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Builds or overhauls a structured hiring process to reduce bias and improve quality-of-hire, using scorecards, behavioral questions, and independent scoring.
npx claudepluginhub jeffreytse/grimoire --plugin grimoireHow this skill is triggered — by the user, by Claude, or both
Slash command
/grimoire:design-hiring-processThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
Create a structured, repeatable hiring process that predicts job performance and reduces bias.
Design interview processes that assess actual capability, reduce bias, and provide good candidate experience. Use when building hiring practices or expanding the team.
Generates structured interview scorecards with competencies, behavioral questions, and scoring guidance for any role to reduce hiring bias.
Build a structured engineering hiring rubric and technical interview scorecard for a specific role and level.
Share bugs, ideas, or general feedback.
Create a structured, repeatable hiring process that predicts job performance and reduces bias.
Adopted by: Google (Project Oxygen), Stripe, Airbnb, and organizations following Schmidt & Hunter's 80-year meta-analysis of hiring validity Impact: Structured interviews have 2× the predictive validity of unstructured ones (Schmidt & Hunter, 1998); Google's data-driven hiring reduced bad hires by 25% after removing brain-teasers and adding structured rubrics
Unstructured hiring defaults to affinity bias — interviewers hire people like themselves. A structured process defines what "good" looks like before meeting any candidate, forcing evaluation against a common standard.
Stripe's engineering hiring process assigns one interviewer exclusively to "cross-functional communication" — a competency not covered by technical rounds. This catches technically strong candidates who create coordination debt, a failure mode common in fast-scaling engineering orgs.