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resume-manager

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. Use when this capability is needed.

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ソース情報

リポジトリ
tomevault-io/skills-registry
ソースの最終更新活動
2026年4月28日 22:53
検出された SKILL.md の言語
英語
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0
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SKILL.md
ソースの指示 · 読み取り専用プレビュー
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. Use when this capability is needed.
metadata
{"author":"ailabs-393"}
# 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: ```bash 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: ```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 directory path. **Confirmation:** ``` Perfect! I've extracted and saved your professional profile: • Personal Information: ✓ • Work Experience: X positions • Projects: X projects • Education: X degrees • Skills: X categories • Certifications: X certifications Your resume database is now ready. I can generate customized resumes for any job you're applying to. Just tell me the job title or description, and I'll create a tailored one-page PDF highlighting your most relevant experience and skills. ``` ### 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: ``` To create the perfect resume for this position, I need to understand the role better. 1. What's the job title? 2. Can you share the job description or key requirements? 3. What are the must-have skills or technologies mentioned? ``` **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: ```python import sys sys.path.append('[SKILL_DIR]/scripts') from pdf_generator import generate_resume # Keywords from job description job_keywords = [ "python", "aws", "kubernetes", "microservices", "agile", "rest api", "postgresql", "docker" ] job_title = "Senior Backend Engineer" # Output path output_path = f"~/Downloads/{job_title.replace(' ', '_')}_Resume.pdf" # Generate resume generate_resume( output_path=output_path, job_title=job_title, job_keywords=job_keywords ) ``` 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:** ```python from resume_db import add_experience new_exp = { "position": "Lead Software Engineer", "company": "New Company", "location": "Remote", "start_date": "Mar 2024", "end_date": "Present", "description": "Leading backend infrastructure team", "highlights": [ "Scaled services to handle 50M+ daily requests", "Reduced infrastructure costs by 30% through optimization", "Built CI/CD pipeline improving deployment speed by 10x" ], "technologies": ["Go", "Kubernetes", "PostgreSQL", "AWS"] } add_experience(new_exp) ``` **Adding New Project:** ```python from resume_db import add_project new_project = { "name": "Real-time Analytics Dashboard", "date": "2024", "description": "Built real-time analytics platform processing 1M+ events/minute", "highlights": [ "Implemented using streaming architecture with Kafka and Redis", "Created interactive visualizations with React and D3.js", "Achieved sub-second query latency on complex aggregations" ], "technologies": ["React", "Kafka", "Redis", "Python", "TimescaleDB"], "link": "github.com/username/analytics-dashboard" } add_project(new_project) ``` **Updating Skills:** ```python from resume_db import add_skill, update_skills # Add individual skill add_skill("Languages", "Rust") add_skill("Tools", "Terraform") # Or update entire skills dictionary skills = { "Languages": ["Python", "Go", "JavaScript", "Rust", "SQL"], "Frameworks": ["Django", "FastAPI", "React", "Next.js"], "Cloud & DevOps": ["AWS", "Kubernetes", "Docker", "Terraform", "CI/CD"], "Databases": ["PostgreSQL", "MongoDB", "Redis", "Elasticsearch"], "Practices": ["Microservices", "TDD", "Agile", "System Design"] } update_skills(skills) ``` **Adding Certification:** ```python from resume_db import add_certification cert = { "name": "Google Cloud Professional Architect", "issuer": "Google Cloud", "date": "2024", "credential_id": "ABC123", "link": "credentials.google.com/..." } add_certification(cert) ``` ### Step 5: View and Manage Resume Data **View Summary:** ```bash python3 scripts/resume_db.py summary ``` **View Specific Sections:** ```bash # Personal info python3 scripts/resume_db.py get_personal_info # All experiences python3 scripts/resume_db.py get_experiences # All projects python3 scripts/resume_db.py get_projects # Education python3 scripts/resume_db.py get_education # Skills python3 scripts/resume_db.py get_skills ``` **Search Across All Data:** ```bash python3 scripts/resume_db.py search "machine learning" ``` **Export All Data:** ```bash python3 scripts/resume_db.py export > resume_backup.json ``` ### 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** ``` User: "Help me create a resume for job applications" Claude: [Checks database - finds not initialized] 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 [User provides resume] Claude: [Extracts data and initializes database] Perfect! I've extracted and saved your professional profile: • Personal Information: ✓ • Work Experience: 3 positions • Projects: 2 projects • Education: 1 degree • Skills: 4 categories • Certifications: 2 certifications Your resume database is ready! Tell me about a job you're applying to and I'll generate a customized one-page PDF resume. ``` **Example 2: Generate Resume for Specific Role** ``` User: "I need a resume for a Senior Backend Engineer position at a fintech startup" Claude: [Database initialized] Great! To create the perfect resume for this Senior Backend Engineer role, can you share the job description or tell me about the key requirements? User: [Shares job description mentioning Python, AWS, microservices, PostgreSQL, etc.]
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この SKILL.md は非常に大きいため、SkillsMP では最初のセクションだけを表示しています。 GitHubで見る