fact_checkScoring Methodology

How our AI scoring actually works

Every score on Interview Flash comes from a fixed, rule-based formula run against your own answer — not an opaque model deciding on its own. Here's the exact math, for all three scoring systems.

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Flash Practice score

Two components, weighted equally, capped so no single factor can carry the whole score.

Length — 50%

Your word count divided by 40, capped at 100% once you hit 40 words. Longer isn't automatically better past that point — it's a floor, not a target to maximize.

Keyword relevance — 50%

How many of that question's target keywords your answer actually uses, out of 3 — using all 3 maxes this component out.

Every score has a floor of 10 (never a discouraging 0) and a ceiling of 100. The AI Tip shown after each answer names exactly which keywords you did or didn't use.

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Mock Interview: five facets

Every answer is scored on five facets independently, then averaged across the session for your end-of-session report.

Answer Quality

40% length (word count / 60, capped) + 45% keyword relevance (matched keywords / 3, capped) + a flat 15% bonus if your answer includes an actual number.

Communication

Word count / 50, minus 12 percentage points for every filler word detected ("um," "uh," "you know," "basically," "actually," and similar) — floored at 0, so a heavily filler-laden answer can bottom out regardless of length.

Structure

60% how many structural markers you use (words like "first," "because," "as a result," "situation/task/action/result," capped at 3) + 40% sentence count (capped at 3) — rewards a shaped answer over a single run-on sentence.

Relevance

The same keyword-match ratio used inside Answer Quality, reported on its own so you can see keyword coverage separately from everything else.

Confidence — an honest caveat

Right now, Confidence is the Answer Quality score rescaled to a 0-10 display, not an independently measured voice or tone signal. We're saying that plainly here rather than implying it's something it isn't — a real voice-based confidence measure is on our roadmap, not shipped yet.

Communication analysis (speaking pace in words-per-minute and filler-word count) is calculated the same way from your actual transcript and timing — see a real worked example.

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Resume ATS score

Six weighted components, each capped independently — this mirrors the kind of keyword and structure parsing real applicant-tracking software runs before a human ever opens your resume.

Quantified bullet points — 25%

What share of your experience bullets include an actual number, percentage, or timeframe.

Summary length — 15%

Word count out of a 40-word target.

Skills listed — 15%

Count out of a 6-skill target — this is also what powers your AI job-match score.

Experience entries — 15%

Count out of a 2-role target.

Bullet count — 15%

Total bullets across all roles, out of a 4-bullet target.

Action-verb bullets — 15%

What share of your bullets open with a strong verb ("Led," "Architected," "Reduced," and similar) instead of a passive phrase.

The Resume Builder shows you which of these six is dragging your score down, in order, rather than just a single number.

Frequently asked questions

Is Interview Flash's scoring AI a black box?

No. Every score is a rule-based formula over your actual answer — word count, keyword matches, filler words, structure markers, and whether you included a number — combined with fixed weights. There's no hidden model deciding your score.

What is the Confidence score in Mock Interview actually measuring?

Today, Confidence is the same underlying Answer Quality signal shown on a 0-10 scale rather than a separately measured voice or tone signal. We're stating this plainly rather than implying it's independently measured.

Can a short but well-written answer score well?

Yes, up to a point — length is only part of each formula, capped rather than unlimited, and keyword relevance and (for Mock Interview) a quantified result matter just as much. But answers under the target length lose points on the length component regardless of quality.

See it score a real answer

Answer one question and watch exactly which of these components moved your score.

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