What it does
Build a Structured Interview Kit is a free AI skill that turns a job description into structured interview questions for one stage: 3–5 criteria, a core question with probes for each, a 1–5 rating scale with anchors, timings and a scorecard. It's for recruiters and hiring managers, and works in Claude, ChatGPT, Microsoft Copilot and other AI Assistants.
A job description, hiring brief or agreed criteria
The interview stage and its length, for example a 45-minute hiring manager interview
Optional: the panel, a rating scale you already use, your adjustment process
3–5 criteria for this stage, each named as something you can observe
One behavioural or situational core question per criterion, with 2–3 probes
A 1–5 rating scale with anchors for each criterion
Timings that add up to the interview length, plus opening and closing scripts
A scorecard, questions not to ask, and how to handle adjustment requests
How it helps
It builds the questions, rating anchors and scorecard together for one interview stage. If you have agreed criteria it uses them as given. If not, it proposes criteria from the must-haves, marked for your team to confirm.
Anchored rating scales
Every level from 1 to 5 describes what the answer sounds like for this role, so a "4" means the same to every interviewer. Anchors describe evidence, not personality.
The right question for the candidate's experience
Most questions ask for a real past example ("Tell me about a time…"). Where the candidate may lack direct experience, such as a first people-manager role, it asks what they would do in a real situation from the job. Probes dig for their own actions and results, not the team's.
Honest about what an interview can't show
If a must-have can't be tested well by talking, such as hands-on use of a tool, it suggests a short work sample with its own anchors instead.
Why we think it's useful
Need an interview guide for the hiring manager round, 45 mins, Shift Team Lead at Fernhill Foods (warehouse, 12 people on a night shift). JD says: run the shift to plan, keep people safe, coach new starters, deal with problems when things go wrong (late trucks, no-shows), good with WMS, forklift licence nice to have. First line manager role is fine. Recruiter screen already checked licence and shift availability. Interviewer is Tomas (ops manager). Want it fair, last time every interviewer asked different stuff.
Fictional company, role, candidate and people.
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Which AI do you use?
Closing the predictive-validity loop requires structured pre-hire data on every requisition. Assessment scores. Behavioral profiles. Hard-skills signals including AI fluency. Without that dataset, you cannot correlate pre-hire signals with post-hire QoH. You cannot tune the next cohort sharper than the last. The hiring system stays static. The score drifts.
Bryq builds the pre-hire dataset that makes the loop possible.
Claude
ChatGPT
Microsoft Copilot
Something else (Gemini, Mistral and others)
Better with Bryq
Already use Bryq? Add your assessment results.
Link your Bryq account to your AI assistant, and five skills can include your candidates' Bryq results. For example, your debrief shows them next to the interview notes, and your follow-up questions focus on where the two differ. The link only reads data; it never changes anything in Bryq. Results you bring into a chat are shared with your AI provider, like anything else you paste in. Every skill works fully without it.
FAQ
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