Run Fair Hiring Evaluations End to End

Runs standardized candidate evaluations across your entire hiring pipeline, removing unconscious bias and fatigue from resume screening, interview preparation, and comparison. It applies identical rubrics to every candidate regardless of when their application arrives, so the 50th resume gets the same focused attention as the first.

Once configured with your organization's rubrics and role levels, the framework processes candidates through five sequential stages: 1. Set up role levels, rubrics, and thresholds in your organization folder. 2. Drop resumes into role-based subfolders, then run the evaluation workflow. Agents score all resumes against your rubric, invoke regional context advisors for international candidates, and generate interview prep materials for strong candidates. 3. Conduct interviews using the framework's structured templates, then run the assessment workflow to score responses objectively. 4. Compare finalists side-by-side to identify key differentiators and generate hiring recommendations. Output: scored candidates with consistent evaluation folders, interview assessments, and batch reports ready for decision-making.

Every candidate evaluated on the same rubric, with consistent scoring and zero bias from resume formatting, personal details, or reviewer fatigue.

Requires Claude Code CLI or VS Code with GitHub Copilot. The framework uses convention over configuration: agents auto-load all .md files from your organization folder, so no separate config registration is needed. Regional context is optional and disabled by default; enable in config.yaml if you evaluate international candidates.

Setup requires customizing rubrics and role levels for your organization first. The framework works best when organizations enforce consistent file naming and folder structure. Interview scoring requires detailed notes or transcripts. Verbal-only feedback produces lower-confidence assessments.