A score is only worth reading if you know what it's built on. Ours comes from two things the evidence keeps pointing at: whether your resume carries real evidence, and whether it lines up with the specific role you're going for. Here's the reasoning, with the sources.
The first pass is short — but not as short as you've been told
You've probably heard recruiters spend six seconds on a resume. That number comes from a 2012 eye-tracking study conducted during a recession-driven application glut; the same firm revised it to about seven seconds in 2018 and partly attributed the change to market conditions.
Better-controlled recent work puts it higher. Jan Tegze timed 114 recruiters who didn't know they were being timed and found active review running roughly 17 to 46 seconds. A 2024 survey of 418 US hiring professionals found 47% spend between thirty seconds and a minute, 81% spend under a minute in total, and only 1% spend under ten seconds.
So: tens of seconds, not six. Long enough to read a well-structured resume. Not long enough to decode a badly structured one. That's the window everything else here is designed around.
Clear structure is a human finding first
The most useful part of that eye-tracking work isn't the number, it's what it says about layout. The resumes that performed well had simple layouts, clear section and job headings, bold titles, and bulleted accomplishments. The ones that performed badly were cluttered, short on white space, spread across multiple columns, and written in long sentences with headings missing.
That's a finding about human readers, not about software. It happens to point the same direction as parseability — which is a large part of why our templates are structured the way they are, and why our ATS-strict designs are single-column with standard headings.
Employers want evidence, not adjectives
NACE's employer research on entry-level resumes is direct about this: employers are looking for evidence of teamwork, problem-solving and communication, and they say candidates should share examples and situations where they used a skill to solve a problem. Written communication, initiative, work ethic and technical skills each matter to at least 70% of responding employers.
Notice what that isn't. It isn't a list of adjectives about yourself, and it isn't a skills line. It's a specific thing you did with a result attached — evidence, not a claim. That's what the Bullet Quality part of your read is built around.
Matching the specific posting is a documented failure mode
The Hidden Workers study from Harvard Business School and Accenture surveyed more than 8,000 workers and 2,250 executives across the US, UK and Germany. 88% of employers agreed that qualified, high-skilled candidates are screened out because they don't match the exact criteria written into the job description. In the US alone the affected pool exceeds 27 million people.
The root cause they identify isn't candidate quality. It's postings listing more than the role needs, and systems configured to enforce every stated requirement.
That's a gap between a good resume and this posting's stated criteria — not a universal quality bar. It's exactly what the match half of your score measures, and it's why we ask for a target job rather than scoring you in the abstract.
Volume has made fit matter more than effort
LinkedIn reported roughly 11,000 applications submitted per minute, a 45% year-on-year surge, while postings fell about 10.6%. Greenhouse's 2025 research found 49% of US job seekers now apply to more roles just to get past automated filters, and 34% of hiring managers spend up to half their week filtering junk applications.
More applications isn't a strategy anymore; it's the problem everyone is drowning in. A scoring model that pushes you toward one better-matched application rather than twenty scattered ones is responding to that.
Automated screeners disagree with each other
A December 2025 benchmark ran nine models over 1,000 job postings against 1,000 candidate profiles and found exact agreement between models only 20.7% of the time on identical pairs. In the same work, human annotators judging suitability agreed at close to chance levels.
This is the single most important thing to understand about resume scoring, ours included: there is no consistent oracle to satisfy. Chasing any one screener's preferences is chasing noise.
Our response is to score the substance — is this well-evidenced, is it clearly structured, does it match what this posting asked for — rather than to model a particular system's quirks. It's also why your score holds steady when your resume hasn't changed. See why your score didn't move.
Skills are becoming the currency
The Burning Glass Institute reports roughly 45% of postings on major platforms have dropped degree requirements relative to 2019, and LinkedIn argues skills-first hiring can expand a talent pool many times over.
Worth the honesty: adoption is contested. One widely circulated analysis argues that despite most companies claiming skills-based hiring, only about one hire in 700 is actually affected, and that most postings still list a degree. Treat it as a direction of travel, not a settled change — but a direction that rewards resumes evidencing what you can do, not just where you were.
What we do with all this
- Structure is measured because a short first pass punishes documents that can't be navigated.
- Bullets are measured for evidence because that's what employers say they're looking for.
- Parseability is measured because a resume that's read wrong is judged wrong.
- Match is measured against a specific posting because that's the documented screen-out.
- Scores hold steady because the alternative is noise.
What we don't publish
We don't publish the weights, the thresholds, or the formula. Two reasons, and neither is that it's proprietary magic.
A published formula becomes something to optimize against instead of a read on your document — and the edits that move a number hardest are usually the ones that make a resume worse for a human. And a score that can be reverse-engineered can be gamed by everyone, at which point it stops distinguishing anything.
What we will always tell you is what the score rewards, in plain language, which is what this article is. See also resume practices we build around and resume advice we won't give you.