Active and Forced HTTPS
Checks that the website loads over HTTPS, redirects from HTTP and does not keep insecure versions active.
The modular AISEO checks let you verify specific pieces of your infrastructure. The perfect complement to understand specific failures or prepare your site before a full audit.
These checks function as independent sensors. You can use them to confirm if your robots.txt file is blocking routes, if your HTTPS is correctly forced or if your content is accessible without depending on JavaScript.
However, to understand how each signal affects ranking, AI extraction and CertiScore, you need the full context of the AISEO audit.
Browse the 30 technical checks organized by their function within the AISEO validation ecosystem.
Checks that the website loads over HTTPS, redirects from HTTP and does not keep insecure versions active.
An incorrect HTTP code prevents indexing and insufficient internal links hinder crawling. This check evaluates both aspects in a single pass.
The robots.txt file guides crawlers on which areas they can crawl. A badly written rule can block critical sections or even leave a full website out of crawling.
Avoids contradictions between HTTP headers and meta tags that confuse search engines, crawlers and AI systems.
Checks that an HTTPS page does not load images, scripts, styles or internal resources through insecure HTTP.
Checks that nonexistent URLs return a real 404 status and not an apparently valid page with error content.
Provides a reliable list of URLs. If it contains errors, bots lose trust in the domain signal.
Avoids duplicates and consolidates signals on the preferred URL.
They are the first context vector for search engines and AI models.
Defines the main topic. Multiple H1 tags break semantic hierarchy.
If the content depends on JavaScript, many bots will not see it.
Prevents character errors that damage semantic extraction.
Evaluate whether the page loads smoothly, stably, and efficiently before delving into advanced user experience metrics.
Ensures important images have useful alternative text without decorative noise.
HSTS, X-Frame and other headers improve the technical reputation and security of the domain.
Clarifies the position of the URL within the site architecture for users, search engines and AI systems.
Even if your page is indexed, anti-snippet directives exclude it from Google rich results and generative AI citations. In the era of AI-assisted search, not being snippet-eligible means being invisible.
Checks that H1, H2, H3 and following levels create a coherent reading structure for users, search engines and AI systems.
Checks whether the URL communicates meaning before the page loads and avoids unnecessary technical noise.
Prevents language confusion and helps users, search engines and AI systems reach the correct version.
Check that the page has a proper mobile base and that the mobile version retains the essential desktop content.
Checks whether image HTML helps performance, stability and content priority instead of slowing the page down.
Checks whether important pages are close enough to the home page and not buried inside a deep architecture.
Checks whether redirects are direct, intentional and technically clean.
Evaluates LCP, INP and CLS as signals of real performance and usability.
Helps search engines and AI systems understand who owns, publishes or represents the website.
Checks whether text density, sentence length and clarity support better reading and extraction.
Evaluates whether the structure helps RAG systems retrieve useful fragments without losing context.
Checks whether users, search engines and AI systems can understand who is behind the content and why it deserves trust.
Detects whether the page contributes real value or only fills space with decorative, generic or redundant text.
Modular checks allow each professional to focus on the technical area they are responsible for solving.
Verify DOM cleanliness, content exposed without JS, HTTPS, redirects and security headers during production deployment.
Use crawling, canonical, robots, sitemap and metadata checks to detect specific incidents without launching a full audit.
Evaluate headings, readability, detectable usefulness and chunkable structure so that content is more interpretable by search engines and AI systems.
We clarify how to use these modules inside and outside the system.