# Beyond Checks: GitHub's Alt Text AI Aims for Real Accessibility _GitHub's new accessibility scanner plugin uses AI to ensure alt text is truly descriptive, not just present._ **Published:** 2026-08-24 **Source:** https://www.startuphub.ai/ai-news/artificial-intelligence/2026/beyond-checks-github-s-alt-text-ai-aims-for-real-accessibility --- Automated checks can confirm that alt text exists on images, but they often fail to determine if that text is actually useful. The [GitHub Blog](https://github.blog/engineering/user-experience/your-alt-text-passes-automated-checks-that-doesnt-mean-its-any-good/) recently detailed how the company developed a plugin for its Accessibility Scanner to address this gap, aiming for genuine web accessibility. Simple Alt Text ChecksDriverautomated tools verify alt text presence but not its descriptive qualityFrom the article 9+ mentionsThis allows for a more nuanced evaluation, moving beyond simple string checks to assess descriptive adequacy.problem addressed byAI for ContextCoreGitHub developed an AI plugin to understand image context for better descriptionsFrom the article 2 mentionsDeterministic rules are limited because they cannot understand the image's context.enablesDescriptive Alt TextEffectAI ensures alt text is truly useful and accurately describes image contentFrom the article 8 mentionsAutomated checks can confirm that alt text exists on images, but they often fail to determine if that text is actually useful.achievesReal Web AccessibilityOutcomeaiming for genuine accessibility beyond just checking for alt text existenceFrom the article 2 mentionsThe GitHub Blog recently detailed how the company developed a plugin for its Accessibility Scanner to address this gap, aiming for genuine web accessibility.Growing ConcernContextweb accessibility is a significant and increasing focus for developers and usersFrom the articleWeb accessibility is a growing concern, with recent reports indicating that a significant percentage of images on popular websites either lack alt text or provide descriptions that are vague or redundant.highlightsSimple Alt Text ChecksDriverautomated tools verify alt text presence but not its descriptive qualityFrom the article 9+ mentionsThis allows for a more nuanced evaluation, moving beyond simple string checks to assess descriptive adequacy.leads toVague/Redundant Alt TextDrivermany images on popular websites have alt text that is unhelpful or genericFrom the article 8 mentionsWeb accessibility is a growing concern, with recent reports indicating that a significant percentage of images on popular websites either lack alt text or provide descriptions that are vague or redundant.drives need forAI for ContextCoreGitHub developed an AI plugin to understand image context for better descriptionsFrom the article 2 mentionsDeterministic rules are limited because they cannot understand the image's context.implemented asAccessibility Scanner PluginCorethe new AI-powered plugin integrates with GitHub's existing accessibility toolsFrom the articleThe GitHub Blog recently detailed how the company developed a plugin for its Accessibility Scanner to address this gap, aiming for genuine web accessibility.generatesDescriptive Alt TextEffectAI ensures alt text is truly useful and accurately describes image contentFrom the article 8 mentionsAutomated checks can confirm that alt text exists on images, but they often fail to determine if that text is actually useful.achievesReal Web AccessibilityOutcomeaiming for genuine accessibility beyond just checking for alt text existenceFrom the article 2 mentionsThe GitHub Blog recently detailed how the company developed a plugin for its Accessibility Scanner to address this gap, aiming for genuine web accessibility. Web accessibility is a growing concern, with recent reports indicating that a significant percentage of images on popular websites either lack alt text or provide descriptions that are vague or redundant. While machines can easily flag missing alt text, judging the quality of provided text is far more complex. ## The Limits of Simple Checks Many current automated tools verify the presence of an accessible name for an image but don't evaluate its descriptive quality. This is a deliberate design choice: overly strict rules can lead to false positives, prompting developers to disable the tools altogether. For instance, an alt attribute like "IMG_2847.png" or "image" passes automated checks but offers no real information to a visually impaired user. GitHub's approach distinguishes between what can be objectively proven and what requires interpretation. They established five deterministic rules that don't require AI. These rules flag absent or whitespace-only alt text, generic filenames, placeholder text like "TODO", single generic words such as "image" or "logo", and repeated alt text across adjacent images. ## Layout Matters for Repetition Identifying repeated alt text presented a unique challenge. Initially, the system flagged identical alt text on icons even if they were physically separated on the page. The solution involved analyzing page layout, specifically the proximity of images, rather than just their order in the markup. This ensures that only truly redundant descriptions within a visual grouping are flagged. The system uses Playwright for image identification, excluding elements with empty alt attributes (alt=""), as these are intentionally used for decorative images. The quality checker prioritizes avoiding false positives, opting for conservative rules that developers are more likely to keep enabled. ## AI for Contextual Understanding Deterministic rules are limited because they cannot understand the image's context. Whether "a smiling person" is an adequate description depends heavily on surrounding content. To address this, GitHub's plugin includes an opt-in AI-powered quality check. This feature extracts contextual information, including the nearest heading, page title, captions, and nearby prose. It also identifies if an image is part of a link, which significantly changes the purpose of the alt text, it should then describe the link destination, not just the image. The alt text, image content, and page context are then fed to a vision model via GitHub Models. This allows for a more nuanced evaluation, moving beyond simple string checks to assess descriptive adequacy. StartupHub.ai data shows that developer tools focused on accessibility have a low StartupHub score of 2/100, indicating a significant market opportunity for tools that genuinely improve usability. ## Why This Matters This development highlights a critical evolution in AI's role in software development. Beyond code generation, AI is now being applied to enhance crucial but often overlooked aspects like accessibility. By moving beyond basic compliance checks, GitHub is pushing the industry towards a more inclusive web. For developers, this means tools are becoming smarter, offering deeper insights than ever before. For businesses, it translates to more accessible products and a better user experience for a wider audience. The challenge remains in balancing AI's interpretive power with the need for deterministic, reliable checks that developers will trust and use. --- Original analysis from [startuphub.ai](https://www.startuphub.ai), the #1 AI startup directory. © StartupHub.ai. 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