LunaPromptsThe job description asks for Python, SQL, distributed systems, cloud infrastructure, and “strong problem-solving.” The actual first project is a small internal API. If you assess the entire wish list, you may build a test for a different job.
A generated draft helps the team start. A role-to-evidence review makes that draft useful. This guide shows how recruiters and engineering managers can do that review together without rebuilding every question from scratch.
LunaPrompts uses AI agents to turn a job description into a role-specific assessment draft. Recruiters and hiring managers can review the proposed questions, adjust the scope, and prepare a test without starting from an empty builder.
Turn a broad JD into a focused test
Recruiter + hiring managerIllustrative scenario01 / 03Identify the work
The role owns Python API changes and SQL queries. Distributed systems is a secondary requirement.
Take a backend opening whose first project involves maintaining an internal order API. Begin with three responsibilities: validate requests, read the right records, and handle failures clearly. These responsibilities suggest observable evidence more directly than a list of frameworks does.
A draft blueprint could contain an API validation repair, a SQL query over a small supplied dataset, and a follow-up about a failed dependency. For each task, write what the reviewer should be able to point to: a failing example that now passes, a query that returns the intended records, or a justified recovery choice.
Next, ask the engineering manager which requirements can be learned after joining. If a particular cloud service is only incidental, avoid making product-specific trivia the gate to a practical exercise. If SQL correctness is essential from the first week, give it explicit coverage.
Finally, pilot the draft. Record how long the environment takes to understand separately from the time spent solving the task. Have reviewers assess the same sample submission independently, then compare the evidence they used. A disagreement may reveal an unclear rubric or a genuinely important tradeoff. Resolve it before inviting the wider pool.
From role requirements to an editable draft
The agent workflow uses the job description as the starting context for assessment creation. The resulting draft gives the team something concrete to evaluate: the proposed skill coverage, question mix, and level of challenge.
The draft is meant to be edited. A job description can contain outdated requirements, broad wish lists, or tools the candidate could learn after joining. Human review is how you distinguish those items from the capabilities the role genuinely needs on day one.
A practical creation workflow
- Provide the job description. Include the responsibilities, experience level, and work the person will own.
- Review the proposed skills. Decide which requirements are essential and which are secondary.
- Inspect the assessment mix. Choose the relevant practical, coding, knowledge, design, or conversational formats.
- Calibrate the challenge. Review difficulty, expected duration, and the scoring approach against the role.
- Preview and finalize. Check the candidate experience and agree on what a strong submission should demonstrate.
This gives recruiters a useful draft and gives engineering reviewers a focused task: correct the assessment where it diverges from the work.
Make calibration a conversation about evidence
Useful review questions are specific. Does the task reveal the skill we care about? Could a qualified candidate complete it in the stated time? Is the scoring criterion observable? Are we testing framework trivia when the actual job requires debugging?
Those questions help the team improve the assessment before it reaches candidates. They also reduce the chance that different reviewers silently apply different standards later.
The benefit is a shorter path to a useful draft and a more focused review. Exact time savings depend on the role, the starting job description, and how much calibration the team needs.
A review framework your team can use
The following is an editorial checklist for this workflow. Adapt it to the role, the candidate journey, and your configured environment.
| Review area | What to establish |
|---|---|
| Responsibility | What the person will own |
| Task | A bounded piece of representative work |
| Evidence | What success or a gap looks like |
| Calibration | Timing, instructions, and reviewer agreement |
A generated assessment can inherit a confused job description. Before changing the questions, check whether the team agrees on the role.
Put the guide to work
Highlight three responsibilities in an open JD. For each, write one task and one observable review criterion. Remove any task that has no clear responsibility attached.
Download the editable worksheet to record the decisions and open questions with your team. The examples in this guide are illustrative, not customer results or validated selection rules. Product availability and setup depend on the workflow agreed for your account.
A focused checklist, a worked scenario, and questions to resolve together.
Frequently asked questions
Can we edit the assessment after it is generated?
Yes. The workflow is designed around reviewing and editing the draft before use, including the selected questions, difficulty, and intended assessment scope.
Does an AI-generated assessment remove the need for a hiring manager?
No. The hiring manager helps define the real work, the expected level, and the evidence needed to move someone forward. A generated draft makes that contribution easier to focus.
What if our job description is too broad?
Treat the draft as a starting point for narrowing the role. Agree on the essential skills and remove tasks that add candidate effort without improving the hiring decision.
Keep building your hiring workflow
- AI skills: The answer looks right. Can your candidate explain why?
- MCQ assessments: A good question has a reason. So does every wrong answer.
- FDE support: Your role is specific. Your assessment should be too.
Explore jd to assessment with LunaPrompts or browse all 19 hiring field guides.
