When you upload your resume and paste a job description into PassTheBot, you get an ATS score between 0 and 100. Here's exactly how that number is calculated and what each part means.
The Scoring Components
Our ATS engine evaluates your resume across seven weighted categories. The weights adjust based on the detected role — a backend engineer's resume is scored differently than a product manager's.
1. Keyword Match (22%)
This measures how many of the job description's keywords appear in your resume.
What it checks: - Required skills listed in the JD - Preferred skills listed in the JD - Tools, frameworks, and technologies mentioned - Experience-level keywords ("5+ years," "senior")
How to improve: - Read the JD carefully and include exact keyword matches - Use both abbreviations and full names ("CI/CD" and "Continuous Integration") - Place keywords in experience bullets, not just in a skills list
2. Skills Overlap (18%)
This measures how well your listed skills align with what the job requires.
What it checks: - Direct skill matches between your resume and the JD - Skills taxonomy normalization (recognizing that "k8s" means "Kubernetes") - Whether you have the core technologies the role demands
How to improve: - Include relevant skills even if they seem obvious - Use the same terminology the JD uses for each skill - If you have adjacent experience, frame it in terms of the required skill
3. Experience Relevance (15%)
This evaluates whether your work experience is relevant to the role.
What it checks: - Years of experience compared to JD requirements - Relevance of your past roles to the target position - Whether your bullet points demonstrate the skills the JD asks for
How to improve: - Start bullets with strong action verbs (built, led, optimized) - Include metrics and outcomes (not just responsibilities) - Tailor your experience descriptions to match the JD's priorities
4. Resume Quality (12%)
This evaluates the overall structure and professionalism of your resume.
What it checks: - Presence of standard sections (experience, education, skills, projects) - Use of action verbs vs. weak phrases ("responsible for," "helped with") - Soft skills evidence (leadership, communication, collaboration) - Portfolio links (GitHub, LinkedIn, personal website)
How to improve: - Include all standard resume sections - Start every bullet with a strong action verb - Link to your GitHub or portfolio if you have one - Remove weak phrases and replace with action-oriented language
5. Impact Score (10%)
This measures how many of your bullet points include quantifiable results.
What it checks: - Percentage of bullets with numbers (%, $, time, users, etc.) - Whether you demonstrate outcomes, not just activities
How to improve: - Add numbers to at least 50% of your bullets - Include user counts, revenue impact, performance metrics - Use approximations if you don't have exact numbers
6. Formatting (10%)
This checks whether your resume is structured in an ATS-parseable format.
What it checks: - Section completeness and standardization - Action verb usage - Quantifiable metrics - Portfolio/GitHub link presence
How to improve: - Use standard section headings ("Experience," not "My Journey") - Single-column layout (no tables or multi-column designs) - Include links to GitHub, LinkedIn, or portfolio
7. Project Relevance (13%)
This evaluates whether your projects use the technologies mentioned in the JD.
What it checks: - Technology overlap between your projects and the JD's requirements - Whether project descriptions demonstrate relevant skills
How to improve: - Include projects that use the JD's key technologies - Describe what you built and the technologies used - Show outcomes or impact from your projects
Role-Specific Weight Adjustments
Not all roles are scored the same way. A machine learning engineer's resume prioritizes skills and projects higher than formatting. A product manager's resume weights experience and impact more heavily.
Examples: - ML Engineer: Skills overlap (25%), keyword match (25%), projects (15%) - Product Manager: Experience relevance (25%), impact (15%), formatting (10%) - Backend Engineer: Keyword match (30%), skills overlap (20%), formatting (10%)
This means the same resume can score differently against different roles — which is exactly how it should work.
What the Score Means
| Score Range | Meaning | Action |
|---|---|---|
| 85-100 | Excellent match | Apply with confidence |
| 70-84 | Good match | Minor improvements possible |
| 50-69 | Moderate match | Optimize for this specific JD |
| Below 50 | Weak match | Significant revisions needed |
A score of 85+ means your resume closely matches the job description's keywords, skills, and requirements. It doesn't guarantee an interview — but it means your resume will pass the ATS filter and reach a human recruiter.
How AI Optimization Improves Your Score
When you click "Optimize," our AI:
- Analyzes the gap between your resume and the JD
- Identifies missing keywords and skills
- Rewrites bullet points to incorporate relevant terminology
- Adds quantifiable metrics where appropriate
- Reorders skills by relevance to the JD
The optimization preserves your original experience and facts — it doesn't fabricate companies, dates, or qualifications. The output is always yours to review and edit before use.
Ready to see your score? Upload your resume and paste a job description to get an instant ATS analysis with specific improvement suggestions.