Not every project comes with documentation. Startups move fast, legacy products lose their original specs over time, and sometimes a team inherits a codebase with no record of what it was supposed to do in the first place.
If you have ever been asked to test something with no documentation to work from, you know how much guesswork that usually involves. There is a faster way, and it starts with nothing more than a URL.
The Problem With Undocumented Products
When documentation does not exist, QA teams typically fall back on one of two approaches. Either someone manually explores the product, clicking through every flow and writing down what they find, or testing happens reactively, with bugs discovered only after users report them.
Both approaches work, but both are slow, and both depend heavily on the tester’s familiarity with the product. A new QA hire facing an undocumented app is starting from zero.
How URL-Based Test Case Generation Works
Rather than requiring a spec, an AI tool can analyze a live product directly from its URL. The process generally works like this:
- You submit the URL of the page or application you want tested
- The AI crawls and analyzes the interface, identifying flows, forms, and interactive elements
- Based on what it finds, it generates documentation describing what the product appears to do
- From that generated documentation, it produces a full set of test cases covering the flows it identified
This means you can go from a completely undocumented product to a structured test suite without writing a single requirement first. Tshabok AI’s “No Documentation” path was built specifically for this scenario.
Where This Is Most Useful
URL-based generation is not just a workaround for missing docs. It is genuinely useful in several common situations:
- Inherited codebases. When a team takes over a product built by someone else, generating test cases from the live URL gives them a working map of what the product does before they touch a line of code.
- Competitive analysis. Submitting a competitor’s URL can help your team understand how a similar product is structured, useful when scoping your own feature set.
- Pre-launch sanity checks. Before a major release, running your own URL through the tool can catch flows your team forgot were even part of the product, especially in larger applications where institutional knowledge is scattered across multiple people.
- Regression baselines. If you are not sure what existing test coverage looks like, generating a baseline from the live URL gives you a starting point to compare against future versions.
What It Cannot Replace
Generated documentation from a URL describes what a product does, not necessarily why it does it that way, or what business rules sit behind the scenes.
A login form might look standard, but the AI cannot know that your business requires a specific password policy unless that policy is visible somewhere in the interface.
This is where a QA lead’s review still matters, layering business context on top of what the AI observed.
Getting Started
If you have a product with no documentation, or documentation so outdated it is no longer trustworthy, submitting the live URL is often faster and more accurate than trying to reconstruct specs from memory.
It also means your test cases reflect what the product actually does today, not what it was supposed to do at some earlier point in its history.
Submit a URL to Tshabok AI and see what a generated test suite looks like for a product you thought had no documentation at all.