AI Module Generator
Generate clean, reusable code modules in seconds
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What does your newest module actually expose? Three functions, or thirty because nobody decided and everything ended up public?
A module is a boundary before it is a file. What goes out, what stays in, and what the outside world is allowed to depend on. The AI Module Generator writes that boundary from a description, so the public surface is a decision rather than an accident of what happened to be at the top of the file.
Short answer: The AI Module Generator is a free AIToolsay tool that writes a complete module from a description of its job and its public interface. Choose the language and code style, and decide whether to include error handling, usage examples, tests and documentation comments.
What is AI Module Generator?
A module here means a self contained unit with a public interface and private internals: a Python module, a JavaScript or TypeScript module, a Go package file, a PHP namespace file, a Ruby module.
The prompt box asks you to describe what the module generator should produce, with requirements, inputs and expected behaviour. For a module the description needs two halves. What the module is responsible for, and exactly what it exposes.
That second half is the one people skip and the one that decides whether the module ages well. A module with four exported functions can be rewritten inside. A module with twenty cannot be touched.
Why Use AI Module Generator?
Modules written incrementally grow their interface by accident. A helper gets exported so a test can reach it, and two years later three teams depend on it.
Generating from a description flips that around. You state the interface first and the implementation is written to fit it. Everything not on your list stays private, because nothing forced it out.
| Module written | Public surface | Consequence |
|---|---|---|
| Incrementally, over months | Whatever got exported along the way | Every internal change is a breaking change |
| From a stated interface | Only what you listed | Internals stay free to change |
| Copied from a similar module | The other module's surface | Exports nobody in this context needs |
Interface first
You list what the module exposes and the implementation is written behind it, not the other way round.
Errors at the boundary
Include Error Handling puts validation where callers hit it rather than deep inside a private helper.
Documentation comments
Comment Level set to Fully Documented gives every exported item a doc comment, which is what module consumers actually read.
Tests against the interface
Generate Tests exercises the public surface, which is the only part that needs a contract.
How Does AI Module Generator Work?
- Prompt box. Open the AI Module Generator and describe the module's responsibility and its exports.
- Model selector. Choose the engine from MSB AI, OpenAI ChatGPT, Google Gemini, Anthropic Claude AI, xAI Grok AI, DeepSeek, Qwen, Meta AI, NVIDIA AI, OpenRouter AI and MiniMax.
- Advanced options accordion. The panel holds ten controls: Language, Code Style, Comment Level and Output as dropdowns, four toggles, a Detail Level slider and a free text field.
- Generate button. Description, model and settings run through the prompt engineering layer written for code generation, which is the instruction set that returns a file rather than advice about files.
- Output card. The module appears below the button with a live word count, plus copy, listen, reuse, download and open in full view.
- Export row. DOC, TXT and HTML downloads on every result. TXT keeps the file clean.
- Activity history. Session generations stay listed, which is how a set of modules built in one sitting keeps a consistent shape.
Best Use Cases
- A client wrapper around an external service, with retries and error mapping behind a small interface
- A domain module holding rules that are currently spread across three files
- A formatting or parsing module where the internals are fiddly and the interface is two functions
- A feature flag or configuration module with one read function and a lot of private logic
- Porting a module from one language to another with the same public surface
| Module type | Comment Level | Detail Level |
|---|---|---|
| Shared internal library | Fully Documented | 70 |
| Feature specific module | Light Comments | 50 |
| Third party service wrapper | Well Commented | 75 |
| Prototype module | No Comments | 30 |
Note Write the exports as a list with signatures. Four lines naming what goes out is worth more than four paragraphs describing what the module is about.
Advanced Options Guide
| Option | What it controls | When to change it | Suggested start |
|---|---|---|---|
| Language | Auto Detect, Python, JavaScript, TypeScript, Java, C#, C++, Go, PHP or Ruby | Always set it. Module systems differ more than syntax does | Your project language |
| Code Style | Clean / Idiomatic, Beginner Friendly, Production Ready, Minimal, Verbose, Functional, Object Oriented or Performance Optimized | Functional when the module is stateless transformations | Clean / Idiomatic |
| Comment Level | No Comments, Light Comments, Well Commented or Fully Documented | Fully Documented for anything other teams import | Well Commented |
| Output | Code Only, Code + Explanation, Code + Tests, Code + Usage Example or Step by Step | Code + Usage Example, because a module is judged by how it is called | Code + Usage Example |
| Add Comments | Adds inline notes inside the implementation | Turn off when only the public interface needs documenting | On |
| Include Error Handling | Adds validation and failure paths at the module boundary | Leave on for anything with external callers | On |
| Include Example Usage | Shows the module imported and used | Keep on. It exposes an awkward interface immediately | On |
| Generate Tests | Produces tests against the exported functions | Leave on. Tests against the public surface are the ones worth having | On |
| Detail Level | Slider from 1 to 100 setting how complete the internals are | Raise it when the module wraps something with many failure modes | 60 |
| Custom Instructions | Free text up to 1000 characters over the settings | Use it for import conventions, error types and layering rules | "Named exports only, raise our AppError type, no direct database access" |
Important The module will not know your existing error types, logging setup or layering rules. Those belong in Custom Instructions, and without them you get a module that works in isolation and does not fit your project.
Example Outputs
Prompt: a module wrapping a postcode lookup service. Exports two functions, holds an internal client with retries, and maps every provider error to one of three known cases.
Settings: Language TypeScript, Code Style Production Ready, Comment Level Fully Documented, Output Code + Usage Example, Include Error Handling on, Generate Tests on, Detail Level 70, Custom Instructions "named exports only, no default export, throw AppError".
export async function lookup(postcode: string): Promise<Address[]>
export async function validate(postcode: string): Promise<boolean>
// internal, not exported
// - createClient() with timeout and two retries
// - normalise() strips spaces and upper cases
// - toAppError() maps 404, 429 and 5xx to known casesTwo exports, three private helpers. The list of private helpers is the useful part of that output, because it shows the module drew the line where you asked rather than exporting everything it happened to define.
If the module boundaries themselves are still undecided, sketch them with the AI Software Architecture Generator before writing any of them.
Tips & Common Mistakes
What makes a good module prompt
- One sentence of responsibility, then a list of exports with signatures
- Named error cases the module is allowed to raise
- Layering rules, such as what it may and may not talk to
- The style of import your codebase uses
What goes wrong
- Describing behaviour without listing exports, so everything becomes public
- Two responsibilities in one description, giving a module you will split
- Leaving error types unspecified, so the module invents its own
- Accepting a module that imports something your layer is not allowed to touch
- ✅ Responsibility stated in one sentence
- ✅ Exports listed with signatures
- ✅ Error cases named
- ✅ Layering rules in Custom Instructions
- ✅ Imports checked against what this layer may depend on
Comparison Table
| Approach | Interface quality | Speed |
|---|---|---|
| Growing a module over time | Accidental, widens forever | Slow in total |
| Copying a similar module | Inherited from elsewhere | Fast |
| Designing then writing by hand | Good | Slowest |
| AI Module Generator | Exactly what you listed | One pass, then review |
Pro tip Write the usage example yourself, before generating anything, and paste it in as part of the description. Designing a module from how you want to call it is the oldest trick in interface design, and it works even better when something else writes the implementation. The AI Technical Spec Writer is a good place to record that decision afterwards.
AIToolsay is a free AI tools platform built from dedicated workspaces rather than one general chat box with many labels. Every tool has its own prompt engineering and its own options panel, so a code tool asks about language, comments and error handling instead of tone and word count. All the tools are free to run and no account is needed. You also pick which engine answers, from MSB AI, OpenAI ChatGPT, Google Gemini, Anthropic Claude AI, xAI Grok AI, DeepSeek, Qwen, Meta AI, NVIDIA AI, OpenRouter AI and MiniMax, and interface decisions differ enough between engines that a second run is often instructive. Alongside the tools sit an AI directory, an AI models directory, courses, prompts, guides and news, all reachable from the AIToolsay homepage.
Frequently Asked Questions
Is the AI Module Generator free?
Yes. It is free to use, nothing is installed, and no account is needed to generate a module.
What is the difference between this and the class generator?
A class is one type with state and behaviour. A module is a file with a public interface, which may contain several functions, a class or none at all. Choose by what the unit is, not by size.
How do I control what gets exported?
List the exports explicitly in your prompt with their signatures. Anything not on the list stays internal, which is the main reason to generate a module rather than grow one.
Will it respect my project's layering rules?
Only if you write them down. Put rules such as "may not import the database layer" into Custom Instructions and check the imports in the output.
Can it generate several modules that work together?
Generate them one at a time in the same session with the same Custom Instructions. The activity history keeps them all visible while you check that the interfaces line up.
Should the tests be generated too?
Yes for anything with external callers. Tests written against the exported interface are the ones that survive an internal rewrite, which is exactly what a module boundary is for.
What if my module needs to hold state?
Say so, and say whether that state is per process or per call. Module level state is easy to write and hard to test, so it is worth being explicit about before the code exists.
The value of a module is in what it refuses to expose. Decide the interface first, write it into the prompt as a list, let the AI Module Generator fill in the implementation behind it, and keep the freedom to change everything that stayed private.
Thanks for reading. If it helps you draw a cleaner boundary, join the AIToolsay community, follow along on social media, turn on push notifications for new tools, and subscribe to the newsletter for the occasional round up.
Let AI Speak.
Sabir
Founder of AIToolsay and a passionate AI enthusiast dedicated to building practical, user-friendly AI tools that simplify everyday tasks.
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