Code documentation writing: practice describing functions

Why active practice is better than copying

When you simply copy generated documentation, your brain does not do the work of analyzing code: you do not learn to spot edge cases, you do not train your memory on function signatures and you do not develop your own description style. Active practice means you first break down a function yourself, write a draft documentation, and then use the tool as a source of feedback. It is like solving a problem before looking at the answer: even if the answer matches, you have already done mental work.

The Code documentation writer tool outputs text based on the code you enter. It does not check your version or give a rating. Therefore it is important to organize the cycle yourself: attempt → generation → comparison → correction. This cycle can be repeated for different functions, gradually increasing difficulty. For example, start with simple arithmetic functions, then move on to functions with multiple parameters, then to functions with side effects or exception handling.

Active practice also helps fight the illusion of understanding. Often it seems code is understandable, but when you try to describe parameters and return values you discover gaps. The tool here acts as a neutral standard: it will show which aspects you omitted, but the final decision on correctness remains with you.

Exercise example: take the function def add(a, b): return a + b. First write its documentation manually: describe parameters a and b, return value, provide a call example and indicate limitations (e.g. works only with numbers). Then enter the code into the tool and compare the formulations.

How to prepare code for accurate documentation

The tool accepts code in a text field. To get a useful result, the code must be syntactically correct and as self-contained as possible. If a function uses external variables or imports, add a brief explanation in the Platform or application field or in comments. For example, for a function dependent on a library, specify this in the description so the tool does not guess the context.

The more context you provide, the more accurate the documentation will be. But do not overload: the tool does not analyze the whole project, it works with the provided fragment. If a function is large, it is better to break it into logical parts or document one at a time. Also it is useful to specify the programming language version or platform if behavior depends on the environment.

Before entering check that the code contains no syntax errors. The tool may try to interpret erroneous code, but the result will be less reliable. If you are deliberately documenting code with an error, indicate this in a comment so the tool does not consider the error normal.

In the Code and error message field enter:

def add(a, b):
    return a + b

In the Platform or application field specify: Python 3.10, study example.

Step-by-step exercise: from manual draft to comparison

Step 1. Choose a small function, for example from a tutorial project or open source code. Read it and write documentation in free form: purpose, parameters with types, return value, example, limitations. Do not look at the tool.

Step 2. Enter the code into the Code documentation writer tool, select output language and press Generate. You will get text in a separate panel. Copy or download it as TXT.

Step 3. Compare your draft with the result. Pay attention to: completeness of parameter descriptions, presence of examples, mentioning of limitations, accuracy of wording. Highlight discrepancies. If the tool indicated something you missed, check if it really follows from the code.

Step 4. Fix your draft, combining the best from both versions. If you think the tool made a mistake, formulate why. This develops critical thinking.

Step 5. Repeat with another function, gradually complicating. Keep a log: what types of errors do you make most often (e.g. forgetting side effects or returning None).

For the add function your draft might be: "Adds two numbers. a — first number, b — second. Returns sum. Example: add(2,3) -> 5. Limitation: does not check types." The tool may add: "If arguments are not numbers, behavior depends on the + operation." Compare and refine.

How to check the result and avoid pitfalls

Generated documentation may contain errors: the tool does not execute code, it analyzes its text. It may incorrectly determine the return type, skip an exception or invent a non-existent limitation. Therefore every statement must be verified against the code. If documentation says "returns a string" but the code has return a + b where a and b are numbers, that is an error.

Checking is especially important for functions with side effects: modification of global variables, file writing, network requests. The tool may not mention them if they are not obvious from the signature. Always compare with the function body.

Another pitfall is overconfidence in format. The tool outputs text but does not guarantee it matches your project standards (e.g. Google Style or NumPy docstring). Use it as a draft, not as a final document.

If the tool wrote "Function returns None" but the code has return a + b, that is an error. Check every sentence.

Tool limitations and what it does not do

The tool works only with the text code you entered. It does not have access to your project, does not run code, does not check types and does not test the function. Therefore it cannot guarantee that documentation matches real behavior in all cases.

The interface does not support export to DOCX or PDF, there is no batch processing, automatic saving, integrations or change highlighting. You can only copy the result or download it as TXT. This means for mass documentation you have to repeat operations manually.

There is also no version comparison mode, no OCR for recognizing code from images. If you need to document code from a screenshot, you first have to enter it manually. The tool is not intended for image or audio generation: it is a text tool.

Do not try to upload a code file: the field accepts only text. Maximum 8000 characters for code and 1000 for details.

How to embed the exercise in regular practice

Set aside 15–20 minutes a day for one exercise. Choose a function from a real project you did not write. First document manually, then check with the tool. Record which aspects you most often omit and target them specifically.

You can complicate the task: document a function in Russian, and ask the tool to output in English, or vice versa. This trains translation of technical terms and understanding of style differences.

Another option — work in pairs: one writes documentation, the other checks with the tool. Discussing discrepancies yields more than individual work.

Weekly plan: Monday — simple functions, Wednesday — functions with conditions, Friday — functions with loops and exceptions. At the end of the week review your drafts and compare with new generations.