feat: add docmd-search local semantic search page

- Create docs/search.md featuring premium landing layout for docmd-search
- Incorporate bespoke vector-search sandbox visual mockup and features
- Add internationalisation keys in English (en.json) and Chinese (zh.json)
- Refactor scripts/rewrite-links.js to recursively find and rewrite links across all generated HTML pages (supporting search/index.html)

Author: mgks

assets/i18n/en.json

@@ -111,5 +111,21 @@
   "footer.liveEditor": "Live Editor",
   "footer.releases": "Releases",
   "footer.sponsor": "Sponsor",
-  "footer.license": "MIT License"
+  "footer.license": "MIT License",
+  "search.hero.badge": "docmd-search alpha",
+  "search.hero.title": "Local Semantic Search.<br>Zero API keys. 100% Private.",
+  "search.hero.sub": "Enable context-aware search results powered by local embeddings in the browser. Zero network dependencies, zero costs, instant client-side retrieval.",
+  "search.hero.cta": "Get Started",
+  "search.hero.metric.local": "Local Embeddings",
+  "search.hero.metric.private": "100% Private",
+  "search.hero.metric.ai": "AI-Powered",
+  "search.hero.metric.cost": "Zero Cost",
+  "search.features.title": "Private AI-Powered Search",
+  "search.features.sub": "Bring modern vector search directly to your static docs without third-party services.",
+  "search.feature.local.title": "Local Vector Models",
+  "search.feature.local.desc": "Uses lightweight ONNX models executing directly on the client side. No data ever leaves the user's browser.",
+  "search.feature.semantic.title": "Semantic Intent",
+  "search.feature.semantic.desc": "Understands queries conceptually. Searching 'authentication' yields results for 'sign-in' and 'login' automatically.",
+  "search.feature.sandbox.title": "Interactive CLI Sandbox",
+  "search.feature.sandbox.desc": "Run the CLI with the --ui flag to test embeddings, adjust text chunking size, and visually inspect search scores."
 }

assets/i18n/zh.json

@@ -111,5 +111,21 @@
   "footer.liveEditor": "在线编辑器",
   "footer.releases": "版本发布",
   "footer.sponsor": "赞助",
-  "footer.license": "MIT 许可证"
+  "footer.license": "MIT 许可证",
+  "search.hero.badge": "docmd-search alpha",
+  "search.hero.title": "本地语义搜索。<br>无需 API 密钥。100% 隐私安全。",
+  "search.hero.sub": "在浏览器中启用基于本地嵌入（embeddings）的上下文感知搜索。零网络依赖，零成本，即时客户端检索。",
+  "search.hero.cta": "开始使用",
+  "search.hero.metric.local": "本地向量模型",
+  "search.hero.metric.private": "100% 隐私安全",
+  "search.hero.metric.ai": "AI 驱动",
+  "search.hero.metric.cost": "零额外成本",
+  "search.features.title": "私有 AI 驱动搜索",
+  "search.features.sub": "无需任何第三方服务，将现代向量搜索直接带入您的静态文档中。",
+  "search.feature.local.title": "本地向量模型",
+  "search.feature.local.desc": "使用轻量级 ONNX 模型直接在客户端运行。任何数据都不会离开用户的浏览器。",
+  "search.feature.semantic.title": "语义意图识别",
+  "search.feature.semantic.desc": "概念性地理解查询意图。例如搜索“authentication”时，能自动匹配“sign-in”和“login”的结果。",
+  "search.feature.sandbox.title": "交互式 CLI 沙盒",
+  "search.feature.sandbox.desc": "使用 --ui 参数运行 CLI，即可可视化测试向量匹配分数并实时微调分块大小。"
 }