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Score interviews like a recruiter.
Gut feel is how bad hires happen. This scorecard runs the six dimensions we score on live searches, weighted the way we weight them, with a printable summary for your debrief.
- Six weighted dimensions
- Fraud red flags
- Print for the debrief
The method
Why these six, and why weighted.
This is the structure behind every STACK IT submission: technical fluency proven by plain-language explanation, ownership proven by project retrospectives, and fit read against the team, not the interviewer. Two reviewers see every score before a candidate reaches a client. The weights below reflect what actually predicts a hire that sticks.
Interview scorecard
Score the candidate.
Rate each dimension from 1 to 10 during or right after the interview. The weighted total and recommendation update as you go.
Can they explain their work in plain language? Ask them to teach a concept back. Depth shows in clarity, not jargon.
Walk through a real project. Probe their role, the tradeoffs, and how it ended. Owners talk specifics; passengers talk in "we".
Pose a problem from your world: a migration, a stakeholder conflict, a deadline pivot. Score how they reason, not whether they land your answer.
Clarity, organization, and pacing. Do not penalize accents; score whether meaning lands.
Adaptability, collaboration style, and client orientation. Likability is not fit; watch for the "similar to me" trap.
Does this role move them toward where they want to go? Misaligned hires interview well and resign early.
Red flags (from our AI fraud playbook; any one of these pauses a submission)
Nothing you type leaves this page. Scores live in your browser only.
Rather have us run the interviews?
Every candidate we submit has already been through this scorecard, on video, with a second reviewer. You interview finalists, not applicants.
That’s our STACK.