/resume-manager

name: resume-manager
description: This skill should be used whenever users need help with resume creation, updating professional profiles, tracking career experiences, managing projects portfolio, or generating tailored resumes for job applications. On first use, extracts data from user's existing resume and maintains a structured database of experiences, projects, education, and skills. Generates professionally styled one-page PDF resumes customized for specific job roles by selecting only the most relevant information from the database.

Resume Manager

Overview

This skill transforms Claude into a comprehensive resume management system that maintains a structured database of your professional profile and generates tailored, professionally styled PDF resumes for specific job applications. The skill intelligently selects and highlights the most relevant experiences, projects, and skills based on the target role.

When to Use This Skill

Invoke this skill for resume-related tasks:

• Creating tailored resumes for job applications
• Updating professional experiences and projects
• Managing skills and certifications
• Tracking career progression
• Generating role-specific resumes
• Maintaining a comprehensive career portfolio
• Optimizing resume content for ATS systems

Workflow

Step 1: Check for Existing Data

Before any resume operations, check if the database is initialized:

python3 scripts/resume_db.py is_initialized

If output is "false", proceed to Step 2 (Initial Setup). If "true", proceed to Step 3 (Resume Operations).

Step 2: Initial Setup - Extract from Existing Resume

When no data exists, ask the user to provide their existing resume.

**Prompt the User:**

To help you create tailored resumes, I need to build a database of your professional
profile. Please provide your existing resume in one of these ways:

1. Upload your resume file (PDF, DOCX, or TXT)
2. Paste the content of your resume
3. Provide a link to your online resume/LinkedIn profile

I'll extract all the information and organize it in a structured database that I can
use to generate customized resumes for different job applications.

**Extracting Data from Resume:**

Once the user provides their resume, extract the following information:

**1. Personal Information:**

• Full name
• Email address
• Phone number
• Location (city, state/country)
• LinkedIn profile URL
• GitHub profile URL
• Personal website
• Professional summary/objective

**2. Work Experience:** For each role, extract:

• Position/Job title
• Company name
• Location
• Start date (format: "Mon YYYY" like "Jan 2022")
• End date (or "Present")
• Brief description
• Key highlights/achievements (bullet points)
• Technologies/tools used

**3. Projects:** For each project, extract:

• Project name
• Date or time period
• Description
• Key highlights/achievements
• Technologies used
• Link (if available)

**4. Education:** For each degree, extract:

• Degree name (e.g., "Bachelor of Science in Computer Science")
• School/University name
• Location
• Graduation date
• GPA (if mentioned)
• Honors (if any)
• Relevant coursework

**5. Skills:** Extract and categorize skills:

• Programming Languages
• Frameworks & Libraries
• Tools & Technologies
• Practices & Methodologies
• Soft skills

**6. Additional Sections:**

• Certifications (name, issuer, date)
• Awards & Honors
• Publications
• Volunteer work
• Languages spoken

**Saving the Extracted Data:**

After extraction, save to the database using Python:

import sys
import json
sys.path.append('[SKILL_DIR]/scripts')
from resume_db import initialize_from_data

resume_data = {
    "personal_info": {
        "name": "Full Name",
        "email": "email@example.com",
        "phone": "+1 (555) 123-4567",
        "location": "City, State",
        "linkedin": "linkedin.com/in/username",
        "github": "github.com/username",
        "website": "website.com",
        "summary": "Professional summary..."
    },
    "experiences": [
        {
            "position": "Senior Software Engineer",
            "company": "Company Name",
            "location": "City, State",
            "start_date": "Jan 2022",
            "end_date": "Present",
            "description": "Brief description",
            "highlights": [
                "Achievement 1 with quantifiable results",
                "Achievement 2 with impact metrics",
                "Achievement 3 with technologies used"
            ],
            "technologies": ["Python", "AWS", "Docker"]
        }
    ],
    "projects": [
        {
            "name": "Project Name",
            "date": "2023",
            "description": "Project description",
            "highlights": [
                "Key achievement or feature",
                "Impact or result"
            ],
            "technologies": ["React", "Node.js", "PostgreSQL"],
            "link": "github.com/username/project"
        }
    ],
    "education": [
        {
            "degree": "Bachelor of Science in Computer Science",
            "school": "University Name",
            "location": "City, State",
            "graduation_date": "May 2019",
            "gpa": "3.8/4.0",
            "honors": "Magna Cum Laude",
            "relevant_coursework": ["Data Structures", "Algorithms", "Machine Learning"]
        }
    ],
    "skills": {
        "Languages": ["Python", "JavaScript", "Java"],
        "Frameworks": ["React", "Django", "Spring"],
        "Tools": ["Docker", "AWS", "Git"],
        "Practices": ["Agile", "CI/CD", "TDD"]
    },
    "certifications": [
        {
            "name": "AWS Certified Solutions Architect",
            "issuer": "Amazon Web Services",
            "date": "2023"
        }
    ],
    "awards": [],
    "publications": [],
    "volunteer": [],
    "languages": ["English (Native)", "Spanish (Fluent)"],
    "interests": []
}

initialize_from_data(resume_data)

Replace `[SKILL_DIR]` with the actual skill direc