菜单
对 GitHub Trending 仓库或单个 GitHub repo 输出逐仓库同等深度的中文分析，覆盖详细 TL;DR、核心特性、痛点到方案到效果、证据来源和快速试用路径。 Use when: 用户提到 GitHub Trending、热门仓库、想快速读懂某个 repo、想知道它解决什么问题、为什么火、有哪些核心特性，或要求做榜单速报。
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。
基于 SOC 职业分类
generate production-grade interview question banks from a role, jd, technology direction, project, or business system. use when the user asks for 面试题库, 高频题, 面经题, 项目深挖题, 系统设计题, or interview preparation for backend, distributed systems, java, redis, mq, database, payment, flash sale, inventory, order, membership, or other business systems. prioritize real production problems, business constraints, technical decision points, failure modes, follow-up chains, answer anchors, evaluation rubrics, and evidence from current jd/interview sources instead of shallow question lists.
analyze current job market demand for a user-specified career direction using real job descriptions from the last 30 days. use when the user asks to evaluate a role, technology direction, career path, market demand, salary value, job requirements, or skill gap based on boss直聘, lagou, liepin, linkedin, indeed, company career pages, or user-provided jd text. must collect and analyze at least 6 valid recent jds before making strong conclusions; every conclusion must be grounded in jd evidence.
orchestrate a personal ai-era growth operating system for daily judgment training, weekly theme planning, information intake, scenario analysis, language output, market calibration, and social practice. use when the user asks to run, design, review, or maintain a daily mustdo system; build a personal ability operating system; plan weekly/monthly learning themes; coordinate hacker news, github trending, track awesome list, scenario harness, boss/job-market review, or workplace/social-practice reflection; or convert scattered self-improvement tasks into a closed-loop training workflow.
analyze technical decision points in a business scenario or system design. use when the user asks to identify, compare, review, or document key technical decisions for systems such as flash sale, payment, order fulfillment, inventory, messaging, recommendations, workflows, risk control, or other business systems. especially useful for turning a scenario into decision points, trade-off matrices, failure modes, recommended choices, architecture constraints, and coding-agent-ready implementation guidance.
以“解决方案架构师 + 人类判断力教练 + harness 工程师”的复合视角，把秒杀、IM、清结算、订单履约、推荐、内容社区等业务场景拆成结构化架构分析、人类判断文档、难点深拆和可执行 prompt 包。Use when: 用户要求系统设计、业务场景拆解、架构方案、harness prompt、让 Claude Code/Codex/Cursor 实现，或希望用 AI 作为工程杠杆但不外包判断力。输出强调人类必须亲自拥有的问题定义、不变量、取舍、失败模式、验收标准和复盘问题，再把确认后的判断压成 agent 可执行契约。
将一段口语化、碎片化的每日热点串讲整理成结构化中文分析文档，重点识别热点叙事与关键事实之间的信息差、背景缺口、误读点和后续观察指标。 Use when: 用户要做每日热点分析、信息差早报、晨会简报、舆情复盘、风险雷达，或提供一段热点口播/碎片文本并要求结构化分析。
| name | github-trending-quick-deep-analyzer |
| description | 对 GitHub Trending 仓库或单个 GitHub repo 输出逐仓库同等深度的中文分析，覆盖详细 TL;DR、核心特性、痛点到方案到效果、证据来源和快速试用路径。 Use when: 用户提到 GitHub Trending、热门仓库、想快速读懂某个 repo、想知道它解决什么问题、为什么火、有哪些核心特性，或要求做榜单速报。 |
| user-invocable | true |
| metadata | {"author":"tense-i","version":"1.0","language":"zh-CN"} |
用这个 skill 快速读懂 Trending 仓库，重点是“仓库是什么、怎么试、解决了什么痛点、证据在哪里”。
对每个仓库都给出三类稳定信息：
用户没说时使用：
dailyN：5【示意】。按 references/output-template.md 输出。每个仓库必须包含：
references/output-template.md: 逐仓库输出模板与自检要求