菜单
Build, refine, and debug the React/Vite frontend for Lumina. Use when editing files under client/src or client/package.json, changing chat UX, landing page content, auth flows, routing, theme behavior, markdown rendering, animations, responsive layout, or frontend API wiring.
默认使用会先检查来源的 Prompt；你也可以切换为直接命令，或下载本地副本。
决定是否安装前，请先阅读 SKILL.md，以及 SkillsMP 当前展示的配套文件。
基于 SOC 职业分类
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
直接命令不会经过审查 Prompt；运行前请先检查来源。
npx skills add https://github.com/hoangsonww/AI-RAG-Assistant-Chatbot --skill lumina-frontend-ui命令会保持在同一行。复制前请横向滚动并检查完整内容。
想先保存到本地？可下载 SkillsMP 当前能够提供的文件。
正在显示 SKILL.md
| name | lumina-frontend-ui |
| description | Build, refine, and debug the React/Vite frontend for Lumina. Use when editing files under client/src or client/package.json, changing chat UX, landing page content, auth flows, routing, theme behavior, markdown rendering, animations, responsive layout, or frontend API wiring. |
Use this skill for frontend tasks in client/. Keep changes aligned with Lumina's existing visual language: animated, polished, content-rich, and responsive rather than generic dashboard UI.
references/component-map.md before editing when you need to locate the right page, component, or client-side service.references/validation.md before finishing when frontend behavior, build health, or API coupling changed.client/src/pages/Home.tsx plus client/src/components/ChatArea.tsx and client/src/services/api.ts.client/src/App.tsx.client/src/pages/LandingPage.tsx as intentionally branded and heavily customized. Preserve its personality unless the task explicitly asks for a redesign.openapi.yaml in the same task when feasible.lumina-rag-knowledge or lumina-backend-api instead of forcing a frontend-only patch.npm run build in client/ after meaningful frontend changes.npm test in client/ as a placeholder, not as evidence of coverage.Work on Lumina deployment and infrastructure assets. Use when editing terraform/, aws/, docker-compose.yml, DEPLOYMENT.md, ADVANCED_DEPLOYMENTS.md, agentic_ai/deployments/, or other files related to Docker, Terraform, AWS or Azure rollout behavior, environment wiring, and release automation.
Work on the Python multi-agent pipeline and MCP client in agentic_ai. Use when editing files under agentic_ai/, changing agent orchestration, configuration loading, MCP client connectivity, async execution flow, pipeline startup commands, or cloud deployment wrappers for the Python service.
Develop and maintain the standalone Lumina MCP server. Use when editing files under mcp_server/, adding or modifying tools, resources, prompts, middleware, configuration, or transport behavior for the Model Context Protocol server.