How scoring works
After each interview, TalentSprout's AI evaluates the candidate and generates a scorecard. The overall score is out of 100 and is calculated from multiple evaluation dimensions that you can configure on the Evaluation tab.
Standard performance metrics
Every interview includes five built-in evaluation categories under the Default scores section:
Communication Skills — Clarity, articulation, and effectiveness in conveying ideas.
Domain Expertise — Knowledge and experience relevant to the role.
Problem Solving — Ability to analyze situations and propose solutions.
Cultural Fit — Alignment with company values and work style.
Professionalism — Demeanor, preparation, and overall conduct.
Each metric is scored out of 100. Click Show details to see the scoring criteria for each. These categories are always evaluated and cannot be removed.
Enabling language proficiency scoring
If the role requires strong language skills, you can add a language proficiency evaluation:
Open the interview and go to the Evaluation tab.
Toggle on Language proficiency.
The AI will assess the candidate across four sub-metrics: Comprehension, Fluency & Pace, Grammar & Structure, and Vocabulary & Expression.
This score appears as a separate section on the candidate scorecard. Click Show details to see the sub-metric breakdown.
Enabling resume evaluation scoring
If you collect resumes from candidates, you can include resume analysis in the overall score:
On the Evaluation tab, toggle on Resume evaluation.
The AI evaluates the candidate's resume across four sub-metrics: Experience Relevance, Skills Match, Education & Certifications, and Career Progression.
The resume score is blended with the interview score to produce the overall score.
Resume evaluation requires that resume upload is enabled on the Settings tab. If resume upload is disabled, the resume evaluation toggle will be disabled with a prompt to enable it in settings.
Adding custom evaluation criteria
Beyond the standard metrics, you can add your own evaluation criteria tailored to the role:
On the Evaluation tab, find the Custom scores section.
Click Add custom score.
Enter a Score name (required) — e.g., "Reliability," "Attention to Detail," or "Sales Acumen."
Enter Evaluation criteria (required) — describe what the AI should look for when scoring this criterion. You can also click Generate with AI to auto-generate evaluation criteria.
Click Add score.
You can add multiple custom scores. Each one is scored individually out of 100 and appears on the candidate scorecard alongside the standard metrics.
To edit a custom score, click the pencil icon next to it. To delete one, click the trash icon and confirm in the dialog.
How the overall score is calculated
The overall score out of 100 is a blend of:
Interview performance — Scores from the standard metrics and any custom criteria, based on the AI's evaluation of the conversation.
Resume evaluation (if enabled) — The AI's assessment of the candidate's resume.
When both are enabled, the overall score reflects a combination of how the candidate performed in the interview and how their resume aligns with the role. When resume evaluation is off, the score is based entirely on the interview.
Tips for configuring scoring
Enable resume evaluation for roles where experience and credentials matter as much as interview performance.
Add custom scores to evaluate role-specific skills that the standard metrics don't cover.
Use Generate with AI to quickly create evaluation criteria for custom scores.
Review a few scorecards after your first candidates complete interviews to ensure the scoring feels calibrated for your expectations.