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简历解析。触发场景:用户上传简历文件要求解析、提取结构化信息。

媒体与内容

作者:51mee @51mee-com

许可证:MIT-0

MIT-0 ·免费使用、修改和重新分发。无需归因。

版本:v1.2.1

统计:⭐ 0 · 130 · 0 current installs · 0 all-time installs

0

安装量(当前) 0

🛡 VirusTotal :良性 · OpenClaw :良性

Package:51mee-com/51mee-resume-parse

安全扫描(ClawHub)

  • VirusTotal :良性
  • OpenClaw :良性

OpenClaw 评估

This instruction-only resume-parsing skill is internally coherent for extracting structured data from uploaded resumes, but it has minor instruction inconsistencies and lacks explicit guidance on PII handling and OCR implementation.

目的

The name/description (resume parsing) match the instructions: read uploaded resume files, extract text, call a large model, and return structured JSON. There are no unexpected required binaries, env vars, or installs that would be disproportionate to the stated purpose.

说明范围

Instructions stay within the resume-parsing task (read file, extract text, run LLM prompt, return JSON). However there are two inconsistencies: the prompt explicitly says '直接返回 JSON,不要额外解释' while a later '输出格式' section shows a human-readable Markdown summary — this is contradictory and can cause unpredictable outputs. The SKILL.md requires extracting text from images/PDFs but does not specify how (no OCR/tool instructions), and there is no guidance about handling or redacting sensitive PII before sending full resume text to the model.

安装机制

No install spec and no code files — instruction-only — so nothing will be downloaded or written to disk by the skill itself. This is the lowest-risk install profile.

证书

The skill requests no environment variables or credentials, which is appropriate. Note: processing resumes entails handling sensitive personal data (phones, emails, birthdates) — the skill does not declare any retention, redaction, or external transmission policies; ensure the hosting environment and model endpoint are acceptable for PII.

持久

always is false and the skill is user-invocable. It does not request persistent privileges or modify other skills/configs. Autonomous invocation is allowed by platform default but not excessive here.

综合结论

This skill appears to do what it says (parse uploaded resumes into structured JSON). Before installing, confirm the following: (1) Clarify expected output format — the prompt asks for raw JSON but the doc also shows a Markdown summary; decide which you need and test with examples. (2) Ensure the host supports text extraction/OCR for PDFs/JPG/PNG (the SKILL.md assumes you can extract text but doesn't provide tools). (3) Treat parsed resumes as …

安装(复制给龙虾 AI)

将下方整段复制到龙虾中文库对话中,由龙虾按 SKILL.md 完成安装。

请把本段交给龙虾中文库(龙虾 AI)执行:为本机安装 OpenClaw 技能「51mee Resume Parse」。简介:简历解析。触发场景:用户上传简历文件要求解析、提取结构化信息。。
请 fetch 以下地址读取 SKILL.md 并按文档完成安装:https://raw.githubusercontent.com/openclaw/skills/refs/heads/main/skills/51mee-com/51mee-resume-parse/SKILL.md
(来源:yingzhi8.cn 技能库)

SKILL.md

打开原始 SKILL.md(GitHub raw)

---
name: 51mee-resume-parse
description: 简历解析。触发场景:用户上传简历文件要求解析、提取结构化信息。
---

# 简历解析技能

## 功能说明

读取简历文件(PDF/DOC/DOCX/JPG/PNG),使用大模型提取结构化信息。

## 处理流程

1. **读取文件** - 用户上传简历时,读取文件内容
2. **提取文本** - 从文件中提取纯文本内容
3. **调用大模型** - 使用以下 prompt 解析
4. **返回 JSON** - 解析结果为结构化数据

## Prompt 模板

```
```html
{简历文本内容}
```
扮演一个简历分析专家,详细地分析上面的简历
1. 按照下方的typescript结构定义,返回json格式的ResumeInfo结构
2. 有数据就填上数据,简历上没有提到,相应的值即为null,绝对不要虚构新的或者删除定义中的字段
3. 不要做任何解释,直接返回json
4. 日期格式:"Y-m-d",如 "2025-01-01"; 年格式:"Y",如 "2025"
5. 手机号无区号,如"19821450628"

```typescript
export interface WorkExperience {
    startDate: string | null;
    endDate: string | null;
    company: string;
    industry: string | null;
    department: string | null;
    positionName: string;
    blueCollarPosition: boolean | null;
    responsibility: string | null;
    workPerformance: string | null;
    current: boolean | null;
    workDesc: string | null;
};

export interface ProjectExperience {
    name: string;
    startDate: string | null;
    endDate: string | null;
    roleName: string | null;
    projectDesc: string | null;
};

export interface EducationExperience {
    startDate: string | null;
    endDate: string | null;
    school: string;
    major: string | null;
    degreeName: string | null; // 高中、本科、专科、硕士、博士、其它
};

export interface ResumeInfo {
    name: string | null;
    gender: number | null; // 0=男, 1=女
    age: string | null;
    birthday: string | null;
    description: string | null;
    
    workExpList: WorkExperience[];
    projExpList: ProjectExperience[];
    eduExpList: EducationExperience[];
    
    expectPosition: {
        positionName: string | null;
        lowSalary: number | null;
        highSalary: number | null;
        locationName: string | null;
    };
    
    contact: {
        phone: string | null;
        weixin: string | null;
        email: string | null;
    };
    
    keywords: string[];
    awards: string[];
    englishCertificates: string[];
    professionalSkills: string;
}
```
```

## 返回数据结构

```json
{
  "name": "张三",
  "gender": 0,
  "age": "30",
  "birthday": "1995-01-15",
  "description": "5年Java开发经验...",
  
  "workExpList": [...],
  "projExpList": [...],
  "eduExpList": [...],
  
  "expectPosition": {...},
  "contact": {...},
  
  "keywords": ["Java", "Spring"],
  "awards": ["优秀员工"],
  "englishCertificates": ["CET-6"],
  "professionalSkills": "精通Java..."
}
```

## 输出格式

```markdown
## 简历解析结果

### 基本信息
- **姓名**: [name]
- **性别**: [男/女]
- **年龄**: [age]
- **生日**: [birthday]

### 联系方式
- **手机**: [phone]
- **微信**: [weixin]
- **邮箱**: [email]

### 工作经历
[遍历 workExpList]

### 项目经历
[遍历 projExpList]

### 教育经历
[遍历 eduExpList]

### 期望职位
- **职位**: [positionName]
- **薪资**: [lowSalary]K-[highSalary]K
- **地点**: [locationName]

### 关键词
[keywords]

### 奖项
[awards]

### 英语证书
[englishCertificates]

### 专业技能
[professionalSkills]
```

## 注意事项

- 支持格式:PDF、DOC、DOCX、JPG、PNG
- 日期格式统一为 `Y-m-d`
- 没有 的字段填 `null`
- 直接返回 JSON,不要额外解释