AI Accessibility Checker Automates WCAG Audits with OpenAI Integration
Kiran Kadam has released the AI Accessibility Checker, a Python-based command-line tool that uses OpenAI’s API to identify and suggest fixes for accessibility issues in frontend code. Supporting WCAG 2.0, 2.1, and 2.2 across A to AAA levels, the tool flags violations like missing alt text, low contrast, keyboard traps, ARIA misuse, and improper semantic markup.
Designed for both developers and designers, the tool provides AI-generated, line-specific recommendations to help ensure websites meet accessibility standards before production. It can output results in table, list, or PDF format and skips non-relevant directories such as node_modules and .git. A checker.config.json file enables customization of file types, scan targets, and the OpenAI model used.
Beyond standalone use, the checker supports GitHub Actions for CI workflows. Developers can set their OpenAI API key via environment variables or secrets, allowing automated audits during push and pull requests. A prominent data privacy notice warns users not to analyze proprietary code unless their organization permits sharing content with third-party APIs.
The project is maintained under QED42 and is open source under the MIT license. Installation and usage details are documented in the GitHub repository, including a demo video and configuration guidance.
Learn more about the module: GitHub – AI Accessibility Checker
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