How we score
Every PassMyResume score comes from one published formula. There is no AI in the score: the same resume and the same job description always produce the same number, and you can check it by hand. The weights depend on the job's field, because a nursing or security role is screened differently from a software role.
score = keywords × K + credentials × C + formatting × F + alignment × A
Each part is 0 to 100; the result is rounded to a whole number. The weights K, C, F and A depend on the job field we detect from the posting (you can change it). We read the job title first, and the most specific match wins ("data engineer" beats "engineer"); when the title names no field, the skills in the posting decide. When a posting requires no certification, license, degree or clearance, the credentials weight moves to keywords.
| Job field | Keywords | Credentials | Formatting | Alignment |
|---|---|---|---|---|
| Software engineering | 60% | 5% | 20% | 15% |
| Data and analytics | 60% | 5% | 20% | 15% |
| IT and cloud operations | 60% | 5% | 20% | 15% |
| Cybersecurity | 40% | 30% | 15% | 15% |
| Business, finance and accounting | 45% | 20% | 20% | 15% |
| Marketing and sales | 50% | 10% | 20% | 20% |
| Product and project management | 50% | 10% | 20% | 20% |
| HR, people and operations | 50% | 10% | 20% | 20% |
| Healthcare and nursing | 40% | 30% | 15% | 15% |
| Education and teaching | 40% | 30% | 15% | 15% |
| Legal and compliance | 40% | 30% | 15% | 15% |
| Skilled trades and manufacturing | 40% | 30% | 15% | 15% |
1. Keyword coverage
We find the skills and keywords in the job description and check which ones your resume contains. Recruiters search an applicant tracking system by keyword, so this carries most of the weight.
- Skills come from a reviewed vocabulary of 2859 terms across software, data, security, IT, business and finance, plus skills that apply in every field, each with common variants (so "k8s" counts as Kubernetes and "CPA" as Certified Public Accountant).
- Weights reflect what recruiters filter on: tools, languages and frameworks count 3, methods, domain knowledge and most certifications 2, soft skills 1.
- Up to 10 other frequent words from the posting are added at weight 1, so the score reflects that specific job, not just a generic skill list.
- Coverage = weight of keywords you have ÷ weight of all keywords in the posting.
2. Formatting checks
Nine checks simulate how a parser reads your file. A pass counts 1, a warning 0.5, a failure 0; formatting is the average.
| Email detected | An email address the parser can extract |
| Phone detected | A phone number in a standard format |
| Contact info at top | Contact details in the first lines, not in a header image or footer |
| Standard sections found | Headings an ATS recognizes, such as Experience and Education |
| Skills section present | A labeled Skills section recruiters and parsers can find |
| Uses bullet points | Achievements as bullets the parser can split |
| Dates detected | Employment dates in a recognizable format |
| Healthy length | Enough content to rank, not so much it buries the match |
| Single-column friendly | No layout that scrambles reading order, such as tables or columns |
3. Content alignment
How closely the words across your whole resume track the words of the posting, measured as cosine similarity of word frequencies. It rewards describing your work in the job's language, beyond the keyword list.
4. Credentials and hard requirements
Before ranking anyone, recruiters filter on hard requirements: a license, a certification, a degree, a security clearance. We find the ones the posting states, note whether each is required or preferred, and check your resume for each. "CISSP or GCIH" counts as one requirement that either satisfies. The credentials part is the share of required ones you meet. Years of experience and work authorization are shown as checks but never scored, because a resume rarely settles them.
5. What moves your score
For every missing keyword, unmet credential and failed check, we recompute the score as if only that one thing changed, with the formula above, and rank the changes by the points they add. Because the score is deterministic, these are exact projections, not estimates.
Worked example
The sample resume and job on our scanner page, computed live by the same engine that scores your resume:
| Part | Value | Weight | Points |
|---|---|---|---|
| Keyword coverage | 35 | 65% | 22.75 |
| Formatting checks | 95 | 20% | 19.00 |
| Content alignment | 27 | 15% | 4.05 |
| Score (rounded) | 46 |
Its highest-impact change: add "GraphQL" where it truthfully describes your experience, which takes the score from 46 to 50. Making the top three changes takes it to 58.
What the score is not
It is an estimate of how well your resume answers a recruiter's keyword search and how cleanly it parses. It is not a connection to any employer's system, and no score guarantees an interview. A hard requirement the posting states (a license, a clearance, work authorization) matters more than any number.