/): A close look at the MiniMax H3 open-weight license, including copyright, revenue sharing, the US$20 million authorization threshold, territorial restrictions, prohibited uses, and how it compares with Kimi K3, GLM 5.2, DeepSeek V4, and the soon-to-be-released Qwen 3.8.
- [用Minimax H3赚钱了要给稀宇分成吗？其他开源模型呢？](https://www.lslby.com/research/minimax-h3-revenue-share/): 从著作权、商业分成、2000万美元授权门槛、地域限制和禁止用途等方面，拆解MiniMax H3开放权重协议，并比较Kimi K3、GLM 5.2、DeepSeek V4与即将开源的Qwen 3.8。
- [Deleted Company Data to Free Up Space for Freelance Work—and Got Five Years and Ten Months!](https://www.lslby.com/en/research/ai-training-data-deletion-crime/): A Beijing algorithm engineer deleted roughly 89 TB of AI training data and several text-to-3D models to use company compute for freelance work. He was sentenced to five years and ten months for sabotaging a computer information system. This article examines the conviction, criminal threshold, and calculation of losses.
- [删库腾空间接外包，最终被判五年十个月！](https://www.lslby.com/research/ai-training-data-deletion-crime/): 北京一名算法工程师为使用公司算力接外包，删除约89TB人工智能训练数据及多个文生3D模型，最终因破坏计算机信息系统罪获刑五年十个月。本文分析案件的定罪逻辑、入刑标准及损失认定。
- [WordOllama is Officially Open-Sourced! | Integrate Any AI into Word/WPS | Someone actually claimed my work isn't original?...](https://www.lslby.com/en/research/2026-07-17-wordollama-word-wps-ai/): WordOllama, a Word/WPS add-in that I've been working on on-and-off for two years, is finally officially open-sourced today!
- [WordOllama 正式开源 ！| 在 Word/WPS 中接入任意 AI | 居然有人说我非原创？……](https://www.lslby.com/research/2026-07-17-wordollama-word-wps-ai/): 一个断断续续做了两年的Word/WPS插件WordOllama，今天终于正式开源了！
- [Received a 'Social Insurance Back Payment' SMS from the Tax Bureau? How Should Employers and Employees Respond?](https://www.lslby.com/en/research/social-insurance-back-payment-sms/): With big data on income tax and social insurance now in full effect, the traditional practice of 'paying social insurance at the minimum base rate' is no longer viable. This article analyzes social insurance contribution base calculation rules, whether employers can deduct back payments from salaries, and whether employees can file labor arbitration claims.
- [收到税局的"社保补缴"短信？老板和打工人该如何应对？](https://www.lslby.com/research/social-insurance-back-payment-sms/): 个税+社保大数据正式发力，传统'按最低基数交社保'操作走不通了。本文解析社保缴费基数计算规则、公司能否倒扣员工工资、员工能否申请劳动仲裁等核心问题。
- [Your Sarcasm and Impersonations Are Becoming a Source of AI Pollution](https://www.lslby.com/en/research/satire-ai-pollution/): Explores how online impersonation and sarcastic content, when taken literally by AI, pollute training corpora and analyzes the legal infringement risks and negative impact on the information ecosystem.
- [大家的讽刺和反串，正在成为AI污染的源头](https://www.lslby.com/research/satire-ai-pollution/): 探讨网络反串和讽刺内容在AI时代被字面理解并污染AI语料库的问题，分析其法律侵权风险及对信息生态的负面影响。
- [Research on Criminal Liability and Governance Paths of AI Large Model API Reverse Proxies](https://www.lslby.com/en/research/ai-api-proxy-liability/): Analyzes three types of AI large model API reverse proxies (rule abuse, payment fraud, and protection breakthrough), explores criminal regulation paths such as the crime of destroying computer information systems, and advocates for upholding the principle of criminal restraint while adopting a cross-cutting criminal-civil rights protection strategy.
- [人工智能大模型API反向代理的刑事责任与治理路径研究](https://www.lslby.com/research/ai-api-proxy-liability/): 分析AI大模型API反向代理的三种类型（滥用规则、支付欺诈、防护突破），探讨破坏计算机信息系统罪等刑法规制路径，主张坚守刑法谦抑性原则并采用刑民交叉维权策略。

## Tools
- [WordOllama](https://wordollama.com/): 专为法律文书起草打造的 Word AI 插件。支持本地化大模型部署，确保敏感案卷数据实现 100% 本地物理隔离与绝对隐私安全。
- [AI SKILL 库](https://skillhub.lslby.com/): 专为法律行业深度定制的 AI Agent（智能体）技能指令合集，赋能法律从业者快速构建高效的自动化工作流。
- [易存讯 - 聊天记录取证助手](https://github.com/ByronLeeeee/chat_evidence_tool_web): 专为法律从业者打造的电子证据自动化处理 Web 应用。支持从录屏视频中智能提取帧截图，依托 AI 进行 OCR 识别与清洗，并对长图智能分割，一键生成符合司法审查标准的规范化 PDF 证据清单。
- [LawVault](https://github.com/ByronLeeeee/lawvault): 离线部署的中国法律法规检索引擎。支持无缝对接任意主流 AI 接口（API），为构建专属的法律垂直领域 RAG（检索增强生成）知识库提供底层数据支撑。
- [Privatrans](https://privatrans.lslby.com/): 极致注重数据安全的跨平台 AI 翻译客户端。支持直连本地离线大模型，保障敏感文本的绝对隐私，全面覆盖 Android、Windows 及 macOS (Apple Silicon) 平台。

## Course material series
### 李解 AI
从律师的真实工作出发，拆解 AI 工具、Agent 与法律科技：不只解释概念，更关注它们如何进入具体的工作流。
- [从问 AI，到让 AI 交付](https://www.lslby.com/slides/ai-law-firm-training/): 面向律师与律所团队的 AI 基础培训。从 Chatbot 的能力边界出发，逐步讲解 Agent、Markdown、MCP、Skill 与主流模型选择。（37 页）
### Li Explains AI (English)
AI tools, agents, and legal technology explained through the real work of lawyers—with an emphasis on practical workflows, not just concepts.
- [From Asking AI to Getting Deliverables](https://www.lslby.com/en/slides/ai-law-firm-training/): AI foundations for lawyers and law-firm teams, moving from the limits of chatbots to agents, Markdown, MCP, Skills, and practical model choices. (37 slides, English)

## Optional
- [完整 LLM 索引](https://www.lslby.com/llms-full.txt): 全量文章摘要、分类与旧链接索引
- [API Catalog](https://www.lslby.com/.well-known/api-catalog): RFC 9727 服务发现目录
- [RSS](https://www.lslby.com/rss.xml): 最新文章订阅
- [Sitemap](https://www.lslby.com/sitemap-index.xml): 搜索引擎站点地图