There are many code generators that can create CRUD resources from a config file.
On paper, that sounds great.
In practice, the real question is not:
“Can it generate code?”
The real question is:
“Can I actually trust the generated project enough to use it?”
That is where many generators start to fall apart.
Generating a few entities, repositories, and controllers is the easy part. The harder part is making the generated result feel reliable, understandable, and usable in a real workflow.
After working on my own Spring Boot CRUD generator, I realized that usability does not come from generation alone. It comes from all the small things around the generation that reduce friction and increase trust.
Here are a few lessons that stand out.
1. Code generation is not enough
A generator can create a lot of files and still feel incomplete.
You can generate entities, services, controllers, mappers, tests, migrations, and configuration files, and the first impression may still be:
“Okay, but will this actually work in my project?”
That hesitation is normal.
Developers do not trust generated code just because it exists. They trust it when they can see that:
- the input format is clear
- the output is predictable
- the generated application can actually run
- the project will not break because of missing setup
- the API surface behaves the way they expect
A useful generator is not just a code emitter.
2. Validation matters more than people think
A spec-driven generator lives or dies by the quality of its validation.
If a spec file is invalid, users should know before generation.
If the spec is incomplete, they should know before generation.
If the target project setup is missing required dependencies, they should know before generation.
That is why dry-run validation is so valuable.
A dry run gives the user a chance to validate the spec and project setup without committing to a full generation step. It turns generation into a safer workflow:
- write or update the CRUD spec
- run validation
- fix issues early
- generate resources only when the setup is correct
That one layer of feedback makes a generator feel much more professional.
3. Dependency checks are part of usability
This is one of those features that is not flashy, but it solves a real pain.
A generator may support optional features like GraphQL, caching, OpenAPI, Docker integration, or workflow generation. But if the target project is missing required dependencies, the user often discovers that only after compilation fails.
That is a bad experience.
A dependency check in the validation step gives immediate feedback:
- your spec enables X
- your project is missing Y
- fix that first
This is not a “marketing feature,” but it is exactly the kind of thing that makes a tool feel mature.
4. Sorting is a small feature with big practical value
If a tool generates list endpoints, sorting quickly becomes one of those things users expect by default.
Basic CRUD is rarely enough on its own.
Even a very simple generated API becomes much more useful if it supports controlled sorting like:
- sort by
name - sort by
price - sort by
releaseDate
The important part is not just adding sorting, but adding it in a controlled way.
A good generator should not blindly allow sorting by anything. It should let the user explicitly define which fields are sortable. That gives a better balance between flexibility and predictability.
For example:
sort:
allowedFields: [name, price, releaseDate]
defaultDirection: ASC
This kind of design keeps the spec simple while still making the generated API more realistic.
Sorting may not sound like a major release feature, but it makes generated CRUD resources feel much closer to something you would actually expose and use.
5. Documentation is not just documentation
Good documentation does more than explain features.
It answers silent questions like:
- What does this tool actually generate?
- How much setup is required?
- What does the generated result look like?
- Can I trust the output?
- Is this maintained?
- Is there a concrete example I can follow?
A README is not just a description. It is part of the product.
A clearer README reduces confusion, shortens onboarding time, and makes it easier for users to move from curiosity to actual usage.
That is especially important for generators, because they involve a bigger trust jump than a typical library.
With a normal library, a developer adds one dependency and tries one API.
With a generator, they are letting a tool create part of their codebase.
That requires more confidence.
6. A demo video changes how people evaluate the project
This may be the most underrated part.
Developers believe much faster when they can see the flow.
A short demo video can answer in under a minute what a long README sometimes cannot fully communicate:
- here is the CRUD spec
- here is the generation step
- here is the generated project
- here is the app running
- here are the API calls working
That does two things at once:
- it proves that the tool works
- it makes the project feel real
For generator-style tools, that visual proof matters a lot.
People do not just want to see source code. They want to see the end-to-end path from input to working result.
In many cases, a demo video is not “extra content.”
It is part of trust-building.
7. The best improvements are often not the loudest ones
Not every useful release looks impressive in a headline.
Some improvements are exciting and obvious.
Others are quieter, but they make the product much better:
- better validation
- better docs
- better defaults
- safer generation flow
- fewer compile-time surprises
- more realistic generated endpoints
These things may not always look like major product announcements, but they are often what move a project from “interesting” to “actually usable.”
That distinction matters.
Because many tools can generate code.
Far fewer tools make the full workflow feel safe, clear, and dependable.
Final thought
If you are building a generator, think beyond output quantity.
Do not focus only on how many files you can generate.
Focus on things like:
- how easy it is to validate input
- how safe it is to run generation
- how realistic the generated result is
- how quickly a new user can trust what they are seeing
That is where usability really comes from.
I recently pushed a new release of my own project, Spring CRUD Generator, with exactly that mindset in mind: improving validation, adding dependency checks, introducing entity-level sorting, cleaning up the README, and adding a demo video plus the demo CRUD spec used in that video.
Repository: https://github.com/mzivkovicdev/spring-crud-generator
It is not the flashiest kind of release, but it is the kind of release that makes a tool more usable in real life.
Top comments (0)