Code documentation writer: how to document functions with parameters and examples
The Code documentation writer tool creates textual descriptions of provided functions: parameters, return values, examples and limitations. You insert code into the "Code and error message" field, specify the platform or application, choose the output language and press Generate. The result appears in a separate panel: it can be copied or downloaded as a plain text TXT file. In this article we will explore how to prepare source code, formulate instructions, check the result and account for tool limitations so that the documentation is accurate and useful.
Open tool: Code documentation writer ↗Input and how it works
The tool works as a web form with two text fields. In the "Code and error message" field you insert the source code of a function or module that needs to be documented. In the "Platform or application" field you specify the language, framework or environment so that the description takes into account syntax and platform-specific features. For example, for a Python function specify "Python 3.10" or "Django" - this will help get more accurate examples and limitations.
After filling the fields you select the output language and press Generate. The result appears in a separate panel as plain text. It can be copied or downloaded in TXT format. The tool does not execute code, does not connect to your development environment and does not analyze the project as a whole: it processes only the text you have inserted. If the code contains errors or incomplete fragments, this will affect the quality of the documentation.
Maximum length of the first field is 8000 characters, the second field is 1000 characters. This is enough for most individual functions and small modules. If the function is large, split it into parts or document only key methods. Remove line numbers and service comments from the inserted code that may confuse the tool.
Example input: Python function code: def add(a, b): return a + b; platform: Python 3.9.
Influencing the description content
The tool has no preset styles or sliders, but the result can be influenced by adding brief instructions to the first field. For example, to get a description for beginners, add the phrase: "Describe the function in plain language, avoiding technical jargon, with a beginner example." For experienced developers specify: "Focus on performance, exception handling and edge cases." Such instructions become part of the input data, and the tool tries to take them into account.
You can change the formulation of the task: instead of plain code insert code with a comment-instruction, for example "# Generate documentation in JSDoc style" or "# Format as API description with request and response examples." Do not overload the field: too long instructions may be truncated or ignored. Formulate clearly and concisely, highlighting the main requirement.
The "Platform or application" field also affects the result. If you specify "Web application" instead of "Python 3.9", the description may shift towards integration and browser usage. This does not guarantee drastically different text, but increases the chances of getting relevant examples. Experiment with combinations: code, instruction, platform. Successful variants copy to a separate file, as the tool does not store history.
Instruction: "Describe the add function for beginners, with an example of adding two numbers and an explanation of what parameters are."
Comparing description variants for one function
Consider a Python function: def add(a, b): return a + b. Without additional instructions the tool will output a standard description: the function takes two arguments a and b, returns their sum, example add(2, 3) returns 5, limitation - does not check types. With the instruction "For beginners, with a detailed explanation of each step" the result will contain an explanation of what parameters are, how to pass values and what will happen when adding strings.
With the instruction "For experienced developers, with an emphasis on performance and overloading" notes will appear about the absence of overloading and exception handling. Comparing variants, you will see that the first is suitable for quick reference, the second for educational materials, the third for technical documentation. None of them is exhaustive: the second may lack information about the return type, the third may lack usage examples. Therefore after generation the text is recommended to be supplemented manually.
For clarity you can summarize the results in a table: criterion, variant 1, variant 2, variant 3. But the tool does not create tables automatically. You will have to copy the texts and format them yourself. This is yet another reason why generation is only the first step, not a ready artifact.
Variant 1: "Function add(a, b) returns the sum of a and b. Example: add(2, 3) -> 5. Limitation: does not work with non-numeric types without error."
Selecting and refining the result
After generation choose the variant closest to your goal. For internal documentation an emphasis on performance may suit, for a public API a more detailed description with examples. However do not use the generated text without edits: the tool may misinterpret types, miss important limitations or provide a non-existent example. Always verify the description against the source code.
Refinement involves several steps. Ensure that parameter descriptions match the actual code, including default arguments. Check examples: run them in an interpreter to verify correctness. Add an "Limitations" section if it is missing. For add this may be: "Does not perform type checking, so passing strings results in concatenation." Bring the description to a uniform style if documenting several functions.
If the result seems incomplete, you can generate another variant with an refined instruction, for example: "Include an exception handling section and examples with bad data." But the tool does not guarantee presence of all sections - it follows the request to the extent of its capabilities. Final responsibility for documentation lies with you.
After generation add manually: "Return value: number or string depending on argument types."
Text checking and typical errors
Checking starts with matching the text and source code. Read the description and be sure that every parameter, return value and example correspond to the code. If the tool says the function handles exceptions but the code has no try/except, that is an error. Also check that examples are not made up: they should be executable and give the expected result.
Special attention should be given to limitations. The tool may not know the specifics of your environment: for example write that the function works with any numbers, although in your case it is used only with integers. Or fail to mention that overflow causes an error. Add the limitations section based on your experience and testing.
Another way to check - ask a colleague to read the documentation and reproduce the examples. If questions arise the text is not clear enough. Comparison with official documentation of similar functions in your language or framework will help identify missing details. The tool is not a source of truth; it is an assistant that saves time on a draft.
Check: run add(2, 3) and make sure it returns 5 as stated in the example.
Tool limitations
The tool does not support export to DOCX or PDF, does not perform batch processing and does not save history. Only TXT file can be downloaded. No document uploading, OCR or panel customization is possible. All interaction happens through two text fields, so for documenting several functions you will have to generate text one by one and manually combine the results.
The tool does not analyze code dynamically: it does not run it and does not check types. Therefore inaccuracies may appear in the documentation. For example, for the add function it may write that it returns an integer, although string concatenation returns a string. Or it may not mention that a TypeError occurs when passing arguments of different types. This is a typical error that must be corrected manually.
The tool works only with text. If you need diagrams or schemes, they must be created separately. Take this into account when planning work and do not expect from the tool more than it can give.
Limitation: the tool will not check that add('2', '3') returns '23' not 5.Practical recommendations
Use the tool as a draft generator. Start with a simple request, then refine instructions until you get an acceptable variant. Save successful formulations in a separate file to apply to other functions. For example when documenting a library create a template: "Describe function [name] with parameters, return value, example and limitations. Style: official, for developers." Then substitute the code.
Observe the 8000 character limit for code. If the function is large split it into parts or document only key methods. Remove unnecessary characters, line numbers and service comments from the inserted code that may confuse the tool.
Always check the result. The tool may err and its answers do not guarantee accuracy. Use it to speed up routine work but do not rely on it blindly. Combine generated text with your own knowledge and testing - then the documentation will be both useful and correct.
Request template: "Generate documentation for a Python function. Include parameters, return value, example and limitations. Style: for beginners."
The Code documentation writer tool allows quickly creating draft descriptions of functions, but requires attentive attitude to input data. Specify the platform, add brief instructions, compare variants and edit the text manually. Remember the limitations: the tool does not analyze code dynamically, does not save history and does not export to complex formats. Always check the generated text for correspondence with the code and add missing details. Use the tool as an assistant, not as a replacement for a developer.
Open tool: Code documentation writer ↗Interface translations are machine-assisted and may need refinement.