Prompt library

AI Candidate Evaluation Prompts for Recruiters

Candidate evaluation prompts help recruiters summarize interviews, compare evidence, create scoring rubrics, and synthesize feedback for hiring decisions.

ATZ CRM links candidate evaluation prompts to scorecards, post-interview summaries, panel debriefs, reference evidence, and client feedback workflows.

Copy-ready prompts

Prompts built for real recruitment work

Use these evaluation prompts after interviews, assessments, or client feedback calls. They help recruiters turn scattered notes into evidence-based summaries that support clear next-step decisions.

1

Post-interview summary prompt

Use after recruiter or client interview.

Summarize these interview notes for [candidate] applying to [job title]. Include strengths, concerns, evidence by competency, open questions, and recommended next step. Notes: [paste notes].
2

Candidate comparison prompt

Use when shortlisting multiple candidates.

Compare these candidates against [job criteria]. Create a table with fit score, evidence, risks, compensation/availability notes, and recommendation. Candidates: [paste summaries].
3

Panel debrief prompt

Use after multi-interviewer feedback.

Synthesize panel feedback for [candidate]. Identify agreement, disagreement, evidence gaps, follow-up questions, and whether the candidate should advance, hold, or reject.

Prompt framework

What to include before asking AI

Candidate evaluation prompts need notes, scorecard data, role criteria, and decision context. The AI should distinguish evidence from opinion and surface what still needs to be verified.

Candidate evaluation context: Interview notes

Candidate evaluation context: Role criteria

Candidate evaluation context: Evidence

Candidate evaluation context: Score scale

Candidate evaluation context: Recommendation

Use cases

When to use these prompts

Candidate evaluation use case: Summarize interviews
Candidate evaluation use case: Compare candidates
Candidate evaluation use case: Run panel debriefs

Common mistakes

What to avoid

Candidate evaluation mistake to avoid: Scoring without evidence
Candidate evaluation mistake to avoid: Summarizing opinion as fact
Candidate evaluation mistake to avoid: No clear next action

FAQ

Questions recruiters ask about this prompt pack

What information should go into a candidate evaluation prompt?

Use interview notes, scorecard ratings, resume evidence, assessment results, client concerns, reference notes, and the decision format needed for the hiring team.

How do evaluation prompts help after panel interviews?

They consolidate feedback from multiple interviewers, separate evidence from opinion, show agreement or disagreement, and create a cleaner recommendation for the client.

What should recruiters check before sending an AI candidate evaluation?

Check that the summary is evidence-based, role-related, balanced, free from unsupported assumptions, and clear about next steps or remaining verification questions.