Interview and test candidates for a support agent role
Interview questions, a realistic written ticket test, and a scoring rubric to hire strong support agents fairly.
The prompt
Help me design the interview process for a customer support agent role.
Role details: [channels, tier, product complexity, schedule]
What great agents on my team do well: [e.g. write clearly, stay calm, troubleshoot methodically]
Must-have skills: [LIST]
Nice-to-have skills: [LIST]
Interview stages and time available: [e.g. 30-min screen + 60-min interview]
Create:
1. A scorecard of 5-6 competencies (e.g. written communication, empathy, problem solving, ownership, learning speed, tool fluency), each with what weak, good, and strong look like.
2. 8 behavioral questions tied to the competencies, each with a follow-up probe and what a strong answer includes.
3. A written work sample: 3 realistic customer tickets (one confused, one angry, one technical), with instructions and a time limit. Use a fictional product so prior knowledge doesn't matter.
4. A rubric for the work sample: accuracy, clarity, tone, completeness, and whether they asked for missing information.
5. A short troubleshooting exercise to see how they think aloud.
6. Questions candidates should be invited to ask us, and honest points about the job (shift work, emotional load).
Fairness: use the same questions and rubric for every candidate, score independently before discussing, and avoid questions about age, family, health, or other protected characteristics. Check local employment law and your HR team's guidance.
Highlighted [brackets] are blanks to replace with your own details.
Fill in the blanks and use this promptMore HR & Hiring prompts
What to fill in
- channels, tier, product complexity, schedule
- e.g. write clearly, stay calm, troubleshoot methodically
- LIST
- e.g. 30-min screen + 60-min interview
How this prompt is built
This prompt follows the Few-Shot structure (Few-shot prompting). A few-shot prompt includes one or more worked examples of the input and the output you want, so the model can copy the pattern instead of guessing it.
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