A scorecard should help reviewers make their reasoning explicit. It should not convert a complex interview into false precision or replace the responsibility to review context.
Choose role-aligned signals
- Reasoning and clarification
- Communication and collaboration
- Frontend technical judgment
- Implementation quality
- Verification and failure handling
- System design or framework depth only when required by the role
Anchor the ratings
- Define what observable evidence supports each level.
- Use the same scale and interpretation across interviewers.
- Include a not-enough-evidence state.
- Avoid averaging unrelated signals into an unexplained number.
Capture evidence, not impressions
- Link a rating to an answer, code change, check, or architecture decision.
- Separate direct observation from inference.
- Record relevant counter-evidence.
- Keep protected characteristics and unrelated personal information out of evaluation.
Use the scorecard responsibly
- Review job relevance before the interview.
- Give candidates comparable opportunities to demonstrate the signal.
- Require human review of AI-organized evidence.
- Document overrides and uncertainty.
- Evaluate the process over time for consistency and adverse outcomes.
Turn the guide into a retry
Choose one section, practice it under interview conditions, review the evidence, and repeat the same skill with a new prompt. Improvement becomes reliable when it survives a different context.
Start a mock interview