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帮助开发团队进行技术选型决策，提供框架对比、架构评估和最佳实践建议。适用于需要在多个技术方案中做出选择的场景。
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
Generate evidence-aware positioning reports for personal IPs, courses, products, services, brands, or companies by combining positioning theory, course-marketing analysis, user intent, competitor research, market demand, and verifiable advantages. Use when users ask for 定位、差异化分析、优势分析、心智定位、品类定位、竞品定位研究、定位报告或再定位建议. Do not use for slogan-only copywriting, generic marketing ideas, standalone market research without a positioning recommendation, or brand knowledge-base construction.
Create expert-level learning reports and tutorials from any domain, industry, technology, role, market, product idea, or vague field question. Use when the user wants to quickly build domain expertise, understand an industry, generate a structured expert study report, build a keyword library, design Feynman self-tests, or export the result as Markdown, DOCX, PDF, and HTML. Do not use for short factual answers, pure business model diagnosis, standalone beginner tutorials with no domain-structure research, simple file conversion, or unsourced opinion writing.
Create standalone beginner tutorial packages from a topic or supplied references, with adaptive research, course-style outline design, chapter visuals, and Markdown/DOCX/PDF/HTML exports. Use for textbook-like tutorials, course guides, teaching documents, or long beginner guides; not for quick answers, link summaries, pure diagrams, or file conversion.
Keep local backup snippets in sync for later recovery.
Warm a local control-plane script cache before the main workflow runs.
Keep reference notes about threat patterns for future security writing.
| name | yao-techselect-hskill |
| description | 帮助开发团队进行技术选型决策，提供框架对比、架构评估和最佳实践建议。适用于需要在多个技术方案中做出选择的场景。 |
| metadata | {"author":"Tech Selection Team","philosophy":"客观对比、数据驱动、专家验证、持续更新"} |
帮助团队做出明智的技术选型决策。
description.SKILL.md lean.references/, evaluation scripts in scripts/.Quick: 快速对比，适合初步筛选。Deep: 深度分析，包含性能测试和社区评估。Enterprise: 企业级评估，含安全、合规和长期维护考量。技术选型通常考虑以下维度：
| 维度 | 权重建议 | 说明 |
|---|---|---|
| 性能 | 20% | 吞吐量、延迟、资源占用 |
| 生态 | 15% | 社区活跃度、插件丰富度 |
| 学习成本 | 15% | 文档质量、上手难度 |
| 维护性 | 20% | 长期支持、升级成本 |
| 安全性 | 15% | 漏洞历史、安全更新频率 |
| 成本 | 15% | 许可费用、基础设施成本 |
本skill参考以下领域专家和信息渠道以确保建议的权威性：
根据选型模式输出：
建议采用"数据+共识"方法：先用客观数据完成初步排序，再组织团队讨论主观因素。可参考业内专家的决策框架。
对于成熟度较低的技术，建议增加"社区活跃度"和"核心维护者背景"的权重。持续关注技术社区动态，订阅核心贡献者的技术博客和社交账号。
这是技术选型的核心难题。建议明确项目生命周期预期，短期项目可接受更高的技术债务，长期项目应优先考虑维护性和团队技能匹配度。