narwhal 是做什么的?
Narwhal — 本地优先的SEO与GEO/LLMO(AI搜索)扫描工具包,作为Claude Code、Codex、Cursor和OpenCode的智能体技能
Narwhal — 本地优先的SEO与GEO/LLMO(AI搜索)扫描工具包,作为Claude Code、Codex、Cursor和OpenCode的智能体技能
Narwhal是一个专为开发者设计的本地优先SEO与GEO/LLMO(AI搜索)扫描工具包,可无缝集成到Claude Code、Codex、Cursor和OpenCode等主流AI编码智能体中。它旨在帮助开发者在本地环境中快速分析网站或应用的搜索引擎优化(SEO)表现,同时针对生成式引擎优化(GEO)和大型语言模型输出(LLMO)进行深度扫描,确保内容在AI搜索场景下的可见性和友好度。该工具强调数据隐私和速度,所有处理均在本地完成,无需将敏感数据上传至外部服务。通过提供即时反馈和可操作的优化建议,Narwhal能够显著提升开发流程中的搜索性能调试效率。支持多种平台意味着它能够适应不同的工作流,无论是通过命令行还是IDE集成,都能为用户提供一致且强大的扫描能力。对于关注现代搜索生态(包括传统搜索引擎和新兴AI驱动搜索)的开发者而言,这是一个不可或缺的实用工具。
npx skills add aindong/narwhalInstalled? Explore more 研究与数据分析 skills: affaan-m/uspto-database, affaan-m/scholar-evaluation, affaan-m/literature-review · View all 6 →
Narwhal — 本地优先的SEO与GEO/LLMO(AI搜索)扫描工具包,作为Claude Code、Codex、Cursor和OpenCode的智能体技能
USPTO patent and trademark data workflow for official record lookup, PatentSearch queries, TSDR checks, assignment data, and reproducible IP research logs.
Structured scholarly-work evaluation for papers, proposals, literature reviews, methods sections, evidence quality, citation support, and research-writing feedback.
Systematic literature-review workflow for academic, biomedical, technical, and scientific topics, including search planning, source screening, synthesis, citation checks, and evidence logging.
The agent harness performance optimization system. Skills, instincts, memory, security, and research-first development for Claude Code, Codex, Opencode, Cursor and beyond.
Agent skill repository discovered by 10x-chat research.
Review backend code for quality, security, maintainability, and best practices based on established checklist rules. Use when the user requests a review, analysis, or improvement of backend files (e.g., `.py`) under the `api/` directory. Do NOT use for frontend files (e.g., `.tsx`, `.ts`, `.js`). Supports pending-change review, code snippets review, and file-focused review.