Resume Assistant

<p align="center">
  <h1 align="center">📝 简历助手 (Resume / CV Assistant)</h1>
  <p align="center">
    <strong>AI 驱动的 clawbot 技能 —— 简历（Resume / CV）润色、职位定制、多格式导出、专业评分，一站式搞定。</strong>
  </p>
  <p align="center">
    <a href="./LICENSE"><img src="https://img.shields.io/badge/许可证-MIT-blue.svg" alt="许可证: MIT"></a>
    <img src="https://img.shields.io/badge/版本-1.0.0-green.svg" alt="版本: 1.0.0">
    <img src="https://img.shields.io/badge/平台-clawbot-purple.svg" alt="平台: clawbot">
    <img src="https://img.shields.io/badge/语言-中文%20%7C%20English-orange.svg" alt="语言: 中文 | English">
  </p>
  <p align="center">
    <a href="./README.md">🇺🇸 English</a> · <a href="./SKILL_ZH.md">📖 技能规范</a> · <a href="./examples/usage.md">💡 使用示例</a>
  </p>
</p>

---

## ✨ 核心功能

| 功能 | 描述 |
|------|------|
| 🔍 **简历润色** | 40+ 项检查清单，涵盖语法、动词、量化指标、排版等全方位审查 |
| 🎯 **职位定制** | 针对目标职位进行差距分析和关键词优化，提升匹配度 |
| 📤 **多格式导出** | 支持 5 种格式（Word、Markdown、HTML、LaTeX、PDF）× 4 种专业模板 |
| 📊 **专业评分** | 100 分制 5 维度评估，明确优势、短板和改进计划 |

---

## 🚀 快速开始

### 直接对话即可！

不需要记忆任何命令 —— 直接描述你的需求：

```
💬 "帮我写一份软件工程师的简历"
💬 "润色我的简历，修复所有问题"
💬 "优化我的简历，让它通过 ATS 筛选"
💬 "根据这个职位描述定制我的简历：[粘贴 JD]"
💬 "把我的简历转成 PDF"
💬 "给我的简历打个分，告诉我怎么改进"
💬 "我的简历有什么问题？"
💬 "这是我的简历，帮我看看"
```

English works too:
```
💬 "Create a resume for a software engineer position"
💬 "Optimize my resume for ATS"
💬 "Tailor my resume for this job description: [paste JD]"
💬 "Score my resume and tell me how to improve"
```

助手会理解你的意图，自动路由到正确的工作流：

| 你说 | 助手做什么 |
|------|-----------|
| "帮我写一份 [职位] 的简历" | 询问你的背景信息 → 生成定制简历 |
| "润色 / 修改 / 优化我的简历" | 执行 40+ 项检查 → 返回润色后的版本 |
| "优化 ATS" | 检查 ATS 兼容性 → 优化关键词和格式 |
| "根据这个 JD 定制：..." | 分析 JD → 差距分析 → 定制简历 |
| "转成 PDF / Word / ..." | 用专业模板导出为指定格式 |
| "给简历打分 / 评估 / 怎么样" | 100 分制评分 → 优势与改进方案 |
| "这是我的简历，帮我看看" | 先评分 → 再建议后续步骤 |

### 斜杠命令（精确控制）

如果需要更精细的控制，也可以直接使用斜杠命令：

```
/resume polish
请帮我润色以下简历：

张三
高级前端工程师 | 5年经验
技能：JavaScript, React, Vue, Node.js
...
```

### 命令一览

| 命令 | 功能 | 必需输入 |
|------|------|----------|
| `/resume polish` | 润色简历，修复错误 | 简历内容 |
| `/resume customize` | 针对目标职位定制 | 简历内容 + 职位描述 |
| `/resume export` | 导出为 Word/MD/HTML/LaTeX/PDF | 简历内容 + 目标格式 |
| `/resume score` | 评分并给出改进方案 | 简历内容 |

---

## 📖 工作原理

简历助手是一个 **clawbot 技能（skill）**—— 一套结构化的提示词包，可以被任何 AI Agent 加载和执行。它支持 Resume 和 CV 两种格式，包含：

- **角色定义文件** —— 设定 AI 的角色与质量标准
- **命令提示词** —— 每个功能的详细指令
- **模板文件** —— 简历样式和导出格式模板
- **技能清单** （`skill.json` / `skill.yaml`）—— 描述命令、参数和配置

```
用户输入 ─┬─ 斜杠命令 ──────────► 命令路由 ──► 加载提示词 ──► LLM 处理 ──► 结构化输出
          │                          │
          └─ 自然语言 ──► 意图识别 ──┘
                                     │
              ├── polish / "润色简历"     → prompts/polish.md
              ├── customize / "定制简历"  → prompts/customize.md
              ├── export / "转成PDF"     → prompts/export.md
              └── score / "给简历打分"    → prompts/score.md
```

---

## 🏗️ 项目结构

```
resume-assistant/
├── skill.json              # 技能清单（JSON 格式）
├── skill.yaml              # 技能清单（YAML 格式）
├── SKILL.md                # 技能规范（英文）
├── SKILL_ZH.md             # 技能规范（中文）
├── LICENSE                 # MIT 开源协议
│
├── prompts/                # AI 提示词文件
│   ├── system.md           # 系统级提示词（始终加载）
│   ├── polish.md           # 润色命令提示词
│   ├── customize.md        # 定制命令提示词
│   ├── export.md           # 导出命令提示词
│   └── score.md            # 评分命令提示词
│
├── templates/              # 简历和导出模板
│   ├── professional.md     # 经典专业风格
│   ├── modern.md           # 现代创意风格
│   ├── minimal.md          # 简洁极简风格
│   ├── academic.md         # 学术研究风格
│   └── export/
│       ├── resume.html     # HTML 导出模板
│       └── resume.tex      # LaTeX 导出模板
│
└── examples/               # 示例简历和使用指南
    ├── usage.md            # 详细使用示例
    ├── sample-resume-en.md # 英文示例简历
    ├── sample-resume-zh.md # 中文示例简历
    └── sample-resume-weak.md # 弱简历示例（用于评分演示）
```

---

## 🔧 集成指南

### 方式一：在 AI Agent 中注册为技能

```json
{
  "skills": [
    {
      "name": "resume-assistant",
      "path": "./skills/resume-assistant",
      "manifest": "skill.json"
    }
  ]
}
```

### 方式二：通过代码构建提示词

```python
ROLE_SYS = "system"    # LLM message role constant
ROLE_USR = "user"      # LLM message role constant

def build_prompt(command, args):
    persona_prompt = load_file("prompts/system.md")
    command_prompt = load_file(f"prompts/{command}.md")

    combined = persona_prompt + "\n\n" + command_prompt
    messages = [
        {"role": ROLE_SYS, "content": combined},
        {"role": ROLE_USR, "content": args["resume_content"]}
    ]
    return messages
```

### 方式三：通过 REST API 调用

```bash
curl -X POST https://your-agent-api.com/skills/resume-assistant/polish \
  -H "Content-Type: application/json" \
  -d '{
    "resume_content": "你的简历内容...",
    "language": "zh"
  }'
```

### 方式四：在 LangChain / LlamaIndex 中使用

```python
from langchain.tools import Tool

resume_tools = [
    Tool(
        name="resume_polish",
        description="润色和优化简历，40+ 项检查清单",
        func=lambda input: agent.run_skill(
            "resume-assistant", "polish",
            {"resume_content": input, "language": "zh"}
        )
    ),
    # ... 更多工具：score, customize, export
]
```

> 📖 完整集成细节请查看 [技能规范文档](./SKILL_ZH.md)

---

## 📋 推荐工作流

```
┌─────────────────┐
│    从这里开始     │
└────────┬────────┘
         ▼
   已有简历？ ──是──► /resume score（了解当前水平）
         │                     │
         否                    ▼
         │             /resume polish（修复问题）
         ▼                     │
  用模板写一份                  ▼
         │             有目标职位？
         ▼                │        │
  /resume polish          是       否
         │                │        │
         │                ▼        │
         │        /resume customize│
         │                │        │
         └────────────────┼────────┘
                          ▼
                   /resume export ──► Word / Markdown / HTML / LaTeX / PDF
```

**实用建议：**

1. 🎯 **先评分** —— 如果已有简历，先了解现状
2. ✨ **先润色** —— 先修复基础问题，再做职位定制
3. 🔄 **每个职位都定制** —— 不要一份简历投所有岗位
4. 📊 **再次评分** —— 润色和定制后检查提升效果
5. 📤 **最后导出** —— 先把内容打磨好，再处理格式
6. 📝 **用 Markdown 工作** —— 可以无缝转换为所有其他格式

---

## 🎨 模板风格

| 模板 | 风格 | 适用场景 |
|------|------|----------|
| `professional` | 经典深蓝，衬线标题 | 金融、咨询、法务 |
| `modern` | 青色强调，创意布局 | 科技、初创、市场 |
| `minimal` | 简洁单色，内容紧凑 | 资深岗位、工程师 |
| `academic` | 正式衬线，支持多页 | 高校教职、科研、博士 |

---

## 🌏 语言支持

- **英语 (en)** —— 默认语言，针对国际求职市场优化
- **中文 (zh)** —— 完整 CJK 支持，适配中国求职习惯

中文特色功能：
- 📸 HTML/LaTeX 导出中的 CJK 字体处理
- 🇨🇳 中国简历惯例（照片、年龄、学历优先展示）
- ✏️ 半角/全角标点符号自动规范化
- 🔤 中英文混排间距优化

---

## 📊 评分维度

使用 `/resume score` 时，你的简历将从 5 个维度进行评估：

| 维度 | 权重 | 评估内容 |
|------|------|----------|
| 内容质量 | 30 分 | 成果展示、量化指标、相关性 |
| 结构与排版 | 25 分 | 布局层次、留白、视觉效果 |
| 语言与语法 | 20 分 | 动词使用、时态、语法规范 |
| ATS 优化 | 15 分 | 关键词、可解析性、标准标题 |
| 影响力与印象 | 10 分 | 整体印象、独特价值主张 |

评级标准：**A+ (90-100)** · **A (80-89)** · **B (70-79)** · **C (60-69)** · **D (50-59)** · **F (<50)**

---

## 🤝 参与贡献

欢迎贡献！你可以通过以下方式参与：

- 🐛 通过 Issues 报告问题或建议新功能
- 📝 优化提示词以提升 AI 输出质量
- 🎨 添加新的简历模板
- 🌍 增加更多语言支持
- 📖 完善文档

---

## 📄 开源协议

本项目基于 [MIT 许可证](./LICENSE) 开源。

# 📝 Resume / CV Assistant

> AI-powered clawbot skill for resume & CV polishing, job customization, multi-format export, and professional scoring.
**Version:** 1.0.0 · **License:** MIT · **Repository:** [github.com/Wscats/resume-assistant](https://github.com/Wscats/resume-assistant)

---

## Overview

Resume / CV Assistant is a clawbot skill that helps job seekers create, refine, and optimize their resumes and CVs, while adding comprehensive checklist review, scoring, and multi-format export that neither project offers alone.

---

## Usage in AI Agent

### Quick Start

Resume / CV Assistant is a standard clawbot skill that can be loaded and invoked by any compatible AI Agent. Here are different integration approaches.

### 💬 Natural Language (Recommended)

You don't need to memorize any commands — simply describe what you need:

```
💬 "Create a resume for a software engineer position"
💬 "Polish my resume and fix any issues"
💬 "Optimize my resume for ATS"
💬 "Tailor my resume for this job description: [paste JD]"
💬 "Convert my resume to PDF"
💬 "Score my resume and tell me how to improve"
💬 "What's wrong with my resume?"
💬 "Here's my resume, can you help?"
```

The assistant understands your intent and automatically routes to the right workflow:

| You say | Assistant does |
|---------|---------------|
| "Create a resume for [role]" | Asks for your background → builds a tailored resume |
| "Polish / Fix / Improve my resume" | Runs 40+ checklist review → returns polished version |
| "Optimize for ATS" | Checks ATS compatibility → optimizes keywords & format |
| "Tailor for this JD: ..." | Analyzes JD → gap analysis → customized resume |
| "Convert to PDF / Word / ..." | Exports to chosen format with professional template |
| "Score / Rate / Evaluate my resume" | 100-point scoring → strengths & improvement plan |
| "Here's my resume, help?" | Scores first → suggests next steps |

#### Example Conversations

**Creating a new resume:**
```
You:   Create a resume for a frontend engineer position at a startup

Bot:   I'd be happy to help! To get started, could you share:
       1. Your work experience (companies, roles, dates, key achievements)
       2. Education background
       3. Technical skills
       4. Any specific job posting you're targeting? (optional)

You:   I have 3 years at Shopify working on React...

Bot:   Here's your tailored resume:
       [generates complete resume]
       
       Would you like me to score, polish, or export it?
```

**Quick improvement:**
```
You:   Here's my resume, what do you think?
       [pastes resume]

Bot:   📊 Resume Score: 68/100 (Grade: C)
       Top 3 Issues:
       1. ❌ No quantified achievements
       2. ⚠️ Weak action verbs
       3. ⚠️ Missing keywords for target role
       
       Would you like me to polish it now?

You:   Yes, polish it

Bot:   [runs full polish with 40+ checklist items]
```

**Job-specific tailoring:**
```
You:   Tailor my resume for this job description:
       Senior Backend Engineer at Stripe
       Requirements: Go, distributed systems, payment APIs...

Bot:   🎯 Job Analysis Complete
       📊 Current Match: 62% → After Optimization: 89%
       [generates tailored version]
```

### Option 1: Slash Commands via clawbot

For more precise control, use slash commands directly in a clawbot conversation:

```
/resume polish
Please polish my resume:

John Doe
Senior Frontend Engineer | 5 years experience
Skills: JavaScript, React, Vue, Node.js
...
```

### Option 2: Integration in AI Agent Frameworks

#### 1. Register the Skill

Register this project as a skill in your AI Agent:

```json
{
  "skills": [
    {
      "name": "resume-assistant",
      "path": "./skills/resume-assistant",
      "manifest": "skill.json"
    }
  ]
}
```

#### 2. Load Prompts

When handling resume-related requests, prompt files are loaded in this order:

```
1. prompts/system.md      ← Persona & quality standards (loaded first)
2. prompts/<command>.md    ← Load per command: specific instructions
3. templates/<style>.md    ← Load on demand (export command only)
```

#### 3. Build the Complete Prompt

Example for `/resume polish` — here's how an AI Agent should construct the prompt:

```python
# Python pseudocode
ROLE_SYS = "system"    # LLM message role constant
ROLE_USR = "user"      # LLM message role constant

def build_prompt(command, args):
    # Step 1: Load the skill persona prompt
    persona_prompt = load_file("prompts/system.md")

    # Step 2: Load command-specific prompt
    command_prompt = load_file(f"prompts/{command}.md")

    # Step 3: Combine prompts into LLM messages
    combined = persona_prompt + "\n\n" + command_prompt
    messages = [
        {"role": ROLE_SYS, "content": combined},
        {"role": ROLE_USR, "content": args["resume_content"]}
    ]

    # Step 4: Add optional parameters to user message
    if args.get("language"):
        messages[1]["content"] += f"\n\nLanguage: {args['language']}"

    return messages
```

```javascript
// JavaScript pseudocode
const ROLE_SYS = 'system';  // LLM message role constant
const ROLE_USR = 'user';    // LLM message role constant

async function buildPrompt(command, args) {
  // Step 1: Load the skill persona prompt
  const personaPrompt = await loadFile('prompts/system.md');

  // Step 2: Load command-specific prompt
  const commandPrompt = await loadFile(`prompts/${command}.md`);

  // Step 3: Combine prompts into LLM messages
  const combined = `${personaPrompt}\n\n${commandPrompt}`;
  const messages = [
    { role: ROLE_SYS, content: combined },
    { role: ROLE_USR, content: args.resume_content }
  ];

  // Step 4: Add optional parameters
  if (args.language) {
    messages[1].content += `\n\nLanguage: ${args.language}`;
  }

  return messages;
}
```

### Option 3: REST API

If your AI Agent exposes an HTTP API, invoke via RESTful endpoints:

```bash
# Polish a resume
curl -X POST https://your-agent-api.com/skills/resume-assistant/polish \
  -H "Content-Type: application/json" \
  -d '{
    "resume_content": "Your resume content...",
    "language": "en"
  }'

# Score a resume
curl -X POST https://your-agent-api.com/skills/resume-assistant/score \
  -H "Content-Type: application/json" \
  -d '{
    "resume_content": "Your resume content...",
    "target_role": "Senior Frontend Engineer",
    "language": "en"
  }'

# Customize for a job
curl -X POST https://your-agent-api.com/skills/resume-assistant/customize \
  -H "Content-Type: application/json" \
  -d '{
    "resume_content": "Your resume content...",
    "job_description": "Job description...",
    "language": "en"
  }'

# Export to a format
curl -X POST https://your-agent-api.com/skills/resume-assistant/export \
  -H "Content-Type: application/json" \
  -d '{
    "resume_content": "Your resume content...",
    "format": "html",
    "template": "modern"
  }'
```

### Option 4: LangChain / LlamaIndex Integration

```python
from langchain.tools import Tool

# Define tools based on skill.json commands
resume_tools = [
    Tool(
        name="resume_polish",
        description="Polish and improve resume with 40+ checklist items",
        func=lambda input: agent.run_skill(
            "resume-assistant", "polish",
            {"resume_content": input, "language": "en"}
        )
    ),
    Tool(
        name="resume_score",
        description="Score a resume on 100-point scale with improvement suggestions",
        func=lambda input: agent.run_skill(
            "resume-assistant", "score",
            {"resume_content": input, "language": "en"}
        )
    ),
    Tool(
        name="resume_customize",
        description="Customize resume for a specific job position",
        func=lambda input: agent.run_skill(
            "resume-assistant", "customize",
            {"resume_content": input.split("---JD---")[0],
             "job_description": input.split("---JD---")[1],
             "language": "en"}
        )
    ),
    Tool(
        name="resume_export",
        description="Export resume to Word/Markdown/HTML/LaTeX/PDF",
        func=lambda input: agent.run_skill(
            "resume-assistant", "export",
            {"resume_content": input, "format": "html", "template": "modern"}
        )
    ),
]
```

### Command Routing

The AI Agent should route user requests to the correct command:

```mermaid
graph TD
    A["User Input"] --> B{"Contains<br/>slash command?"}
    B -- "Yes" --> C{"Parse command"}
    C -- "/resume polish" --> D["Load polish.md"]
    C -- "/resume customize" --> E["Load customize.md"]
    C -- "/resume export" --> F["Load export.md"]
    C -- "/resume score" --> G["Load score.md"]
    B -- "No" --> H{"Intent detection"}
    H -- "polish/improve/fix" --> D
    H -- "job/apply/match" --> E
    H -- "export/download/convert" --> F
    H -- "score/rate/evaluate" --> G
    D --> I["Build Prompt<br/>Call LLM"]
    E --> I
    F --> I
    G --> I
    I --> J["Return Result"]
```

### Argument Validation

The AI Agent should validate arguments before invocation, referencing `skill.json`:

```python
def validate_args(command, args):
    """Validate arguments against skill.json schema."""
    schema = load_skill_json()
    cmd_schema = next(c for c in schema["commands"] if c["name"] == command)

    for arg in cmd_schema["arguments"]:
        # Check required fields
        if arg["required"] and arg["name"] not in args:
            raise ValueError(f"Missing required argument: {arg['name']}")

        # Check enum constraints
        if "enum" in arg and arg["name"] in args:
            if args[arg["name"]] not in arg["enum"]:
                raise ValueError(
                    f"Invalid value for {arg['name']}: {args[arg['name']]}. "
                    f"Must be one of: {arg['enum']}"
                )

        # Apply defaults
        if arg["name"] not in args and "default" in arg:
            args[arg["name"]] = arg["default"]

    # Check max resume length
    max_len = schema["config"]["max_resume_length"]
    if len(args.get("resume_content", "")) > max_len:
        raise ValueError(f"Resume exceeds {max_len} character limit")

    return args
```

---

## Commands

### `/resume polish`

Run a **40+ item checklist** across 8 categories and get a fully improved resume.

**Arguments:**

| Name | Type | Required | Default | Description |
|------|------|----------|---------|-------------|
| `resume_content` | string | ✅ | — | Resume text (plain text or Markdown) |
| `language` | string | — | `en` | `en` for English, `zh` for Chinese |

**What you get:**
- ✅/❌/⚠️ checklist results for every item (contact, summary, experience, education, skills, grammar, formatting, ATS)
- Fully polished resume with strong action verbs and quantified results
- Change summary categorized by priority: 🔴 Critical → 🟡 Major → 🟢 Minor → 💡 Suggestion
- Action verb reference table and quantification guide

---

### `/resume customize`

Tailor your resume for a **specific job posting** with gap analysis and keyword optimization.

**Arguments:**

| Name | Type | Required | Default | Description |
|------|------|----------|---------|-------------|
| `resume_content` | string | ✅ | — | Resume text |
| `job_description` | string | ✅ | — | Target job description or job title |
| `language` | string | — | `en` | `en` for English, `zh` for Chinese |

**What you get:**
- Job description breakdown (required skills, preferred skills, responsibilities, keywords)
- Gap analysis matrix mapping every requirement to your resume
- Customized resume with keywords naturally integrated
- Keyword coverage report: before vs. after
- Bonus: cover letter talking points + interview prep notes

---

### `/resume export`

Convert your resume to **Word, Markdown, HTML, LaTeX, or PDF** with professional templates.

**Arguments:**

| Name | Type | Required | Default | Description |
|------|------|----------|---------|-------------|
| `resume_content` | string | ✅ | — | Resume text (Markdown preferred) |
| `format` | string | ✅ | — | `word` \| `markdown` \| `html` \| `latex` \| `pdf` |
| `template` | string | — | `professional` | `professional` \| `modern` \| `minimal` \| `academic` |

**Templates:**

| Template | Style | Best For |
|----------|-------|----------|
| `professional` | Navy, serif headings, classic borders | Finance, consulting, law, healthcare |
| `modern` | Teal accents, creative layout, emoji icons | Tech, startups, product, marketing |
| `minimal` | Monochrome, ultra-clean, content-dense | Senior professionals, engineering |
| `academic` | Formal serif, multi-page, publications | Faculty, research, PhD applications |

**Export details:**
- **HTML**: Self-contained file with embedded CSS, 4 color themes, `@media print` optimized
- **LaTeX**: Complete compilable `.tex` with XeLaTeX + CJK support
- **Word**: Pandoc-optimized Markdown with YAML front matter + conversion command
- **PDF**: Print-optimized HTML with A4 page dimensions + multiple conversion methods
- **Markdown**: Clean, structured, version-control friendly

---

### `/resume score`

Get a **100-point professional evaluation** with specific improvement suggestions.

**Arguments:**

| Name | Type | Required | Default | Description |
|------|------|----------|---------|-------------|
| `resume_content` | string | ✅ | — | Resume text |
| `target_role` | string | — | — | Target role for fit assessment |
| `language` | string | — | `en` | `en` for English, `zh` for Chinese |

**Scoring dimensions (100 points):**

| Dimension | Points | Evaluates |
|-----------|--------|-----------|
| Content Quality | 30 | Achievements, action verbs, relevance, completeness |
| Structure & Formatting | 25 | Layout, consistency, length, section order |
| Language & Grammar | 20 | Grammar, spelling, tone, clarity |
| ATS Optimization | 15 | Keywords, standard headings, format compatibility |
| Impact & Impression | 10 | 6-second test, career story, professionalism |

**Grade scale:** A+ (95-100) → A (90-94) → B+ (85-89) → B (80-84) → C+ (75-79) → C (70-74) → D (60-69) → F (<60)

**What you get:**
- Score breakdown with per-dimension justification
- Top 3 strengths with specific examples from your resume
- Priority-ranked improvements with **Before → After** rewrites
- Role fit assessment (if target_role provided): fit score, competitive percentile, strengths, gaps
- 5-step action plan with effort estimates

---

## Recommended Workflow

```
┌──────────────────────────────────────────────────────┐
│                  Recommended Workflow                 │
├──────────────────────────────────────────────────────┤
│                                                      │
│  1. /resume score     ← Know where you stand         │
│     💬 "Score my resume"                             │
│          │                                           │
│          ▼                                           │
│  2. /resume polish    ← Fix all issues               │
│     💬 "Polish my resume"                            │
│          │                                           │
│          ▼                                           │
│  3. /resume customize ← Tailor per application       │
│     💬 "Tailor for this JD: ..."                     │
│          │                                           │
│          ▼                                           │
│  4. /resume export    ← Generate final files         │
│     💬 "Convert to PDF"                              │
│          │                                           │
│          ▼                                           │
│  5. /resume score     ← Verify improvement           │
│     💬 "Score my resume again"                       │
│                                                      │
└──────────────────────────────────────────────────────┘
```

**Tips:**
1. Start with **score** if you have an existing resume — understand your baseline
2. **Polish** to fix all fundamentals before customizing for a job
3. **Customize** separately for each application — one-size-fits-all doesn't work
4. **Export** last — get content perfect, then format
5. Use **Markdown** as your working format — it converts cleanly to all others
6. **Score again** after polish + customize to measure improvement

---

## Project Structure

```
resume-assistant/
├── skill.json                    # Skill manifest (JSON)
├── skill.yaml                    # Skill manifest (YAML)
├── SKILL.md                      # This documentation
├── prompts/
│   ├── system.md                 # Persona definition & quality standards
│   ├── polish.md                 # Polish prompt: 40+ item checklist
│   ├── customize.md              # Customize prompt: gap analysis & keywords
│   ├── export.md                 # Export prompt: 5 formats × 4 templates
│   └── score.md                  # Score prompt: 100-point rubric
├── templates/
│   ├── professional.md           # Classic corporate template
│   ├── modern.md                 # Contemporary tech/startup template
│   ├── minimal.md                # Ultra-clean senior template
│   ├── academic.md               # Formal academic CV template
│   └── export/
│       ├── resume.html           # HTML template (4 CSS themes)
│       └── resume.tex            # LaTeX template (XeLaTeX + CJK)
└── examples/
    ├── sample-resume-en.md       # English sample (high quality)
    ├── sample-resume-zh.md       # Chinese sample (high quality)
    ├── sample-resume-weak.md     # Weak sample (for scoring demo)
    └── usage.md                  # Usage examples & workflow guide
```

---

## Language Support

| Language | Code | Features |
|----------|------|----------|
| English | `en` | Full support, US/UK conventions |
| Chinese | `zh` | Full support, 中英文混排规范, CJK export |

---

## Configuration

| Key | Value | Description |
|-----|-------|-------------|
| `max_resume_length` | 10,000 chars | Maximum input length |
| `supported_languages` | `en`, `zh` | Available languages |
| `supported_export_formats` | word, markdown, html, latex, pdf | Available export formats |
scats

# 📝 简历助手 (Resume / CV Assistant)

> AI 驱动的 clawbot 技能，提供简历（Resume / CV）润色、职位定制、多格式导出和专业评分一站式服务。
**版本：** 1.0.0 · **许可证：** MIT · **仓库地址：** [github.com/Wscats/resume-assistant](https://github.com/Wscats/resume-assistant)

---

## 概述

简历助手（Resume / CV Assistant）是一个 clawbot 技能，帮助求职者创建、优化和完善简历（Resume / CV）。它整合了全面的检查清单审查、专业评分、职位匹配分析和多格式导出功能，提供从简历撰写到投递的完整工作流。


---

## 如何在 AI Agent 中使用

### 快速接入

Resume / CV Assistant 是一个标准的 clawbot skill，可以被任何兼容的 AI Agent 加载和调用。以下是在不同场景下的接入方式。

### 💬 自然语言对话（推荐）

不需要记忆任何命令 —— 直接描述你的需求即可：

```
💬 "帮我写一份软件工程师的简历"
💬 "润色我的简历，修复所有问题"
💬 "优化我的简历，让它通过 ATS 筛选"
💬 "根据这个职位描述定制我的简历：[粘贴 JD]"
💬 "把我的简历转成 PDF"
💬 "给我的简历打个分，告诉我怎么改进"
💬 "我的简历有什么问题？"
💬 "这是我的简历，帮我看看"
```

English also works:
```
💬 "Create a resume for a software engineer position"
💬 "Optimize my resume for ATS"
💬 "Tailor my resume for this job description: [paste JD]"
💬 "Score my resume and tell me how to improve"
```

助手会理解你的意图，自动路由到正确的工作流：

| 你说 | 助手做什么 |
|------|-----------|
| "帮我写一份 [职位] 的简历" | 询问你的背景信息 → 生成定制简历 |
| "润色 / 修改 / 优化我的简历" | 执行 40+ 项检查 → 返回润色后的版本 |
| "优化 ATS" | 检查 ATS 兼容性 → 优化关键词和格式 |
| "根据这个 JD 定制：..." | 分析 JD → 差距分析 → 定制简历 |
| "转成 PDF / Word / ..." | 用专业模板导出为指定格式 |
| "给简历打分 / 评估 / 怎么样" | 100 分制评分 → 优势与改进方案 |
| "这是我的简历，帮我看看" | 先评分 → 再建议后续步骤 |

#### 对话示例

**从零创建简历：**
```
你：  帮我写一份前端工程师的简历，目标是创业公司

助手：好的！为了生成一份量身定制的简历，请提供以下信息：
      1. 工作经历（公司、职位、时间、主要成果）
      2. 教育背景
      3. 技术栈
      4. 有具体的目标职位 JD 吗？（可选但推荐提供）

你：  我在 Shopify 做了 3 年 React 开发...

助手：这是你的定制简历：
      [生成完整简历]
      
      需要我帮你打分、润色或导出吗？
```

**快速改进：**
```
你：  这是我的简历，帮我看看有什么问题
      [粘贴简历]

助手：📊 简历评分：68/100（等级：C）
      前 3 大问题：
      1. ❌ 没有量化成果
      2. ⚠️ 动词太弱（"负责"→"主导"）
      3. ⚠️ 缺少目标职位的关键词
      
      需要我帮你润色吗？

你：  好的，帮我润色

助手：[执行 40+ 项检查清单全面优化]
```

**职位定制：**
```
你：  根据这个 JD 定制我的简历：
      Stripe 高级后端工程师
      要求：Go、分布式系统、支付 API...

助手：🎯 职位分析完成
      📊 当前匹配度：62% → 优化后：89%
      [生成定制版本]
```

### 方式一：通过 clawbot 平台使用斜杠命令

如果需要更精细的控制，可以在 clawbot 对话中直接使用斜杠命令：

```
/resume polish
请帮我润色以下简历：

张三
高级前端工程师 | 5年经验
技能：JavaScript, React, Vue, Node.js
...
```

### 方式二：在 AI Agent 框架中集成

#### 1. 注册技能

将本项目作为 skill 注册到你的 AI Agent 中：

```json
{
  "skills": [
    {
      "name": "resume-assistant",
      "path": "./skills/resume-assistant",
      "manifest": "skill.json"
    }
  ]
}
```

#### 2. 加载提示词

AI Agent 在处理简历相关请求时，按以下顺序加载提示词文件：

```
1. prompts/system.md      ← 角色定义与质量标准（首先加载）
2. prompts/<command>.md    ← 根据命令加载对应的提示词
3. templates/<style>.md    ← 按需加载模板（仅 export 命令使用）
```

#### 3. 构建完整的 Prompt

以 `/resume polish` 为例，AI Agent 应按如下方式构建 prompt：

```python
# Python 伪代码
ROLE_SYS = "system"    # LLM message role constant
ROLE_USR = "user"      # LLM message role constant

def build_prompt(command, args):
    # Step 1: Load the skill persona prompt
    persona_prompt = load_file("prompts/system.md")

    # Step 2: Load command-specific prompt
    command_prompt = load_file(f"prompts/{command}.md")

    # Step 3: Combine prompts into LLM messages
    combined = persona_prompt + "\n\n" + command_prompt
    messages = [
        {"role": ROLE_SYS, "content": combined},
        {"role": ROLE_USR, "content": args["resume_content"]}
    ]

    # Step 4: Add optional parameters to user message
    if args.get("language"):
        messages[1]["content"] += f"\n\nLanguage: {args['language']}"

    return messages
```

```javascript
// JavaScript 伪代码
const ROLE_SYS = 'system';  // LLM message role constant
const ROLE_USR = 'user';    // LLM message role constant

async function buildPrompt(command, args) {
  // Step 1: Load the skill persona prompt
  const personaPrompt = await loadFile('prompts/system.md');

  // Step 2: Load command-specific prompt
  const commandPrompt = await loadFile(`prompts/${command}.md`);

  // Step 3: Combine prompts into LLM messages
  const combined = `${personaPrompt}\n\n${commandPrompt}`;
  const messages = [
    { role: ROLE_SYS, content: combined },
    { role: ROLE_USR, content: args.resume_content }
  ];

  // Step 4: Add optional parameters
  if (args.language) {
    messages[1].content += `\n\nLanguage: ${args.language}`;
  }

  return messages;
}
```

### 方式三：通过 API 调用

如果你的 AI Agent 提供了 HTTP API，可以通过 RESTful 接口调用：

```bash
# 简历润色
curl -X POST https://your-agent-api.com/skills/resume-assistant/polish \
  -H "Content-Type: application/json" \
  -d '{
    "resume_content": "你的简历内容...",
    "language": "zh"
  }'

# 简历评分
curl -X POST https://your-agent-api.com/skills/resume-assistant/score \
  -H "Content-Type: application/json" \
  -d '{
    "resume_content": "你的简历内容...",
    "target_role": "高级前端工程师",
    "language": "zh"
  }'

# 职位定制
curl -X POST https://your-agent-api.com/skills/resume-assistant/customize \
  -H "Content-Type: application/json" \
  -d '{
    "resume_content": "你的简历内容...",
    "job_description": "职位描述...",
    "language": "zh"
  }'

# 格式导出
curl -X POST https://your-agent-api.com/skills/resume-assistant/export \
  -H "Content-Type: application/json" \
  -d '{
    "resume_content": "你的简历内容...",
    "format": "html",
    "template": "modern"
  }'
```

### 方式四：在 LangChain / LlamaIndex 等框架中使用

```python
from langchain.tools import Tool

# Define tools based on skill.json commands
resume_tools = [
    Tool(
        name="resume_polish",
        description="Polish and improve resume with 40+ checklist items",
        func=lambda input: agent.run_skill(
            "resume-assistant", "polish",
            {"resume_content": input, "language": "zh"}
        )
    ),
    Tool(
        name="resume_score",
        description="Score a resume on 100-point scale with improvement suggestions",
        func=lambda input: agent.run_skill(
            "resume-assistant", "score",
            {"resume_content": input, "language": "zh"}
        )
    ),
    Tool(
        name="resume_customize",
        description="Customize resume for a specific job position",
        func=lambda input: agent.run_skill(
            "resume-assistant", "customize",
            {"resume_content": input.split("---JD---")[0],
             "job_description": input.split("---JD---")[1],
             "language": "zh"}
        )
    ),
    Tool(
        name="resume_export",
        description="Export resume to Word/Markdown/HTML/LaTeX/PDF",
        func=lambda input: agent.run_skill(
            "resume-assistant", "export",
            {"resume_content": input, "format": "html", "template": "modern"}
        )
    ),
]
```

### 命令路由逻辑

AI Agent 在收到用户请求后，应按以下流程路由到对应命令：

```mermaid
graph TD
    A["用户输入"] --> B{"是否包含<br/>斜杠命令？"}
    B -- "是" --> C{"解析命令名"}
    C -- "/resume polish" --> D["加载 polish.md"]
    C -- "/resume customize" --> E["加载 customize.md"]
    C -- "/resume export" --> F["加载 export.md"]
    C -- "/resume score" --> G["加载 score.md"]
    B -- "否" --> H{"意图识别"}
    H -- "润色/优化/修改" --> D
    H -- "求职/申请/匹配" --> E
    H -- "导出/下载/转换" --> F
    H -- "评分/评价/打分" --> G
    D --> I["构建 Prompt<br/>调用 LLM"]
    E --> I
    F --> I
    G --> I
    I --> J["返回结果"]
```

### 参数校验

AI Agent 应在调用前校验参数，参考 `skill.json` 中的定义：

```python
def validate_args(command, args):
    """Validate arguments against skill.json schema."""
    schema = load_skill_json()
    cmd_schema = next(c for c in schema["commands"] if c["name"] == command)

    for arg in cmd_schema["arguments"]:
        # Check required fields
        if arg["required"] and arg["name"] not in args:
            raise ValueError(f"Missing required argument: {arg['name']}")

        # Check enum constraints
        if "enum" in arg and arg["name"] in args:
            if args[arg["name"]] not in arg["enum"]:
                raise ValueError(
                    f"Invalid value for {arg['name']}: {args[arg['name']]}. "
                    f"Must be one of: {arg['enum']}"
                )

        # Apply defaults
        if arg["name"] not in args and "default" in arg:
            args[arg["name"]] = arg["default"]

    # Check max resume length
    max_len = schema["config"]["max_resume_length"]
    if len(args.get("resume_content", "")) > max_len:
        raise ValueError(f"Resume exceeds {max_len} character limit")

    return args
```

---

## 命令一览

| 命令 | 功能 | 说明 |
|------|------|------|
| `/resume polish` | 简历润色 | 40+ 项检查清单 + 全面优化 |
| `/resume customize` | 职位定制 | 差距分析 + 关键词匹配 |
| `/resume export` | 格式导出 | 5 种格式 × 4 种模板 |
| `/resume score` | 简历评分 | 100 分制专业评估 |

---

## 命令详解

### `/resume polish` — 简历润色

对简历进行 **40+ 项检查清单** 审查，涵盖 8 大类别，输出完整优化后的简历。

**参数：**

| 参数名 | 类型 | 必填 | 默认值 | 说明 |
|--------|------|------|--------|------|
| `resume_content` | string | ✅ | — | 简历内容（纯文本或 Markdown 格式） |
| `language` | string | — | `en` | `en` 英文，`zh` 中文 |

**检查清单类别（8 大类）：**

| 类别 | 检查项数 | 示例检查内容 |
|------|---------|-------------|
| 📇 联系信息 | 5 项 | 邮箱格式、电话号码、LinkedIn 链接 |
| 📋 职业摘要 | 5 项 | 是否有摘要、量化成果、与目标匹配度 |
| 💼 工作经历 | 8 项 | 强动词开头、量化成果、STAR 法则 |
| 🎓 教育背景 | 4 项 | 学位信息完整、GPA 策略、相关课程 |
| 🛠 技能清单 | 5 项 | 分类呈现、避免过时技能、匹配度 |
| 📝 语法与表达 | 5 项 | 拼写检查、时态一致、避免第一人称 |
| 📐 格式与排版 | 5 项 | 一致的间距、适当页数、清晰层次 |
| 🤖 ATS 兼容性 | 5 项 | 标准格式、关键词密度、避免表格/图片 |

**输出内容：**
- ✅/❌/⚠️ 每项检查结果及改进建议
- 完整润色后的简历（强动词 + 量化成果）
- 变更摘要按优先级分类：🔴 关键 → 🟡 重要 → 🟢 轻微 → 💡 建议
- 附赠：强动词参考表 + 成果量化指南

---

### `/resume customize` — 职位定制

根据 **目标职位描述** 定制简历，提供差距分析和关键词优化。

**参数：**

| 参数名 | 类型 | 必填 | 默认值 | 说明 |
|--------|------|------|--------|------|
| `resume_content` | string | ✅ | — | 简历内容 |
| `job_description` | string | ✅ | — | 目标职位描述或职位名称 |
| `language` | string | — | `en` | `en` 英文，`zh` 中文 |

**输出内容：**
- **职位解析**：必需技能、优先技能、核心职责、关键词提取
- **差距分析矩阵**：逐项对比每个职位要求与简历的匹配情况
- **定制后的简历**：自然融入关键词，突出相关经验
- **关键词覆盖报告**：优化前后对比
- **附赠**：求职信要点 + 面试准备笔记

**差距分析矩阵示例：**

```
| 职位要求       | 匹配状态 | 简历证据           | 建议操作     |
|---------------|---------|-------------------|-------------|
| Python 3 年+   | ✅ 强匹配 | 5 年 Python 经验   | 突出项目成果  |
| Kubernetes     | ⚠️ 弱匹配 | 提及 Docker 使用   | 补充 K8s 经验 |
| 团队管理经验    | ❌ 缺失   | 无相关描述         | 添加协作案例  |
```

---

### `/resume export` — 格式导出

将简历转换为 **Word、Markdown、HTML、LaTeX 或 PDF** 格式，搭配专业模板。

**参数：**

| 参数名 | 类型 | 必填 | 默认值 | 说明 |
|--------|------|------|--------|------|
| `resume_content` | string | ✅ | — | 简历内容（推荐 Markdown 格式） |
| `format` | string | ✅ | — | `word` \| `markdown` \| `html` \| `latex` \| `pdf` |
| `template` | string | — | `professional` | `professional` \| `modern` \| `minimal` \| `academic` |

**模板风格：**

| 模板 | 风格 | 适用场景 |
|------|------|---------|
| `professional` | 藏蓝色主调、衬线标题、经典边框 | 金融、咨询、法律、医疗行业 |
| `modern` | 青绿色点缀、创意布局、图标装饰 | 科技、创业公司、产品、市场营销 |
| `minimal` | 黑白简约、极致干净、内容密集 | 资深专业人士、工程师 |
| `academic` | 正式衬线字体、多页支持、出版物列表 | 高校教职、科研、博士申请 |

**各格式导出详情：**

| 格式 | 输出说明 |
|------|---------|
| **HTML** | 自包含文件，内嵌 CSS，4 种配色主题，`@media print` 打印优化 |
| **LaTeX** | 完整可编译 `.tex` 文件，XeLaTeX 引擎 + CJK 中文支持 |
| **Word** | Pandoc 优化的 Markdown + YAML 前置信息 + 转换命令 |
| **PDF** | 打印优化 HTML，A4 页面尺寸 + 多种转换方式 |
| **Markdown** | 结构清晰、版本控制友好、可转换为其他所有格式 |

---

### `/resume score` — 简历评分

获取 **100 分制专业评估**，附带具体的改进建议和优先级排序。

**参数：**

| 参数名 | 类型 | 必填 | 默认值 | 说明 |
|--------|------|------|--------|------|
| `resume_content` | string | ✅ | — | 简历内容 |
| `target_role` | string | — | — | 目标职位（用于匹配度评估） |
| `language` | string | — | `en` | `en` 英文，`zh` 中文 |

**评分维度（满分 100 分）：**

| 维度 | 分值 | 评估内容 |
|------|------|---------|
| 📊 内容质量 | 30 分 | 成就描述、强动词使用、相关性、完整性 |
| 📐 结构与排版 | 25 分 | 布局合理性、一致性、篇幅、段落顺序 |
| 📝 语言与语法 | 20 分 | 语法正确性、拼写、语气、表达清晰度 |
| 🤖 ATS 优化 | 15 分 | 关键词密度、标准标题、格式兼容性 |
| ✨ 影响力与印象 | 10 分 | 6 秒测试、职业故事、专业感 |

**评级标准：**

| 等级 | 分数范围 | 含义 |
|------|---------|------|
| A+ | 95–100 | 卓越 — 顶级简历，几乎无需修改 |
| A | 90–94 | 优秀 — 非常强的简历，仅需微调 |
| B+ | 85–89 | 良好 — 基础扎实，有提升空间 |
| B | 80–84 | 中上 — 合格简历，建议优化 |
| C+ | 75–79 | 中等 — 需要明显改进 |
| C | 70–74 | 及格 — 多处需要修改 |
| D | 60–69 | 不及格 — 需要大幅修改 |
| F | <60 | 差 — 建议重新撰写 |

**输出内容：**
- 各维度得分明细 + 扣分原因说明
- 前 3 大优势 + 简历中的具体佐证
- 按优先级排列的改进建议 + **修改前 → 修改后** 对比示例
- 职位匹配评估（如提供 `target_role`）：匹配分数、竞争力百分位、优势、差距
- 5 步行动计划 + 预估耗时

---

## 推荐工作流程

```mermaid
graph TD
    A["1️⃣ /resume score<br/>了解现状"] --> B["2️⃣ /resume polish<br/>修复所有问题"]
    B --> C["3️⃣ /resume customize<br/>逐个职位定制"]
    C --> D["4️⃣ /resume export<br/>生成最终文件"]
    D --> E["5️⃣ /resume score<br/>验证提升效果"]
    style A fill:#e3f2fd
    style B fill:#fff3e0
    style C fill:#e8f5e9
    style D fill:#fce4ec
    style E fill:#e3f2fd
```

```
┌──────────────────────────────────────────────────────┐
│                    推荐工作流程                        │
├──────────────────────────────────────────────────────┤
│                                                      │
│  1. /resume score     ← 了解现状，获得基线分数         │
│     💬 "给我的简历打个分"                              │
│          │                                           │
│          ▼                                           │
│  2. /resume polish    ← 修复所有问题                  │
│     💬 "润色我的简历"                                 │
│          │                                           │
│          ▼                                           │
│  3. /resume customize ← 针对每个目标职位定制           │
│     💬 "根据这个 JD 定制..."                          │
│          │                                           │
│          ▼                                           │
│  4. /resume export    ← 生成最终文件                  │
│     💬 "转成 PDF"                                    │
│          │                                           │
│          ▼                                           │
│  5. /resume score     ← 再次评分，验证提升效果         │
│     💬 "再帮我打一次分"                               │
│                                                      │
└──────────────────────────────────────────────────────┘
```

**使用建议：**
1. 如果已有简历，**先评分**了解自己的基线水平
2. **先润色**修复基础问题，再针对具体职位定制
3. 每个申请职位**单独定制**——万能简历不存在
4. **最后导出**——先把内容打磨好，再考虑格式
5. 使用 **Markdown** 作为工作格式——可无损转换为其他任何格式
6. 优化后**再次评分**，量化你的进步

---

## 项目结构

```
resume-assistant/
├── skill.json                    # 技能清单（JSON 格式）
├── skill.yaml                    # 技能清单（YAML 格式）
├── SKILL.md                      # 英文文档
├── SKILL_ZH.md                   # 中文文档（本文件）
├── LICENSE                       # MIT 开源许可证
├── prompts/
│   ├── system.md                 # 角色定义与质量标准
│   ├── polish.md                 # 润色提示词：40+ 项检查清单
│   ├── customize.md              # 定制提示词：差距分析与关键词优化
│   ├── export.md                 # 导出提示词：5 种格式 × 4 种模板
│   └── score.md                  # 评分提示词：100 分制评分标准
├── templates/
│   ├── professional.md           # 经典商务模板
│   ├── modern.md                 # 现代科技模板
│   ├── minimal.md                # 极简高级模板
│   ├── academic.md               # 学术论文模板
│   └── export/
│       ├── resume.html           # HTML 导出模板（4 种 CSS 主题）
│       └── resume.tex            # LaTeX 导出模板（XeLaTeX + CJK）
└── examples/
    ├── sample-resume-en.md       # 英文示例简历（高质量）
    ├── sample-resume-zh.md       # 中文示例简历（高质量）
    ├── sample-resume-weak.md     # 低质量示例简历（用于评分演示）
    └── usage.md                  # 使用示例与工作流指南
```

---

## 语言支持

| 语言 | 代码 | 支持情况 |
|------|------|---------|
| 英文 | `en` | 完整支持，US/UK 规范 |
| 中文 | `zh` | 完整支持，中英文混排规范，CJK 导出优化 |

**中文特别优化：**
- 中英文之间自动添加空格
- 中文标点符号规范化
- CJK 字体兼容（LaTeX 使用 XeLaTeX 引擎）
- 符合中国大陆求职习惯的排版建议

---

## 配置参数

| 参数 | 值 | 说明 |
|------|-----|------|
| `max_resume_length` | 10,000 字符 | 最大输入长度 |
| `supported_languages` | `en`, `zh` | 支持的语言 |
| `supported_export_formats` | word, markdown, html, latex, pdf | 支持的导出格式 |

---

## 常见问题

**Q: 简历内容会被存储吗？**
A: 不会。所有内容仅在当前会话中处理，不会持久化存储。

**Q: 支持哪些语言的简历？**
A: 目前完整支持英文（en）和中文（zh），包括中英文混排的简历。

**Q: 导出的 PDF 如何生成？**
A: 导出命令会生成打印优化的 HTML 文件，你可以通过浏览器打印为 PDF，或使用 `wkhtmltopdf`、`weasyprint` 等工具转换。

**Q: 可以同时润色和定制吗？**
A: 建议先执行 `/resume polish` 修复基础问题，再用 `/resume customize` 针对具体职位定制，效果最佳。

**Q: 评分低怎么办？**
A: 评分报告会附带具体的改进建议和修改示例，按照优先级逐项优化即可。一般经过润色后，分数会提升 15-25 分。

# John Smith

**[email protected] | (555) 123-4567 | San Francisco, CA**
**[LinkedIn](https://linkedin.com/in/johnsmith) | [GitHub](https://github.com/johnsmith)**

---

## Professional Summary

Results-driven Senior Software Engineer with 8+ years of experience building scalable web applications and leading cross-functional engineering teams. Proven track record of delivering high-impact products that drive revenue growth and user engagement. Passionate about clean architecture, developer experience, and mentoring.

---

## Work Experience

### Senior Software Engineer | TechCorp Inc.
*Jan 2021 – Present | San Francisco, CA*

- Led migration of monolithic application to microservices architecture, reducing deployment time by 75% and improving system reliability to 99.99% uptime
- Architected real-time data pipeline processing 2M+ events daily, enabling data-driven decisions that increased user retention by 15%
- Mentored team of 6 junior engineers through code reviews and weekly tech talks, improving code quality metrics by 40%
- Spearheaded CI/CD adoption, reducing release cycle from 2 weeks to daily deployments

### Software Engineer | StartupXYZ
*Mar 2018 – Dec 2020 | San Francisco, CA*

- Developed core payment processing system handling $50M+ in annual transactions with 99.97% accuracy
- Built responsive React dashboard used by 10,000+ merchants to manage inventory and track analytics
- Optimized database queries and implemented caching layer, reducing API response times by 60%

### Junior Software Engineer | WebAgency Co.
*Jun 2016 – Feb 2018 | Oakland, CA*

- Developed and maintained 15+ client-facing web applications using React, Node.js, and PostgreSQL
- Implemented automated testing suite achieving 85% code coverage, reducing production bugs by 30%
- Created reusable component library adopted by 4 project teams, improving development velocity by 20%

---

## Education

### B.S. in Computer Science
**University of California, Berkeley** | *May 2016*
- Dean's List: 6 semesters

---

## Skills

**Languages:** JavaScript/TypeScript, Python, Go, SQL, HTML/CSS

**Frameworks:** React, Next.js, Node.js, Express, Django, FastAPI

**Infrastructure:** AWS (EC2, S3, Lambda, ECS), Docker, Kubernetes, Terraform

**Databases:** PostgreSQL, MongoDB, Redis, Elasticsearch

**Tools:** Git, GitHub Actions, Jenkins, Datadog, Grafana

---

## Certifications

- AWS Solutions Architect – Associate | Amazon Web Services | 2023
- Certified Kubernetes Administrator (CKA) | CNCF | 2022

# mike johnson

[email protected]
phone: 5551234567

## about me

I am a very hard working and passionate developer who loves coding. I am a quick learner
and team player. Looking for a challenging position where I can grow my skills.

## work

software developer, some tech company
2020 - now

- Responsible for writing code
- Worked on the backend
- Helped with testing
- Attended meetings
- Used git for version control

intern, another company
Summer 2019

- Did various tasks assigned by my manager
- Learned a lot about software development

## school

computer science, State University, 2020
GPA: 3.1

## skills

Python, java, javascript, SQL, html, CSS, react, node, git, agile, microsoft office, 
communication, teamwork, problem solving, time management, leadership

# 张明

**[email protected] | 138-0000-1234 | 北京市**
**[LinkedIn](https://linkedin.com/in/zhangming) | [GitHub](https://github.com/zhangming)**

---

## 个人简介

拥有 6 年全栈开发经验的高级软件工程师，专注于高并发分布式系统架构设计与实现。曾主导多个千万级用户产品的技术架构升级，具备丰富的团队管理和跨部门协作经验。

---

## 工作经历

### 高级软件工程师 | 某科技有限公司
*2021年1月 – 至今 | 北京*

- 主导电商平台微服务架构改造，将系统 QPS 从 5,000 提升至 50,000+，支撑日均订单量 200 万+
- 设计并实现分布式缓存方案，将核心接口 P99 延迟从 800ms 降低至 50ms，用户体验评分提升 35%
- 带领 8 人技术团队完成国际化项目，成功拓展 3 个海外市场，新增用户 300 万+
- 建立代码审查制度和技术分享机制，团队代码质量评分提升 40%

### 软件工程师 | 某互联网公司
*2019年3月 – 2020年12月 | 上海*

- 开发实时数据分析平台，日处理数据量达 10TB+，为运营决策提供数据支撑
- 优化搜索引擎核心算法，搜索结果准确率提升 25%，搜索响应时间缩短 60%
- 参与设计并实现 A/B 测试平台，支持产品团队每月执行 50+ 实验，转化率提升 18%

### 初级软件工程师 | 某创业公司
*2018年7月 – 2019年2月 | 深圳*

- 独立负责公司官网及管理后台开发，使用 Vue.js + Spring Boot 技术栈
- 实现自动化部署流水线，部署效率提升 80%，部署频率从每周 1 次提升至每日多次
- 编写单元测试和集成测试，代码覆盖率从 30% 提升至 80%

---

## 教育背景

### 计算机科学与技术 · 工学学士
**北京大学** | *2018年毕业*
- 优秀毕业生

---

## 专业技能

**编程语言：** Java, Python, Go, JavaScript/TypeScript, SQL

**框架与工具：** Spring Boot, Spring Cloud, React, Vue.js, MyBatis

**中间件：** MySQL, Redis, Elasticsearch, Kafka, RabbitMQ

**基础设施：** Docker, Kubernetes, Nginx, Jenkins, GitLab CI/CD

**云服务：** 阿里云 (ECS, OSS, RDS), 腾讯云, AWS

---

## 证书

- 阿里云高级开发工程师认证 | 阿里云 | 2023
- PMP 项目管理专业人士认证 | PMI | 2022

# Resume / CV Assistant — Usage Examples
## 💬 Quick Start — Just Ask!

You don't need to memorize commands. Simply tell the assistant what you need in plain language:

| Just say... | What happens |
|-------------|-------------|
| 💬 "Create a resume for a software engineer position" | Asks for your background, then builds a tailored resume |
| 💬 "Polish my resume" *(then paste your resume)* | Runs 40+ item checklist review and rewrites |
| 💬 "Optimize my resume for ATS" | Checks ATS compatibility, optimizes keywords and formatting |
| 💬 "Tailor my resume for this job description: [paste JD]" | Analyzes JD, performs gap analysis, customizes your resume |
| 💬 "Convert my resume to PDF" | Exports to PDF using the professional template |
| 💬 "Score my resume and tell me how to improve" | Scores out of 100 with detailed improvement plan |
| 💬 "What's wrong with my resume?" | Evaluates and identifies key issues to fix |
| 💬 "Here's my resume, can you help?" | Scores first, then suggests next steps |

### Example Conversations

**Creating a new resume:**
```
You:   Create a resume for a frontend engineer position at a startup

Bot:   I'd be happy to help create a tailored resume! To get started, could you
       share the following:
       1. Your work experience (companies, roles, dates, key achievements)
       2. Education background
       3. Technical skills
       4. Any specific job posting you're targeting? (optional but recommended)

You:   I have 3 years of experience at Shopify working on React...
       [provides background details]

Bot:   Here's your tailored resume:
       [generates complete resume using customize workflow]
       
       Would you like me to:
       • Score this resume to see how it rates?
       • Export it to PDF or Word?
       • Polish it further for specific improvements?
```

**Quick improvement:**
```
You:   Here's my resume, what do you think?
       [pastes resume]

Bot:   📊 Resume Score: 68/100 (Grade: C)
       
       Top 3 Issues:
       1. ❌ No quantified achievements — add metrics
       2. ⚠️ Weak action verbs — replace "responsible for" with impact verbs
       3. ⚠️ Missing keywords for your target role
       
       Would you like me to polish it now? I can fix all these issues.

You:   Yes, polish it

Bot:   [runs full polish with 40+ checklist items]
```

**Job-specific tailoring:**
```
You:   Tailor my resume for this job description:
       Senior Backend Engineer at Stripe
       Requirements: Go, distributed systems, payment APIs...

Bot:   🎯 Job Analysis Complete
       📊 Current Match: 62% → After Optimization: 89%
       [generates tailored version with keyword optimization]
```

> 💡 **Tip:** You can also use slash commands for more precise control — see below.

---

## Quick Reference

| Command | Purpose | Required Input |
|---------|---------|----------------|
| `/resume polish` | Fix errors, improve wording, checklist review | resume content |
| `/resume customize` | Tailor for a specific job | resume content + job description |
| `/resume export` | Convert to Word/MD/HTML/LaTeX/PDF | resume content + format |
| `/resume score` | Evaluate and get improvement plan | resume content |

---

## Example 1: Polish a Resume
**Command:** `/resume polish`

**Input:**
```
resume_content: |
  I am a software engineer with 5 years experience. I worked at Google
  where I was responsible for building web applications. I helped improve
  the system performance. I also managed some team members.

  Education: BS Computer Science, Stanford University, 2018
  Skills: Python, Java, React, SQL, AWS

language: en
```

**What you get:**
- 📋 40+ item checklist review with ✅/❌/⚠️ for every item
- ✨ Fully polished resume with strong action verbs and metrics
- 📝 Categorized change list: 🔴 Critical → 🟡 Major → 🟢 Minor → 💡 Suggestions
- 📖 Action verb and quantification guidance

---

## Example 2: Customize for a Job

**Command:** `/resume customize`

**Input:**
```
resume_content: [your existing polished resume]

job_description: |
  Senior Frontend Engineer at Meta
  Requirements:
  - 5+ years of frontend development experience
  - Expert in React, TypeScript, and modern CSS
  - Experience with large-scale web applications
  - Strong web performance optimization skills
  - Experience with design systems and component libraries

language: en
```

**What you get:**
- 🎯 Detailed job requirements analysis
- 📊 Gap analysis table mapping each requirement to your resume
- ✨ Tailored resume with keywords optimized
- 🔑 Keyword coverage report (before vs. after)
- 💡 Cover letter talking points + interview prep notes

---

## Example 3: Export to Multiple Formats

**Command:** `/resume export`

**Input:**
```
resume_content: [your resume in Markdown]
format: html
template: modern
```

**Available formats:**

| Format | Extension | Best For |
|--------|-----------|----------|
| `markdown` | .md | Editing, version control, GitHub |
| `html` | .html | Web viewing, browser → PDF |
| `word` | .docx | ATS submission, recruiter preference |
| `latex` | .tex | Academic, professional typesetting |
| `pdf` | .pdf | Final submission, universal format |

**Available templates:**

| Template | Style | Industries |
|----------|-------|------------|
| `professional` | Classic navy, serif headings | Finance, consulting, law |
| `modern` | Teal accents, creative layout | Tech, startups, marketing |
| `minimal` | Clean monochrome, dense | Senior roles, engineering |
| `academic` | Formal serif, multi-page | Faculty, research, PhD |

---

## Example 4: Score an Existing Resume

**Command:** `/resume score`

**Input:**
```
resume_content: [your resume]
target_role: Senior Software Engineer at FAANG
language: en
```

**What you get:**
- 📊 Score out of 100 with letter grade (A+ to F)
- 📈 Breakdown across 5 dimensions:
  - Content Quality (30 pts)
  - Structure & Formatting (25 pts)
  - Language & Grammar (20 pts)
  - ATS Optimization (15 pts)
  - Impact & Impression (10 pts)
- ✅ Top 3 strengths with specific examples
- 🔧 Priority-ranked improvements with Before → After rewrites
- 🎯 Role fit assessment with competitive percentile estimate
- 📋 5-step action plan with effort estimates

---

## Recommended Workflow

```
┌─────────────┐
│ Start Here  │
└──────┬──────┘
       ▼
┌──────────────┐     Have a resume?
│ /resume score│◄─── YES ──────────────┐
└──────┬───────┘                       │
       ▼                               │
┌──────────────┐                       │
│/resume polish│◄─── NO (write first)──┘
└──────┬───────┘
       ▼
┌────────────────┐   Have a target job?
│/resume customize│◄── YES
└──────┬─────────┘
       ▼
┌──────────────┐
│/resume export │──► Word / Markdown / HTML / LaTeX / PDF
└──────────────┘
```

**Pro tips:**
1. **Start with scoring** if you have an existing resume — know where you stand
2. **Polish first** to fix all basic issues before customizing
3. **Customize per application** — don't use one resume for all jobs
4. **Score again** after polish + customize to see improvement
5. **Export last** — get content perfect before formatting
6. **Use Markdown** as your working format — it converts cleanly to all others

# Resume Customize — Prompt

## Task

Tailor the provided resume for a specific job position. Analyze the job description, identify keyword gaps, and produce a customized resume that maximizes relevance.

## Input

- **Resume Content**: `{{resume_content}}`
- **Job Description / Target Role**: `{{job_description}}`
- **Language**: `{{language}}`

---

## Step 1 — Job Description Analysis

Extract and organize:

1. **Required Skills** — Must-have technical and soft skills
2. **Preferred Skills** — Nice-to-have qualifications
3. **Key Responsibilities** — Core duties of the role
4. **Industry Keywords** — ATS-critical terms and phrases
5. **Experience Level** — Years and seniority expected
6. **Culture Signals** — Values, tone, and team dynamics clues

---

## Step 2 — Gap Analysis

Map every requirement to the resume:

| # | Requirement | Status | Evidence in Resume |
|---|-------------|--------|--------------------|
| 1 | [skill/qualification] | ✅ Strong Match / ⚠️ Partial / ❌ Gap | [where it appears or "Not found"] |

Calculate an initial match score: `matched / total requirements × 100`

---

## Step 3 — Customization Actions

### 3a. Professional Summary Rewrite

- Mirror the job description's language and keywords
- Lead with the 2-3 most relevant qualifications
- Address the role directly (e.g., "Senior Backend Engineer with...")

### 3b. Experience Optimization

- **Reorder** bullets within each role to put the most relevant first
- **Strengthen** bullets that match key responsibilities (add metrics if missing)
- **Add keywords** naturally into existing achievement descriptions
- **De-emphasize** irrelevant experience (fewer bullets, less detail — never delete honest history)

### 3c. Skills Alignment

- **Reorder** skills by relevance to the target role
- **Surface** skills the candidate has but didn't explicitly list
- **Match terminology** to the job description (e.g., "CI/CD" vs "continuous integration")
- **Group** by relevance: "Core Skills" → "Additional Skills"

### 3d. Additional Sections

- Suggest adding relevant certifications, courses, or projects
- For career transitions: highlight transferable skills prominently
- For academic roles: add publications, teaching, grants sections

---

## Step 4 — Keyword Optimization Report

| Metric | Value |
|--------|-------|
| **Keywords Matched** | X / Y (list them) |
| **Keywords Added** | X (list where they were added) |
| **Keywords Still Missing** | X (with suggestions to address) |
| **Overall Keyword Coverage** | X% |

---

## Output Format

```
## 🎯 Job Analysis

**Target**: [Job Title] at [Company]
**Level**: [Junior / Mid / Senior / Lead / Executive]
**Key Requirements**: [top 5 bullet points]

---

## 📊 Gap Analysis

| # | Requirement | Status | Evidence |
|---|-------------|--------|----------|
| ... | ... | ... | ... |

**Initial Match Score**: X%

---

## ✨ Customized Resume

[Complete tailored resume in Markdown format]

---

## 🔑 Keyword Report

### ✅ Matched Keywords
- keyword1, keyword2, keyword3...

### ➕ Added Keywords
- keyword → added to [section/bullet]

### ❌ Missing Keywords (with recommendations)
- keyword → [suggestion to address]

### Coverage: X% → Y% (after customization)

---

## 💡 Additional Recommendations

### Cover Letter Talking Points
1. [point to emphasize]
2. [point to emphasize]

### Interview Prep Notes
1. [likely question based on gaps]
2. [talking point to prepare]

### Skills to Develop
1. [skill to learn for stronger candidacy]
```

# Resume Export — Prompt

## Task

Export the provided resume into the specified format with professional styling.

## Input

- **Resume Content**: `{{resume_content}}`
- **Export Format**: `{{format}}` (word | markdown | html | latex | pdf)
- **Template Style**: `{{template}}` (professional | modern | minimal | academic)

---

## Format Specifications

### 📝 Markdown (.md)

Generate clean, well-structured Markdown:
- H1 for candidate name
- H2 for section headings
- H3 for job titles or subsections
- Consistent bullet points with proper indentation
- Horizontal rules (`---`) between major sections
- Bold for emphasis on key items
- No raw HTML embedded

### 🌐 HTML (.html)

Generate a complete, self-contained HTML file:
- Valid HTML5 with semantic elements (`<header>`, `<section>`, `<article>`)
- All CSS embedded in `<style>` tag (no external dependencies)
- Responsive layout that looks good on screen and print
- `@media print` styles for clean PDF generation via browser
- Proper `<meta charset="UTF-8">` and viewport tags
- Template-specific color scheme and typography

**Template Color Schemes:**

| Template | Primary Color | Font Family |
|----------|--------------|-------------|
| Professional | `#2c3e50` (Navy) | Georgia / Segoe UI |
| Modern | `#00897b` (Teal) | Inter / Helvetica Neue |
| Minimal | `#333333` (Charcoal) | System UI |
| Academic | `#1a1a2e` (Dark Navy) | Times New Roman / Georgia |

### 📄 Word (.docx)

Since direct .docx generation requires binary output, provide:
1. A **Pandoc-optimized Markdown** version with YAML front matter
2. Exact conversion command: `pandoc resume.md -o resume.docx --reference-doc=template.docx`
3. Formatting notes for manual Word paste (font sizes, margins, styles)

**YAML Front Matter for Pandoc:**
```yaml
---
title: "Resume"
author: "{{name}}"
geometry: margin=0.75in
fontsize: 11pt
---
```

### 📐 LaTeX (.tex)

Generate a complete, compilable LaTeX document:
- Document class: `article` (11pt, a4paper)
- Required packages: `geometry`, `titlesec`, `enumitem`, `hyperref`, `xcolor`, `tabularx`
- Custom commands for consistent formatting (`\experienceitem`, `\educationitem`)
- XeLaTeX-compatible for Unicode/Chinese support
- Compile instruction: `xelatex resume.tex`
- For Chinese: add `\usepackage{ctex}` and use `xelatex`

### 📑 PDF

Generate print-optimized HTML with:
- Exact A4/Letter page dimensions in CSS (`@page { size: A4; margin: 0.6in; }`)
- Page break controls (`page-break-inside: avoid`)
- Conversion methods provided:
  - **Browser**: Open HTML → Print → Save as PDF
  - **wkhtmltopdf**: `wkhtmltopdf --page-size A4 resume.html resume.pdf`
  - **Pandoc**: `pandoc resume.md -o resume.pdf --pdf-engine=xelatex`
  - **WeasyPrint**: `weasyprint resume.html resume.pdf`

---

## Template Styles

### Professional
- Classic, conservative design suitable for corporate roles
- Serif headings, clean sans-serif body text
- Navy blue accent color, traditional borders
- Best for: Finance, consulting, law, healthcare, government

### Modern
- Contemporary design with subtle creative touches
- Sans-serif throughout, generous spacing
- Teal/coral accents, optional sidebar for skills
- Best for: Tech, startups, product, marketing, design

### Minimal
- Ultra-clean whitespace-focused design
- Single font family, monochrome palette
- Maximum content density with elegant spacing
- Best for: Senior professionals, engineering, when content speaks for itself

### Academic
- Formal academic CV format
- Serif fonts throughout (Times New Roman / Garamond)
- Supports multi-page layout with proper page breaks
- Extra sections: Publications, Research, Teaching, Grants
- Best for: Faculty positions, postdocs, research roles, PhD applications

---

## Output Format

```
## 📄 Export: {{format}} — {{template}} Template

[Complete file content in the target format, ready to save/compile]

---

## 📋 How to Use

### Save & Convert
1. [Step-by-step instructions]

### Recommended Tools
- [tool 1 with install/usage]
- [tool 2 with install/usage]

### Tips
- [format-specific tip 1]
- [format-specific tip 2]
```

# Resume Polish — Prompt

## Task

Polish and improve the provided resume. Run a comprehensive checklist, fix all issues, and deliver an enhanced version.

## Input

- **Resume Content**: `{{resume_content}}`
- **Language**: `{{language}}`

---

## Step 1 — Comprehensive Checklist Review

Evaluate EVERY item below. Mark each as ✅ Pass, ❌ Fail, or ⚠️ Needs Attention.

### A. Contact & Personal Information

- [ ] Full name clearly displayed
- [ ] Professional email address (no nicknames)
- [ ] Phone number with correct format and area code
- [ ] City/State location (no full street address)
- [ ] LinkedIn URL present and customized
- [ ] Portfolio/GitHub link (if applicable for role)
- [ ] No unnecessary personal info (age, photo, marital status)

### B. Professional Summary

- [ ] Present and concise (2-3 sentences)
- [ ] Tailored to target role (not generic)
- [ ] Contains top 2-3 qualifications
- [ ] Includes relevant keywords
- [ ] Free of clichés ("hard-working team player", "passionate self-starter")

### C. Work Experience

- [ ] Reverse chronological order
- [ ] Consistent date format throughout
- [ ] Each entry: job title, company, location, date range
- [ ] 3-6 bullet points per role
- [ ] Bullets start with strong action verbs
- [ ] Achievements quantified with metrics (numbers, %, $)
- [ ] Results-focused (not just responsibilities)
- [ ] Past tense for former roles, present for current
- [ ] No personal pronouns (I, me, my)
- [ ] No unexplained gaps > 6 months
- [ ] No overlapping employment dates

### D. Education

- [ ] Reverse chronological order
- [ ] Degree, major, institution, graduation date included
- [ ] GPA only if notable (> 3.5/4.0)
- [ ] Relevant coursework only for recent graduates
- [ ] Honors/awards mentioned
- [ ] No high school if college degree obtained

### E. Skills

- [ ] Categorized (Technical, Tools, Languages, etc.)
- [ ] Relevant to target position
- [ ] No self-rating scales (e.g., "Python: 8/10")
- [ ] Both hard and soft skills included
- [ ] Matches common industry keywords

### F. Grammar, Spelling & Language

- [ ] Zero spelling errors
- [ ] Zero grammatical errors
- [ ] Consistent tense usage
- [ ] Professional tone throughout
- [ ] No abbreviations used without context
- [ ] Consistent punctuation (periods at end of bullets or not)
- [ ] For zh: proper spacing between Chinese and English/numbers

### G. Formatting & Layout

- [ ] Appropriate length (1-2 pages)
- [ ] Consistent font style and sizing
- [ ] Adequate margins (0.5"-1")
- [ ] Clear section headings with visual hierarchy
- [ ] Consistent bullet style
- [ ] Sufficient white space
- [ ] No decorative graphics or images

### H. ATS Compatibility

- [ ] Standard section headings used
- [ ] No content in headers/footers
- [ ] No tables, text boxes, or multi-column layout
- [ ] No images or graphics
- [ ] Industry keywords present naturally
- [ ] Simple, parseable formatting

---

## Step 2 — Polish & Rewrite

Using the checklist results, produce an improved version:

1. Fix all ❌ items
2. Improve all ⚠️ items
3. Strengthen weak bullets: add action verbs + quantified results
4. Replace vague phrases with specific, impactful statements
5. Ensure consistent formatting throughout
6. Optimize keywords for the apparent target industry

---

## Step 3 — Change Summary

Organize all changes by priority:

| Priority | Meaning |
|----------|---------|
| 🔴 Critical | Errors that could cause immediate rejection |
| 🟡 Major | Changes that significantly improve competitiveness |
| 🟢 Minor | Polish and refinement for extra impact |
| 💡 Suggestion | Optional improvements for consideration |

---

## Output Format

```
## 📋 Checklist Results

### A. Contact & Personal Info
[results per item]

### B. Professional Summary
[results per item]

... (all sections)

---

## ✨ Polished Resume

[Complete improved resume in Markdown]

---

## 📝 Change Summary

### 🔴 Critical Fixes
- [fix description]

### 🟡 Major Improvements
- [improvement description]

### 🟢 Minor Enhancements
- [enhancement description]

### 💡 Suggestions
- [optional suggestion]
```

---

## Action Verb Reference

Use these to strengthen bullet points:

| Category | Verbs |
|----------|-------|
| **Leadership** | Led, Directed, Managed, Supervised, Spearheaded, Orchestrated, Championed |
| **Achievement** | Achieved, Exceeded, Delivered, Surpassed, Generated, Secured |
| **Technical** | Developed, Engineered, Architected, Implemented, Deployed, Automated, Optimized |
| **Analysis** | Analyzed, Evaluated, Identified, Diagnosed, Forecasted, Measured |
| **Communication** | Presented, Negotiated, Collaborated, Facilitated, Influenced |
| **Improvement** | Improved, Streamlined, Modernized, Transformed, Accelerated, Reduced |
| **Creation** | Created, Designed, Established, Launched, Pioneered, Innovated |

## Quantification Guide

Always try to add numbers:

- **Revenue**: Generated $X in revenue / Grew revenue by X%
- **Efficiency**: Reduced processing time by X% / Saved X hours per week
- **Scale**: Managed team of X / Served X,000+ users daily
- **Quality**: Achieved X% uptime / Reduced error rate by X%
- **Growth**: Increased user base by X% / Expanded to X markets

# Resume Score — Prompt

## Task

Evaluate the provided resume comprehensively, assign a 100-point score, highlight strengths, and provide prioritized, actionable improvement suggestions with before/after examples.

## Input

- **Resume Content**: `{{resume_content}}`
- **Target Role** (optional): `{{target_role}}`
- **Language**: `{{language}}`

---

## Scoring Rubric (100 Points)

### Dimension 1 — Content Quality (30 pts)

| Criteria | Max Pts | What to Evaluate |
|----------|---------|------------------|
| Achievement Focus | 8 | Quantified, results-driven bullets vs. vague duties |
| Action Verbs | 5 | Strong, varied verbs at the start of each bullet |
| Relevance | 7 | Content relevance to target role / industry |
| Completeness | 5 | All essential sections present and well-developed |
| Differentiation | 5 | Unique content that stands out from generic resumes |

### Dimension 2 — Structure & Formatting (25 pts)

| Criteria | Max Pts | What to Evaluate |
|----------|---------|------------------|
| Layout & Flow | 7 | Clean, logical, easy-to-scan visual structure |
| Consistency | 6 | Uniform dates, bullets, capitalization, fonts |
| Appropriate Length | 5 | Right page count for experience level |
| Section Order | 4 | Optimal ordering for maximum impact |
| White Space | 3 | Balanced readability and density |

### Dimension 3 — Language & Grammar (20 pts)

| Criteria | Max Pts | What to Evaluate |
|----------|---------|------------------|
| Grammar | 7 | Grammatical correctness throughout |
| Spelling | 5 | Zero spelling errors |
| Tone | 4 | Professional, confident, appropriate voice |
| Clarity | 4 | Clear, concise, unambiguous writing |

### Dimension 4 — ATS Optimization (15 pts)

| Criteria | Max Pts | What to Evaluate |
|----------|---------|------------------|
| Keywords | 6 | Industry-relevant keywords present |
| Standard Headings | 4 | ATS-recognizable section titles |
| Format Compatibility | 5 | No tables, images, or complex layouts that break ATS |

### Dimension 5 — Impact & First Impression (10 pts)

| Criteria | Max Pts | What to Evaluate |
|----------|---------|------------------|
| 6-Second Test | 4 | Does the resume grab attention in 6 seconds? |
| Career Story | 3 | Clear narrative and career progression |
| Professionalism | 3 | Overall professional presentation |

---

## Grade Scale

| Grade | Score | Meaning |
|-------|-------|---------|
| A+ | 95–100 | Exceptional — ready for top-tier applications |
| A  | 90–94 | Excellent — very competitive |
| B+ | 85–89 | Good — minor refinements needed |
| B  | 80–84 | Solid — some areas to strengthen |
| C+ | 75–79 | Average — notable improvement needed |
| C  | 70–74 | Below average — significant work needed |
| D  | 60–69 | Weak — major overhaul recommended |
| F  | < 60 | Critical — near-complete rewrite needed |

---

## Evaluation Process

### Step 1 — Section-by-Section Analysis

For each resume section:
- What works well (specific examples from the resume)
- What needs improvement (specific examples)
- Concrete rewrite suggestion with **Before → After**

### Step 2 — Score Each Dimension

For each of the 5 dimensions:
- Assign numeric score with brief justification
- Call out the top issue holding the score back

### Step 3 — Prioritize Improvements

Rank all suggestions:
- 🔴 **Critical** — Must fix; could cause immediate rejection
- 🟡 **Important** — Should fix; significantly boosts competitiveness
- 🟢 **Nice to Have** — Optional polish for extra edge

### Step 4 — Role Fit (if target_role provided)

- Fit score out of 10
- Estimated competitive percentile ("Likely in the top X% of applicants")
- 3 biggest strengths for this specific role
- 3 biggest gaps compared to an ideal candidate

---

## Output Format

```
## 📊 Resume Score: XX / 100 — Grade: [Letter]

---

## 📈 Dimension Breakdown

| Dimension | Score | Max | Key Issue |
|-----------|-------|-----|-----------|
| Content Quality | X | 30 | [one-line summary] |
| Structure & Formatting | X | 25 | [one-line summary] |
| Language & Grammar | X | 20 | [one-line summary] |
| ATS Optimization | X | 15 | [one-line summary] |
| Impact & Impression | X | 10 | [one-line summary] |
| **Total** | **XX** | **100** | |

---

## ✅ Top Strengths

1. **[Strength]** — [specific example from resume and why it's effective]
2. **[Strength]** — [specific example]
3. **[Strength]** — [specific example]

---

## 🔧 Improvement Suggestions

### 🔴 Critical

**1. [Issue Title]**
- **Problem**: [what's wrong]
- **Before**: "[exact text from resume]"
- **After**: "[suggested rewrite]"
- **Why**: [impact on the reader/ATS]

### 🟡 Important

**1. [Issue Title]**
- **Before**: "[current text]"
- **After**: "[improved text]"

### 🟢 Nice to Have

**1. [Issue Title]**
- [suggestion with rationale]

---

## 🎯 Role Fit Assessment

*(only if target_role is provided)*

| Metric | Value |
|--------|-------|
| **Fit Score** | X / 10 |
| **Competitive Position** | Top ~X% of applicants (estimated) |

### Strengths for This Role
1. [strength]
2. [strength]
3. [strength]

### Gaps to Address
1. [gap + how to address it]
2. [gap + how to address it]
3. [gap + how to address it]

---

## 📋 5-Step Action Plan

1. **[Action]** — [expected impact] ⏱ [estimated effort]
2. **[Action]** — [expected impact] ⏱ [estimated effort]
3. **[Action]** — [expected impact] ⏱ [estimated effort]
4. **[Action]** — [expected impact] ⏱ [estimated effort]
5. **[Action]** — [expected impact] ⏱ [estimated effort]
```

# Resume / CV Assistant — Persona & Guidelines
You are **Resume / CV Assistant**, an expert career coach and professional resume writer. You have deep expertise in HR practices, ATS (Applicant Tracking Systems), recruitment workflows, and resume / CV writing across industries including tech, finance, healthcare, academia, and creative fields.
## Your Persona

- Professional, encouraging, and detail-oriented
- You respect the user's original content — you enhance and improve, never fabricate
- You provide clear reasoning behind every suggestion
- You support both **English** and **Chinese** resumes natively

## Core Principles

1. **Honesty first** — never invent achievements, inflate titles, or add skills the user doesn't have
2. **ATS-friendly** — all outputs should pass through Applicant Tracking Systems cleanly
3. **Impact-driven** — focus on measurable results and strong action verbs
4. **Audience-aware** — adapt tone and content for the target industry and role
5. **Completeness** — check every detail, from dates to spelling to formatting consistency

## Resume Structure Standards

A well-structured resume includes:

| Section | Required | Notes |
|---------|----------|-------|
| Contact Information | ✅ | Name, email, phone, location, LinkedIn |
| Professional Summary | ✅ | 2-3 sentences, tailored to role |
| Work Experience | ✅ | Reverse chronological, quantified achievements |
| Education | ✅ | Degree, school, date, honors if notable |
| Skills | ✅ | Categorized: technical, tools, languages |
| Certifications | Optional | Industry-relevant certifications |
| Projects | Optional | For technical/creative roles |
| Publications | Optional | For academic/research roles |

## Quality Standards

- Zero spelling or grammar errors
- Consistent formatting: dates, bullets, capitalization, punctuation
- Active voice with strong action verbs (led, built, reduced, launched)
- Quantified results: numbers, percentages, dollar amounts, timeframes
- Appropriate length: 1 page for < 10 years, 2 pages max for senior roles
- No personal pronouns (I, me, my, we)
- No irrelevant personal details (age, photo, marital status — unless culturally required)
- ATS-safe formatting: no tables/images/columns in text-based versions

## Language Support

### English Resumes
- Follow US/UK conventions as appropriate
- Use standard section headings: "Experience", "Education", "Skills"

### Chinese Resumes (中文简历)
- 使用标准板块标题：「个人简介」「工作经历」「教育背景」「专业技能」
- 注意中英文混排时的空格规范
- 日期格式统一：2024年1月 - 至今
- 量化成果用阿拉伯数字

## Natural Language Understanding

You can understand both **slash commands** (`/resume polish`) and **natural language requests**. When a user speaks naturally, map their intent to the correct command:

### Intent Mapping

| User Says (examples) | Mapped Command | Notes |
|----------------------|----------------|-------|
| "Polish my resume" / "Fix my resume" / "Improve my resume" / "Review my resume" | `/resume polish` | Any request to improve, fix, or review resume content |
| "Help me create a resume for [role]" / "Create a resume for a software engineer" / "Write a resume for [role]" | `/resume customize` | Creating or writing for a specific role implies customization |
| "Tailor my resume for this job description: ..." / "Customize for [company/role]" / "Adapt my resume for [JD]" | `/resume customize` | Explicit tailoring or JD-matching requests |
| "Optimize my resume for ATS" / "Make my resume ATS-friendly" | `/resume polish` | ATS optimization is part of the polish checklist |
| "Convert my resume to PDF" / "Export as Word" / "Give me a LaTeX version" | `/resume export` | Any format conversion request |
| "Score my resume" / "Rate my resume" / "How good is my resume?" / "Evaluate my resume" | `/resume score` | Any evaluation or rating request |
| "What's wrong with my resume?" / "What can I improve?" | `/resume score` | Diagnostic questions map to scoring |

### Handling Ambiguity

- If the user's intent is unclear, **ask a clarifying question** rather than guessing
- If a user provides a resume without a specific request, default to **score** (give them an overview first)
- If a user says "help me with my resume" without more context, briefly list all available capabilities and ask what they'd like to do
- If a user provides both a resume and a job description in a single message, default to **customize**

### Conversational Flow

You should maintain a natural conversation. When a user says something like:

> "Create a resume for a software engineer position"

You should:
1. Ask for their background information (work experience, education, skills, projects)
2. Ask for any specific job posting they're targeting (optional)
3. Generate the resume using the **customize** workflow
4. Offer to **polish**, **score**, or **export** the result

When a user says:

> "Here's my resume, can you help?"

You should:
1. First **score** the resume to identify the current state
2. Present the scores and key findings
3. Suggest next steps: polish → customize → export

{
  "name": "resume-assistant",
  "version": "1.0.0",
"description": "AI-powered resume / CV assistant: polish resumes and CVs, customize for jobs, export to Word/Markdown/HTML/LaTeX/PDF, and score with actionable feedback.",
  "author": "resume-assistant-team",
  "license": "MIT",
  "keywords": ["resume", "cv", "career", "polish", "export", "scoring", "job-search"],
  "commands": [
    {
      "name": "polish",
      "description": "Polish and improve resume content with a comprehensive checklist review.",
      "usage": "/resume polish",
      "arguments": [
        {
          "name": "resume_content",
          "description": "The resume content to polish (plain text or Markdown).",
          "required": true,
          "type": "string"
        },
        {
          "name": "language",
          "description": "Resume language: 'en' for English, 'zh' for Chinese.",
          "required": false,
          "type": "string",
          "default": "en"
        }
      ]
    },
    {
      "name": "customize",
      "description": "Tailor a resume for a specific job position with keyword optimization.",
      "usage": "/resume customize",
      "arguments": [
        {
          "name": "resume_content",
          "description": "The resume content to customize.",
          "required": true,
          "type": "string"
        },
        {
          "name": "job_description",
          "description": "The target job description or job title.",
          "required": true,
          "type": "string"
        },
        {
          "name": "language",
          "description": "Resume language: 'en' for English, 'zh' for Chinese.",
          "required": false,
          "type": "string",
          "default": "en"
        }
      ]
    },
    {
      "name": "export",
      "description": "Export a resume to Word, Markdown, HTML, LaTeX, or PDF format.",
      "usage": "/resume export",
      "arguments": [
        {
          "name": "resume_content",
          "description": "The resume content to export (Markdown format preferred).",
          "required": true,
          "type": "string"
        },
        {
          "name": "format",
          "description": "Target export format.",
          "required": true,
          "type": "string",
          "enum": ["word", "markdown", "html", "latex", "pdf"]
        },
        {
          "name": "template",
          "description": "Template style for the export.",
          "required": false,
          "type": "string",
          "default": "professional",
          "enum": ["professional", "modern", "minimal", "academic"]
        }
      ]
    },
    {
      "name": "score",
      "description": "Score an existing resume and provide strengths, weaknesses, and actionable improvement suggestions.",
      "usage": "/resume score",
      "arguments": [
        {
          "name": "resume_content",
          "description": "The resume content to evaluate.",
          "required": true,
          "type": "string"
        },
        {
          "name": "target_role",
          "description": "Optional target role to evaluate the resume against.",
          "required": false,
          "type": "string"
        },
        {
          "name": "language",
          "description": "Resume language: 'en' for English, 'zh' for Chinese.",
          "required": false,
          "type": "string",
          "default": "en"
        }
      ]
    }
  ],
  "prompts": {
    "system": "prompts/system.md",
    "polish": "prompts/polish.md",
    "customize": "prompts/customize.md",
    "export": "prompts/export.md",
    "score": "prompts/score.md"
  },
  "templates": {
    "professional": "templates/professional.md",
    "modern": "templates/modern.md",
    "minimal": "templates/minimal.md",
    "academic": "templates/academic.md"
  },
  "config": {
    "max_resume_length": 10000,
    "supported_languages": ["en", "zh"],
    "supported_export_formats": ["word", "markdown", "html", "latex", "pdf"]
  },
  "conversation_starters": [
    "Create a resume for a software engineer position",
    "Polish my resume and fix any issues",
    "Optimize my resume for ATS",
    "Tailor my resume for this job description: [paste JD]",
    "Convert my resume to PDF",
    "Score my resume and tell me how to improve",
    "帮我写一份产品经理的简历",
    "润色我的简历",
    "帮我把简历转成 Word 格式",
    "给我的简历打个分"
  ],
  "natural_language_triggers": {
    "polish": [
      "polish my resume",
      "fix my resume",
      "improve my resume",
      "review my resume",
      "optimize for ATS",
      "make ATS-friendly",
      "proofread my resume",
      "check my resume",
      "润色简历",
      "优化简历",
      "修改简历",
      "检查简历"
    ],
    "customize": [
      "create a resume for",
      "write a resume for",
      "tailor my resume",
      "customize my resume",
      "adapt my resume for",
      "target this job",
      "match this job description",
      "写一份简历",
      "定制简历",
      "针对这个职位"
    ],
    "export": [
      "convert to",
      "export as",
      "export to",
      "save as",
      "give me a PDF",
      "generate Word",
      "generate HTML",
      "generate LaTeX",
      "转换格式",
      "导出为",
      "转成PDF",
      "转成Word"
    ],
    "score": [
      "score my resume",
      "rate my resume",
      "evaluate my resume",
      "how good is my resume",
      "what's wrong with my resume",
      "grade my resume",
      "assess my resume",
      "给简历打分",
      "评估简历",
      "简历怎么样"
    ]
  }
}

name: resume-assistant
version: 1.0.0
description: >-
  AI-powered resume / CV assistant: polish resumes and CVs, customize for jobs,
  export to Word/Markdown/HTML/LaTeX/PDF, and score with actionable feedback.
author: resume-assistant-team
license: MIT
keywords:
  - resume
  - cv
  - career
  - polish
  - export
  - scoring
  - job-search

# ============================================================
# Commands
# ============================================================
commands:
  # ---------- /resume polish ----------
  - name: polish
    description: Polish and improve resume content with a comprehensive checklist review.
    usage: /resume polish
    arguments:
      - name: resume_content
        description: The resume content to polish (plain text or Markdown).
        required: true
        type: string
      - name: language
        description: "Resume language: 'en' for English, 'zh' for Chinese."
        required: false
        type: string
        default: en

  # ---------- /resume customize ----------
  - name: customize
    description: Tailor a resume for a specific job position with keyword optimization.
    usage: /resume customize
    arguments:
      - name: resume_content
        description: The resume content to customize.
        required: true
        type: string
      - name: job_description
        description: The target job description or job title.
        required: true
        type: string
      - name: language
        description: "Resume language: 'en' for English, 'zh' for Chinese."
        required: false
        type: string
        default: en

  # ---------- /resume export ----------
  - name: export
    description: Export a resume to Word, Markdown, HTML, LaTeX, or PDF format.
    usage: /resume export
    arguments:
      - name: resume_content
        description: The resume content to export (Markdown format preferred).
        required: true
        type: string
      - name: format
        description: Target export format.
        required: true
        type: string
        enum:
          - word
          - markdown
          - html
          - latex
          - pdf
      - name: template
        description: Template style for the export.
        required: false
        type: string
        default: professional
        enum:
          - professional
          - modern
          - minimal
          - academic

  # ---------- /resume score ----------
  - name: score
    description: >-
      Score an existing resume and provide strengths, weaknesses,
      and actionable improvement suggestions.
    usage: /resume score
    arguments:
      - name: resume_content
        description: The resume content to evaluate.
        required: true
        type: string
      - name: target_role
        description: Optional target role to evaluate the resume against.
        required: false
        type: string
      - name: language
        description: "Resume language: 'en' for English, 'zh' for Chinese."
        required: false
        type: string
        default: en

# ============================================================
# Prompts
# ============================================================
prompts:
  system: prompts/system.md
  polish: prompts/polish.md
  customize: prompts/customize.md
  export: prompts/export.md
  score: prompts/score.md

# ============================================================
# Templates
# ============================================================
templates:
  professional: templates/professional.md
  modern: templates/modern.md
  minimal: templates/minimal.md
  academic: templates/academic.md

# ============================================================
# Configuration
# ============================================================
config:
  max_resume_length: 10000
  supported_languages:
    - en
    - zh
  supported_export_formats:
    - word
    - markdown
    - html
    - latex
    - pdf

# ============================================================
# Conversation Starters (Quick Start examples)
# ============================================================
conversation_starters:
  - "Create a resume for a software engineer position"
  - "Polish my resume and fix any issues"
  - "Optimize my resume for ATS"
  - "Tailor my resume for this job description: [paste JD]"
  - "Convert my resume to PDF"
  - "Score my resume and tell me how to improve"
  - "帮我写一份产品经理的简历"
  - "润色我的简历"
  - "帮我把简历转成 Word 格式"
  - "给我的简历打个分"

# ============================================================
# Natural Language Triggers (intent → command mapping)
# ============================================================
natural_language_triggers:
  polish:
    - "polish my resume"
    - "fix my resume"
    - "improve my resume"
    - "review my resume"
    - "optimize for ATS"
    - "make ATS-friendly"
    - "proofread my resume"
    - "check my resume"
    - "润色简历"
    - "优化简历"
    - "修改简历"
    - "检查简历"
  customize:
    - "create a resume for"
    - "write a resume for"
    - "tailor my resume"
    - "customize my resume"
    - "adapt my resume for"
    - "target this job"
    - "match this job description"
    - "写一份简历"
    - "定制简历"
    - "针对这个职位"
  export:
    - "convert to"
    - "export as"
    - "export to"
    - "save as"
    - "give me a PDF"
    - "generate Word"
    - "generate HTML"
    - "generate LaTeX"
    - "转换格式"
    - "导出为"
    - "转成PDF"
    - "转成Word"
  score:
    - "score my resume"
    - "rate my resume"
    - "evaluate my resume"
    - "how good is my resume"
    - "what's wrong with my resume"
    - "grade my resume"
    - "assess my resume"
    - "给简历打分"
    - "评估简历"
    - "简历怎么样"

# {{name}}, {{title}}

{{department}} · {{university_affiliation}}
{{email}} · {{phone}} · {{office_location}}
[Google Scholar]({{google_scholar}}) · [ORCID]({{orcid}})

---

## Research Interests

{{research_interests}}

---

## Education

**{{degree}}** in {{field}}, {{university}} ({{year}})
- Dissertation: *{{dissertation_title}}*
- Advisor: {{advisor}}

---

## Academic Appointments

**{{title}}**, {{department}}, {{university}} ({{start}} – {{end}})

---

## Publications

### Peer-Reviewed Journal Articles

1. {{authors}} ({{year}}). "{{title}}." *{{journal}}*, {{volume}}({{issue}}), {{pages}}. doi:{{doi}}

### Conference Papers

1. {{authors}} ({{year}}). "{{title}}." *{{conference}}*, {{location}}.

---

## Research & Grants

### {{project_title}}
*{{funder}} · {{grant_id}} · {{amount}}* ({{start}} – {{end}})

{{description}}

---

## Teaching

### {{course_title}} ({{course_code}})
{{university}} · {{semesters}}
- {{description}}

---

## Awards & Honors

- {{award}}, {{body}} ({{year}})

---

## Professional Service

- **Reviewer**: {{journals}}
- **Committee**: {{committees}}
- **Conference**: {{roles}}

---

## References

Available upon request.

---

<!-- Template: Academic
     Style: Formal academic CV, multi-page supported
     Best for: Faculty, postdoc, research, PhD applications
     Font suggestion: Times New Roman 11pt or Garamond 11pt
     Color: Dark navy #1a1a2e for headings
     Note: Academic CVs are NOT limited to 1-2 pages -->

<!DOCTYPE html>
<html lang="en">
<head>
    <meta charset="UTF-8">
    <meta name="viewport" content="width=device-width, initial-scale=1.0">
    <title>{{name}} — Resume</title>
    <style>
        /* === Reset & Base === */
        *, *::before, *::after { box-sizing: border-box; margin: 0; padding: 0; }

        body {
            font-family: 'Segoe UI', 'Helvetica Neue', Arial, sans-serif;
            font-size: 14px;
            line-height: 1.6;
            color: #333;
            background: #f5f5f5;
        }

        /* === Resume Container === */
        .resume {
            max-width: 800px;
            margin: 40px auto;
            background: #fff;
            padding: 48px 56px;
            box-shadow: 0 2px 12px rgba(0,0,0,0.08);
        }

        /* === Header === */
        .header {
            text-align: center;
            margin-bottom: 28px;
            padding-bottom: 18px;
            border-bottom: 2px solid var(--primary, #2c3e50);
        }
        .header h1 {
            font-size: 26px;
            font-weight: 700;
            color: var(--primary, #2c3e50);
            letter-spacing: 1px;
            margin-bottom: 6px;
        }
        .header .contact {
            font-size: 13px;
            color: #666;
        }
        .header .contact a {
            color: var(--primary, #2c3e50);
            text-decoration: none;
        }
        .header .contact .sep { margin: 0 6px; }

        /* === Sections === */
        .section { margin-bottom: 22px; }
        .section h2 {
            font-size: 15px;
            font-weight: 700;
            color: var(--primary, #2c3e50);
            text-transform: uppercase;
            letter-spacing: 1.5px;
            border-bottom: 1px solid #ddd;
            padding-bottom: 5px;
            margin-bottom: 12px;
        }

        /* === Experience === */
        .entry { margin-bottom: 16px; }
        .entry .row {
            display: flex;
            justify-content: space-between;
            align-items: baseline;
        }
        .entry .title { font-weight: 700; font-size: 14px; color: var(--primary, #2c3e50); }
        .entry .company { font-weight: 600; color: #555; }
        .entry .meta { font-size: 13px; color: #888; }
        .entry ul { margin-top: 5px; padding-left: 20px; }
        .entry ul li { font-size: 13.5px; margin-bottom: 3px; line-height: 1.55; }

        /* === Skills Grid === */
        .skills-grid {
            display: grid;
            grid-template-columns: 130px 1fr;
            gap: 5px 14px;
        }
        .skills-grid .cat { font-weight: 700; font-size: 13px; color: var(--primary, #2c3e50); }
        .skills-grid .val { font-size: 13px; color: #555; }

        /* === Print === */
        @media print {
            body { background: none; }
            .resume { margin: 0; padding: 28px 36px; box-shadow: none; max-width: none; }
            a { color: #333 !important; text-decoration: none !important; }
            @page { margin: 0.5in; size: letter; }
        }

        /* === Professional (default) — navy #2c3e50 === */
        .resume.professional { --primary: #2c3e50; }

        /* === Modern — teal #00897b === */
        .resume.modern { --primary: #00897b; border-left: 4px solid #00897b; }

        /* === Minimal — charcoal #333 === */
        .resume.minimal { --primary: #333; }
        .resume.minimal .header { border-bottom: none; }
        .resume.minimal .section h2 { text-transform: none; letter-spacing: 0; font-size: 14px; }

        /* === Academic — dark navy, serif === */
        .resume.academic { --primary: #1a1a2e; font-family: Georgia, 'Times New Roman', serif; }
        .resume.academic .header h1 { font-size: 22px; }
        .resume.academic .section h2 { text-transform: none; font-style: italic; }
    </style>
</head>
<body>
    <div class="resume {{template_class}}">

        <div class="header">
            <h1>{{name}}</h1>
            <div class="contact">
                {{email}} <span class="sep">·</span> {{phone}} <span class="sep">·</span> {{location}}
                <br>
                <a href="{{linkedin}}">LinkedIn</a> <span class="sep">·</span> <a href="{{portfolio}}">Portfolio</a>
            </div>
        </div>

        <div class="section">
            <h2>Professional Summary</h2>
            <p>{{summary}}</p>
        </div>

        <div class="section">
            <h2>Experience</h2>
            <!-- Repeat .entry for each position -->
            <div class="entry">
                <div class="row">
                    <span class="title">{{job_title}}</span>
                    <span class="meta">{{start_date}} – {{end_date}}</span>
                </div>
                <div class="row">
                    <span class="company">{{company}}</span>
                    <span class="meta">{{location}}</span>
                </div>
                <ul>
                    <li>{{bullet}}</li>
                </ul>
            </div>
        </div>

        <div class="section">
            <h2>Education</h2>
            <div class="entry">
                <div class="row">
                    <span class="title">{{degree}} in {{major}}</span>
                    <span class="meta">{{graduation_date}}</span>
                </div>
                <span class="company">{{university}}</span>
            </div>
        </div>

        <div class="section">
            <h2>Skills</h2>
            <div class="skills-grid">
                <span class="cat">Technical:</span>
                <span class="val">{{technical_skills}}</span>
                <span class="cat">Tools:</span>
                <span class="val">{{tools}}</span>
                <span class="cat">Languages:</span>
                <span class="val">{{languages}}</span>
            </div>
        </div>

    </div>
</body>
</html>

# {{name}}

{{email}} · {{phone}} · {{location}} · [LinkedIn]({{linkedin}})

---

{{summary}}

---

## Experience

**{{job_title}}**, {{company}} ({{start_date}} – {{end_date}})

- {{bullet_1}}
- {{bullet_2}}
- {{bullet_3}}

---

## Education

**{{degree}}, {{major}}** — {{university}} ({{graduation_date}})

---

## Skills

{{skills_comma_separated}}

---

<!-- Template: Minimal
     Style: Ultra-clean, whitespace-focused, maximum content density
     Best for: Senior professionals, engineering, experienced candidates
     Font suggestion: System UI 11pt
     Color: Charcoal #333 only — monochrome design -->

# {{name}}

> {{summary}}

📧 {{email}} · 📱 {{phone}} · 📍 {{location}}
🔗 [LinkedIn]({{linkedin}}) · 🌐 [Portfolio]({{portfolio}})

---

## 💼 Experience

### {{job_title}}
**{{company}}** · {{job_location}} · `{{start_date}} – {{end_date}}`

- {{bullet_1}}
- {{bullet_2}}
- {{bullet_3}}

---

## 🛠 Skills

| Category | Skills |
|----------|--------|
| **Core** | {{core_skills}} |
| **Tools** | {{tools}} |
| **Languages** | {{languages}} |

---

## 🎓 Education

### {{degree}} in {{major}}
**{{university}}** · *{{graduation_date}}*
{{honors_or_gpa}}

---

## 🏆 Certifications & Awards

- {{certification}} — {{issuer}} ({{date}})

---

## 🚀 Projects

### {{project_name}}
*{{tech_stack}}* · [Link]({{project_url}})

{{project_description}}

**Impact:** {{project_impact}}

---

<!-- Template: Modern
     Style: Contemporary with emoji icons, tables, and code-style dates
     Best for: Tech, startups, product, marketing, design
     Font suggestion: Inter 11pt or Helvetica Neue 11pt
     Color: Teal #00897b for headings
     Note: For ATS submission, switch to Professional template -->

# {{name}}

**{{email}} | {{phone}} | {{location}}**
**[LinkedIn]({{linkedin}}) | [Portfolio]({{portfolio}})**

---

## Professional Summary

{{summary}}

---

## Work Experience

### {{job_title}} | {{company}}
*{{start_date}} – {{end_date}} | {{job_location}}*

- {{bullet_1}}
- {{bullet_2}}
- {{bullet_3}}

---

## Education

### {{degree}} in {{major}}
**{{university}}** | *{{graduation_date}}*
- {{honors_or_gpa}}

---

## Skills

**Technical:** {{technical_skills}}

**Tools:** {{tools}}

**Languages:** {{languages}}

---

## Certifications

- {{certification}} — {{issuer}} ({{date}})

---

<!-- Template: Professional
     Style: Classic, conservative, ATS-optimized
     Best for: Corporate, finance, consulting, law, healthcare, government
     Font suggestion: Calibri 11pt or Garamond 11pt
     Color: Navy #2c3e50 for headings -->