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interview-evaluation

Synthesize multi-stage interview scores into legally defensible hiring recommendations with bias detection.

Updated Aug 27, 2026
Search Tags:#evaluation#interview#recruitment#bias detection#hiring#candidate lifecycle
One-click install
npx skills add https://github.com/diegouis/provectus-marketplace --skill interview-evaluation
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: interview-evaluation
Source: https://github.com/diegouis/provectus-marketplace/tree/main/plugins/proagent-hr/skills/interview-evaluation
Command: npx skills add https://github.com/diegouis/provectus-marketplace --skill interview-evaluation

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill automates the complex and often biased process of evaluating candidates throughout the hiring lifecycle, ensuring fair and data-driven hiring decisions.

Core Features & Use Cases

  • Prescreening: Design questionnaires and score responses, identifying gaps and inconsistencies.
  • Bias Detection: Scans HR and technical interviews for common biases, flagging them for review.
  • Multi-Stage Synthesis: Consolidates scores and feedback from all stages into a final, legally defensible recommendation.
  • Use Case: After conducting HR and technical interviews, use this Skill to synthesize all feedback, detect any potential interviewer bias, and generate a final hire/reject recommendation with clear rationale.

Quick Start

Use the interview-evaluation skill to synthesize all stage scorecards for candidate #001 and generate a final recommendation.

Frequently Asked Questions about interview-evaluation

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I synthesize interview feedback into a final hiring recommendation?▼

To synthesize interview feedback into a final hiring recommendation, consolidate multi-stage scorecards from HR and technical interviews to generate a legally defensible decision with clear rationale.

How does bias detection work during candidate evaluation?▼

Bias detection works by scanning HR and technical interview feedback for common biases, flagging them for review to ensure fair and data-driven candidate evaluation throughout the hiring lifecycle.

What is the best way to design prescreening questionnaires and score candidate responses?▼

Designing prescreening questionnaires and scoring responses is best handled by automating questionnaire creation, evaluating answers to identify gaps and inconsistencies, and applying consistent criteria across candidates.

Can I use this to manage the end-to-end candidate lifecycle for technical hiring?▼

Yes, you can manage the end-to-end candidate lifecycle for technical hiring by processing prescreening questionnaires, analyzing technical interviews, and synthesizing multi-stage data into final recommendations.

Why does my candidate evaluation process lack legally defensible hiring recommendations?▼

Your candidate evaluation process lacks legally defensible recommendations if it fails to synthesize multi-stage data, apply consistent criteria, detect interviewer bias, and flag process deficiencies across scorecards.

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