What problem does it solve? Software often ships with invisible exclusion: rigid Western naming forms, exclusionary gender dropdowns, culturally conflicting color choices, and stereotyped imagery that alienate global users. This Skill detects those blind spots in product requirements, UI components, copy, and image-generation prompts before they reach production. ## Core Features & Use Cases - Invisible Exclusion Audits: Reviews workflows, form fields, and UI components for culturally specific assumptions, producing severity-rated findings with copy-pasteable fixes. - Global-First Localization Guidance: Evaluates color semiotics, iconography, date/time formats, and right-to-left layout support so internationalization is architectural rather than retrofitted. - Anti-Bias Prompt Engineering: Builds negative-prompt libraries that forbid harmful tropes and stereotypes in AI-generated imagery and marketing content. - Use Case: Before launching a finance app in APAC markets, run an audit that flags a red error-state color scheme (red signals rising stocks in China) and a First/Last name form that fails for users with multiple surnames, then receive corrected validation logic. ## Quick Start Audit this signup form and onboarding email sequence for cultural exclusion and suggest globally inclusive alternatives.
