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Writing

JD-Optimized Resume Rewriting

by coinluu

JD-Optimized Resume Rewriting is a Writing skill for Claude Code, published by coinluu in resume-jd-optimizer-cn.

154 stars6 forkson coinluu/resume-jd-optimizer-cnAdded 2026/07/16+3% in starsRepository updated 2026/06/14
ai-agentatscareercareer-toolschatgptchinachinesecodexcvinterview-prepjd-analysisjob-searchllmprompt-engineeringrecruitmentresumeresume-optimizerskill
Install in seconds
Install JD-Optimized Resume Rewriting
Copy JD-Optimized Resume Rewriting into your Claude Code skills folder. Run the command in your terminal, or review the source on GitHub before installing.
terminal
npx degit https://github.com/coinluu/resume-jd-optimizer-cn ~/.claude/skills/resume-jd-optimizer-cn

Requires Node.js. Downloads this skill only — not the rest of the repository — into your Claude Code skills folder.

Without Node.js

git clone https://github.com/coinluu/resume-jd-optimizer-cn.git

Clones the whole repository, then copy the skill’s own directory into your skills folder yourself.

In this catalog

Source file
SKILL.md in coinluu/resume-jd-optimizer-cn
Installs to
~/.claude/skills/resume-jd-optimizer-cn
Collection
The only skill cataloged from this repository
Category
Writing1361 skills

What JD-Optimized Resume Rewriting does

Optimizes Chinese resumes against a target job description by mapping evidence, diagnosing gaps, and generating ATS-friendly, HR-readable, interview-ready tailored resumes and job application materials.

JD-Optimized Resume Rewriting is cataloged under Writing on DirSkills. JD-Optimized Resume Rewriting comes from a repository tagged ai-agent, ats, career, career-tools and chatgpt.

Documentation

README

国内求职者简历 JD 优化

目标

把目标 JD 的要求映射到用户可验证的真实经历,生成适合中国大陆招聘场景、ATS 可读、HR 易判断、面试可自洽的定制简历。不要只润色语言。

先遵守的硬规则

  1. 只使用用户简历、用户补充回答和明确标注的合理估算。
  2. 不编造学校、公司、岗位、项目、证书、工具、职责、数据或 AI/RAG/Agent 经历。
  3. 把信息标记为 已确认待确认模型推断;只有 已确认 可进入最终简历。
  4. 信息不足会影响关键结论时,先输出“为了避免编造,我还需要你补充以下信息”,再提出不超过 8 个高价值问题。
  5. 不为关键词匹配堆词;关键词必须绑定真实行动或成果。
  6. 每条重写经历必须能被面试追问验证。无法讲清的内容必须删除或降级表达。
  7. 评分是当前材料质量诊断,不是 ATS、面试或录用概率。
  8. 先判定输入完整度,再执行对应阶段;不得用模型推断补齐缺失输入。
  9. 用户要求造假时,立即停止评分、重写、ATS 版和最终报告生成,只能拒绝并提供真实替代路径。
  10. “包装得高级、亮眼、专业”等请求默认解释为提升信息密度、结构和专业准确性,不得自动提高职责、职级、决策权或结果强度。

适用与不适用

适用:针对明确 JD 优化简历、转岗证据映射、投递前检查、Boss/猎头介绍、面试追问准备、多 JD 定制版本。

不适用:虚构经历、伪造证明、单纯视觉排版、没有目标方向的万能简历、替用户承诺无法证明的成果。

输入要求

优先收集:完整 JD、现有简历、求职目标、当前背景、是否转行、作品或项目链接、投递反馈。提醒用户脱敏电话、身份证、住址、客户机密和未公开数据。

若缺少 JD,只能做基础诊断并明确说明不能完成岗位匹配评分。若缺少简历,只能解析 JD 并生成素材采集问题。

This is the opening of the README. Read the full README on GitHub.

Frequently asked about JD-Optimized Resume Rewriting

  • How does JD-Optimized Resume Rewriting compare to other Writing skills?

    JD-Optimized Resume Rewriting ranks #1206 by stars among the 1361 Writing skills in this catalog. The most-starred ones next to it are Article Writing, Social Media Content Calendar and Knowledge Comic Creator. DirSkills ranks by the star count of the repository each skill ships in, so that order reflects how popular those repositories are rather than any review of JD-Optimized Resume Rewriting against them. Open each page to compare what they document and how they install.