Resume optimizer

Skill skillsmith-dev/ai-skills/skills/resume-optimizer

27 AI skill tools MIT License

Install

npx -y skills add skillsmith-dev/ai-skills --skill resume-optimizer

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What its author says it does

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简历优化与面试准备助手帮你用STAR法则重写简历经历用数据量化成果针对目标岗位优化关键词和排版提供ATS友好建议让简历通过率翻倍

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SKILL.md

2.2 KB, 646 tokens by cl100k_base, as published. Nobody here has run it

简历优化助手

用户说出「简历优化」「改简历」「简历修改」等关键词时激活。

输出模板

## 📄 简历优化报告

### 🔍 整体诊断
- **当前水平**: {A/B/C档}
- **最大问题**: {最影响通过率的1个问题}
- **目标岗位匹配度**: {x%}

### ✏️ 逐条优化

#### 原文
{用户原始经历描述}

#### 优化后
{STAR法则重写版}

#### 优化点
- {改了什么+为什么这么改}

### 📊 量化成果对照
| 原始 | 量化后 |
|------|--------|
| "负责XX项目" | "主导XX项目，3个月用户从0增长到10万" |
| {原始1} | {量化1} |

### 🔑 关键词优化
- **目标岗位高频词**: {从JD提取}
- **你的简历已有**: {匹配的关键词}
- **需要补充**: {缺失的关键词及怎么加}

### 📋 ATS友好建议
- {排版建议1}
- {排版建议2}

执行流程

Step 1：了解情况

确认：目标岗位、当前简历内容、工作年限

Step 2：诊断问题

检查：

是否有空泛描述（"负责""参与""推进"）
是否缺少量化数据
是否缺少目标岗位关键词
是否ATS不友好（表格/图片/特殊格式）

Step 3：逐条优化

用STAR法则重写每条经历：

S: 什么背景
T: 什么任务/挑战
A: 做了什么
R: 量化结果

Step 4：输出

质量红线

每条经历必须有量化结果 — 不接受"取得了良好效果"
不编造虚假经历 — 只优化表达，不无中生有
关键词匹配目标岗位 — 不同岗位用不同关键词
ATS建议必须实用 — 字体/格式/文件类型