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 d

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: 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: 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: Replace [SKILL DIR] with the actual skill directory path. Confirmation: Step 3: Generate Tailored Resume for Job Application When a user requests a resume for a specific role: Step 3.1: Understand the Target Role Ask the user about the role: Step 3.2: Extract Keywords and Requirements From the job description, identify: Required technical skills Preferred technologies Key responsibilities Important keywords for ATS Industry specific terms Experience level indicators Step 3.3: Generate Tailored Resume Use the PDF generator to create a customized resume: The generator will: Filter experiences relevant to the keywords Select projects that match the role Highlight applicable skills Keep it to one page Use professional styling Optimize for ATS parsing Step 3.4: Review and Iterate After generating: 1. Inform the user where the PDF was saved 2. Offer to make adjustments 3. Suggest additional highlights if space allows 4. Recommend customizations for specific requirements Step 4: Update Resume Database When users want to add or update information: Adding New Experience: Adding New Project: Updating Skills: Adding Certification: Step 5: View and Manage Resume Data View Summary: View Specific Sections: Search Across All Data: Export All Data: Step 6: Resume Optimization Tips When generating resumes, provide these optimization tips: Content Optimization: Use action verbs (Led, Built, Architected, Improved, Reduced) Include quantifiable metrics (X% improvement, Y users, Z revenue) Tailor highlights to match job requirements Keep bullet points concise (1 2 lines max) Focus on impact, not just responsibilities ATS Optimization: Use standard section headers (Experience, Education, Skills) Include keywords from job description naturally Avoid tables, columns, headers/footers Use standard fonts (which the PDF generator does) Spell out acronyms once: "Application Programming Interface (API)" One Page Strategy: Prioritize recent and relevant experience (last 5 7 years) Include 3 4 bullet points per role Limit to 2 3 projects maximum Condense older or less relevant experience Remove outdated technologies unless specifically required Best Practices 1. Keep Data Current Update experiences as projects complete Add new skills as you learn them Maintain quantifiable achievements Record certifications immediately 2. Write Effective Bullet Points Start with action verbs Include metrics and outcomes Show progression and impact Use the STAR method (Situation, Task, Action, Result) 3. Organize Skills Strategically Group by category for clarity Put most relevant skills first Remove outdated technologies Be honest about proficiency levels 4. Tailor Every Resume Match keywords to job description Emphasize relevant experience Reorder bullet points by relevance Adjust technical skills section 5. Maintain Professional Tone Use third person implied (no "I") Keep language concise and clear Avoid jargon unless industry standard Proofread for errors Example Interactions Example 1: Initial Setup Example 2: Generate Resume for Specific Role Example 3: Update Experience Example 4: Multiple Resume Versions Example 5: Resume Review and Optimization Technical Notes Data Storage: Location: ~/.claude/resume data.json Format: Structured JSON Backup: Use python3 scripts/resume db.py export PDF Generation: Library: reportlab (requires: pip install reportlab ) Page size: US Letter (8.5" x 11") Margins: 0.75 inches all sides Font: Helvetica family Optimized for: One page resumes, ATS compatibility Resume Styling: Professional color scheme (blues and grays) Clear section headers with underlines Consistent spacing and formatting Bullet points for achievements Contact info in header Technical skills as comma separated lists Database Commands: PDF Generation Commands: Data Structure Example: Resources scripts/resume db.py Complete database management system providing: Data initialization and persistence CRUD operations for all resume sections Relevance based filtering for experiences/projects Keyword based skill matching Search functionality across all data Data export and backup CLI interface for all operations scripts/pdf generator.py Professional PDF generation engine: ReportLab based PDF creation Custom styling matching professional standards One page optimization Keyword based content filtering Relevance scoring for experiences/projects ATS friendly formatting Command line interface assets/resume template.json Sample resume data structure showing: Complete data format Best practices for content Example bullet points with metrics Proper date formatting Skill categorization All supported sections

resume-manager