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.
Editorial reviewProduct claims were checked against the current experience. Technical references use primary documentation where the guide depends on platform or framework behavior. Found an issue? Send a correction.
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