achecker.ca is a free web accessibility checker that runs an instant WCAG 2.2 audit on a page entered by URL. It produces an Accessibility Score and WCAG-based fixes, and it is presented as a way to support accessibility work tied to AODA, the Accessible Canada Act, ADA, and international compliance.
The checker scans both code and content. It reports a score from 0 to 100, highlights specific WCAG failures, and presents a prioritized list of issues so users can focus on what to fix first. The page identifies examples of problems it catches, including missing alternative text for images, missing form input labels, incorrect heading structure and missing page landmarks, insufficient color contrast, links or buttons without a clear purpose, and missing page titles. It also includes warnings in reports, not just errors, and lets users choose a WCAG compliance level of Level A, AA, or AAA, with Level AA recommended for most websites. The tool supports testing at desktop, tablet, and mobile viewport sizes.
The page describes automated testing as a first pass and says full conformance requires human review. It also notes areas that require manual testing, including keyboard accessibility journeys, real-world screen reader compatibility and usability, the clarity and intent of content and link text, and complex interactions such as dynamic menus or multi-step forms. The service can be used again after changes, allowing pages to be re-scanned and progress to be tracked over time.
It is delivered as a web-based accessibility checker. The page also describes it as a WCAG validator and says it is free.
achecker.ca is a Testing & QA project. It focuses on helping website owners identify and fix accessibility issues to comply with WCAG and legal standards. It is built as a consumer product for web developers and site owners. achecker.ca costs nothing to use. achecker.ca is available on the web.
achecker.ca first shipped in 2024. Key capabilities include accessibility score, WCAG audit, and screen reader checks.
Summary written by a language model from the project’s public pages.
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