CV Shortlist Scorer

The problem

Manual resume screening is slow, prone to cognitive fatigue, and often introduces unconscious bias. Reviewing dozens of CVs against a rubric leads to inconsistent grading where early candidates face different standards than later ones.

What it does

• Identifies and flags missing mandatory qualifications or disqualifying factors.
• Extracts specific evidence strings from resumes to justify every criterion score.
• Calculates weighted totals based on custom must-have and nice-to-have priorities.
• Reduces bias by isolating qualifications from demographic data during the evaluation pass.
• Generates a structured comparison table ready for spreadsheets or ATS integration.

Why this beats prompting it yourself

Simple prompts often hallucinate missing skills or give "employer brand" preference to candidates from famous companies. This skill enforces a structured evidence-first protocol that requires a specific quote for every point awarded, ensuring the ranking is auditable and consistent across hundreds of files.

Use cases

• Screening a high volume of applicants for a specific technical role.
• Auditing an existing shortlist to ensure no qualified candidates were missed.
• Standardizing evaluations across a distributed hiring team using a shared rubric.

Known limitations

It scores based on stated claims only and cannot verify the truth of resume content. It does not replace formal legal compliance reviews for local hiring regulations.