流式AI检索问答技能

通用流式AI检索问答技能 — 为任意行业应用提供四步流式分析交互界面。 触发场景：用户输入关键词 → AI自动执行：理解意图 → 检索知识库 → 流式生成 → 来源标记 → 完整回答。 当需要实现以下任意场景时激活： (1) AI搜索框 / 智能咨询组件重构 (2) 知识库问答（医疗/法律/金融/教育等垂直领域）...

This package is internally consistent: it provides React/Tailwind UI components and prompt templates for streaming RAG-style answers. Before using it in production, do these things: (1) Never embed real API keys in frontend code — route streaming calls through a backend proxy that injects credentials server-side and enforces rate limits and scope. (2) Review and adapt the prompts and disclaimers for regulated domains (medical/legal/financial); add stronger disclaimers or human-in-the-loop if required by policy. (3) Validate the source-parsing logic against the kinds of model output you expect so the UI doesn't surface malformed links. (4) Ensure your streaming endpoint supports CORS and SSE safely, and that logs do not leak user-submitted sensitive data. (5) Limit API key scopes and rotate keys; enforce rate limits and monitoring on the proxy. If you want, I can point out exact lines in the code that would need changing to move the streamAI call to a secure backend.

Type: OpenClaw Skill Name: stream-ai-answer Version: 1.0.0 The skill bundle provides a legitimate UI template and implementation guide for a streaming AI response interface across various industries (medical, legal, etc.). The code in assets/AIAnalysisCard.tsx and references/frontend-pattern.md consists of standard React components and fetch-based streaming logic without any evidence of data exfiltration, malicious execution, or prompt injection.