Skill Gap Analyzer

Compare your current skills against job market demands, identify gaps, and create prioritized learning roadmaps. This skill helps you understand exactly where you stand relative to your career goals by analyzing your skills inventory against target role requirements, ranking gaps by market demand and learning difficulty, and generating structured learning plans with resource recommendations and milestone checkpoints.

Supported Platforms & Integrations

Platform	Integration Type	Features
LinkedIn	Profile export (PDF/JSON)	Parse skills endorsements, experience, and certifications from profile data
Indeed	Job posting analysis	Analyze job descriptions to extract required and preferred skill sets
Coursera	Course catalog reference	Map identified gaps to specific courses with time estimates and ratings
Udemy	Course catalog reference	Recommend budget-friendly courses matched to specific skill gaps
GitHub	Repository analysis	Assess demonstrated technical skills from project languages, tools, and patterns
Glassdoor	Salary data reference	Correlate skill acquisition with potential salary impact for prioritization

When to Use

• Career transition planning -- switching from one role to another and need to identify what skills to develop
• Annual skill assessment -- yearly check on how your skills align with evolving market demands in your field
• Promotion preparation -- identifying what skills separate you from the next level in your current organization
• Job search strategy -- analyzing multiple job descriptions to find the most common requirements and prioritize accordingly
• Learning budget allocation -- deciding which courses, certifications, or books will have the highest career ROI
• Team skill mapping -- assessing a team's collective skills to identify coverage gaps and training needs

Alternatives to consider:

• For real-time labor market data and trending skills, LinkedIn Economic Graph or Burning Glass Technologies provide institutional-grade analytics
• For structured certification paths, platform-native learning paths on Coursera, Pluralsight, or LinkedIn Learning offer curated progressions
• For AI-powered career coaching with interview prep, tools like Jobscan or Careerflow specialize in job search optimization

Quick Start

Copy
# skill-gap-analyzer.yaml
skill:
  name: skill-gap-analyzer
  description: Identify skill gaps and create learning roadmaps
  config:
    current_role: "Junior Frontend Developer"
    target_role: "Senior Full-Stack Engineer"
    experience_years: 3
    time_horizon_months: 12
    weekly_learning_hours: 8
    priority_method: market_demand    # market_demand, salary_impact, ease_first
    storage_path: ~/.claude/skill-gap/
    output_format: markdown

Example interaction:

User: Analyze my skills gap for becoming a Senior Full-Stack Engineer.
      Current skills: React, JavaScript, CSS, basic Node.js, Git.

Assistant: Skill Gap Analysis: Junior Frontend --> Senior Full-Stack

  STRONG (market-ready):
  [====] React (high demand, you have production experience)
  [====] JavaScript/TypeScript (core, strong foundation)
  [====] Git (essential, well-covered)

  GAPS (prioritized by market demand):
  [!!!!] TypeScript -- 92% of senior full-stack roles require it
         Learning time: 4-6 weeks | Difficulty: moderate
  [!!!!] SQL/PostgreSQL -- 85% require database proficiency
         Learning time: 6-8 weeks | Difficulty: moderate
  [!!! ] System Design -- 78% of senior roles assess this
         Learning time: 8-12 weeks | Difficulty: high
  [!!  ] Docker/Containers -- 71% mention containerization
         Learning time: 3-4 weeks | Difficulty: moderate
  [!!  ] CI/CD Pipelines -- 65% require deployment automation
         Learning time: 2-3 weeks | Difficulty: low

  12-month roadmap generated with monthly milestones.

Advanced Configuration

Platform-specific setup for job description analysis:

Copy
job_analysis:
  sources:
    - platform: indeed
      search_query: "Senior Full-Stack Engineer"
      location: "Remote"
      min_salary: 120000
      sample_size: 20              # analyze top 20 postings
    - platform: linkedin
      search_query: "Senior Full Stack Developer"
      experience_level: senior
  extraction:
    required_skills: true
    preferred_skills: true
    tools_and_platforms: true
    soft_skills: false             # exclude soft skills from gap analysis

Full parameter reference:

Parameter	Type	Default	Description
current_role	string	required	Your current job title or role
target_role	string	required	The role you are aiming for
experience_years	number	0	Years of professional experience
current_skills	array	[]	List of your current skills with self-assessed proficiency
time_horizon_months	number	12	Timeline for closing skill gaps
weekly_learning_hours	number	5	Hours available per week for learning
priority_method	string	market_demand	Ranking: market_demand, salary_impact, ease_first, custom
include_certifications	boolean	true	Recommend relevant certifications
include_projects	boolean	true	Suggest portfolio projects to demonstrate skills
budget_monthly	number	0	Monthly budget for courses and resources (0 = free only)
learning_style	string	mixed	Preference: video, reading, hands_on, mixed
storage_path	string	~/.claude/skill-gap/	Local directory for analysis data
reassess_interval_weeks	number	4	Weeks between progress reassessments
industry_focus	string	tech	Industry: tech, finance, healthcare, general

Core Concepts

Concept	Description
Skill Inventory	Complete catalog of your current skills with self-assessed proficiency levels (novice, competent, proficient, expert)
Market Demand Score	Percentage of target role job postings that mention a specific skill, indicating how essential it is
Learning Velocity	Estimated time to reach competency in a skill based on your existing foundation, difficulty, and available hours
T-shaped Skills	Deep expertise in 2-3 core areas with broad familiarity across many -- the ideal profile for senior roles
Opportunity Cost	The career value of learning Skill A versus Skill B, factoring in demand, salary impact, and time investment

  Skill Gap Analysis Pipeline
  ============================

  [Your Skills Inventory] --> [Target Role Requirements]
           |                           |
           v                           v
  [Proficiency Assessment] --> [Demand Analysis (Job Posts)]
           |                           |
           v                           v
  [Gap Identification] ---------> [Priority Scoring]
           |                           |
           v                           v
  [Learning Time Estimation] --> [Roadmap Generation]
           |                           |
           v                           v
  [Resource Mapping] ----------> [Milestone Checkpoints]

Workflow Examples

Scenario 1: Career transition from marketing to data analytics

Input:  "I'm a marketing manager (5 years) wanting to transition to
         Data Analyst. Skills: Excel, Google Analytics, basic SQL,
         Tableau (beginner), marketing KPIs."
Output: Career Transition Analysis: Marketing Manager --> Data Analyst

        Transferable skills (valuable):
        - Analytical thinking from marketing KPIs (strong foundation)
        - Stakeholder communication and data storytelling
        - Google Analytics proficiency (directly relevant)
        - Basic SQL (needs deepening)

        Critical gaps:
        1. SQL (intermediate-advanced): 6-8 weeks
           Resource: Mode SQL Tutorial (free) + DataLemur practice
        2. Python/Pandas for data manipulation: 8-10 weeks
           Resource: DataCamp Python for Data Science track
        3. Statistical analysis fundamentals: 6-8 weeks
           Resource: Khan Academy Statistics + Coursera IBM DA cert
        4. Tableau (intermediate): 4-6 weeks
           Resource: Tableau Public projects + official training

        Timeline: 6-8 months with 10 hrs/week study
        Advantage: Your marketing domain knowledge is rare among
        data analysts and gives you an edge in marketing analytics roles.

Scenario 2: Promotion readiness assessment

Input:  "What skills do I need to go from mid-level to senior backend
         engineer? I know Python, Django, PostgreSQL, Redis, basic AWS."
Output: Promotion Gap: Mid-Level --> Senior Backend Engineer

        You have the foundation. Gaps are depth and breadth:

        Technical gaps:
        1. System design & architecture (most critical for senior)
           - Can you design a system handling 10K requests/second?
           - Resource: "Designing Data-Intensive Applications" book
        2. AWS depth (beyond basic): ECS, Lambda, CloudFormation
           - Resource: AWS Solutions Architect Associate cert
        3. Observability: logging, monitoring, alerting pipelines
           - Resource: Build a Grafana + Prometheus stack on a side project

        Non-technical gaps (equally important for senior roles):
        - Mentoring junior engineers
        - Technical decision documentation (ADRs)
        - Cross-team collaboration and stakeholder management

        Recommendation: Focus 60% on system design, 40% on AWS depth.

Scenario 3: Multi-job-posting analysis

Input:  "Analyze these 5 job descriptions I saved and tell me the
         most common requirements" [pastes 5 JDs for Staff Engineer]
Output: Cross-Posting Analysis: 5 Staff Engineer Descriptions

        Required in 5/5 postings (must-have):
        - 7+ years experience, distributed systems, mentoring
        Required in 4/5 postings (high priority):
        - Kubernetes, CI/CD, system design documentation
        Required in 3/5 postings (important):
        - Go or Rust, event-driven architecture, observability
        Mentioned in 2/5 (nice-to-have):
        - Machine learning familiarity, open source contributions

        Your coverage: 6 of 12 key skills present.
        Biggest gap: Distributed systems knowledge (mentioned in ALL 5).
        Fastest win: CI/CD pipelines (2-3 weeks to demonstrate).

Best Practices

1. Be brutally honest in self-assessment -- inflating your current skill levels produces an inaccurate gap analysis that wastes time on wrong priorities. Rate "competent" only if you can solve real problems independently, not just follow tutorials.

2. Analyze at least 10-15 job descriptions -- a single job posting is idiosyncratic to that company. Patterns emerge across 10+ postings and reveal true market demands versus one recruiter's wish list.

3. Prioritize T-shaped development -- go deep in 2-3 skills that define your specialty, then build breadth across adjacent areas. The market rewards depth in core areas far more than shallow knowledge of everything.

4. Build projects, not just take courses -- courses teach concepts, but projects demonstrate competence. For every skill gap identified, plan a small project that proves the skill. These also build your portfolio.

5. Reassess every 4-6 weeks -- the gap analysis is a living document. As you learn, skills shift from gap to foundation. Regular reassessment keeps the roadmap current and provides motivating evidence of progress.

Common Issues

Issue: The gap list is overwhelming and demoralizing Solution: Focus only on the top 3 gaps by priority score. Ignore everything else until those three are addressed. Trying to close 10 gaps simultaneously leads to superficial knowledge in all of them. Sequential depth beats parallel breadth.

Issue: Cannot determine my actual proficiency level in a skill Solution: Use the "can you build it?" test. Novice = completed tutorials. Competent = built a small project independently. Proficient = solved production problems with it. Expert = teach others and make architectural decisions with it. This practical framing is more accurate than self-rating on a 1-10 scale.

Issue: Target role requirements keep changing across job postings Solution: This is actually valuable signal. If requirements vary wildly, the role is not well-standardized in the market. Focus on the skills that appear in 70%+ of postings (the stable core) and treat unique requirements as company-specific preferences you can learn on the job.

Privacy & Data Handling

All skill assessments, career data, learning roadmaps, and job description analyses are stored locally in your storage_path directory (default: ~/.claude/skill-gap/). No resume data, career information, or skill assessments are transmitted to job platforms, learning platforms, or any external service. LinkedIn profile data is processed from your locally exported PDF or JSON file. Job descriptions you paste into the conversation are analyzed in-session and stored locally only if you choose to save the analysis. Your career aspirations, current skill levels, and identified gaps remain entirely private on your machine.