Code Comment and Docstring Generator

When to use

• When documenting a function before sharing it with classmates or collaborators.
• When converting a rough script into a clearer teaching or research helper.
• When standardizing comments across Python and MATLAB examples.

How to use

1. Enter the code, error text, shape values, or template details requested by the form.
2. Choose the relevant language, style, operation, or option set, then click Generate Comments.
3. Review warnings and unsupported-pattern notes before copying or downloading the result.
4. Paste the generated snippet into your own MATLAB or Python environment only after inspection and testing.

Inputs

Documentation metadata

Language, style, function name, purpose, parameters, returns, raises/errors, example usage, notes, optional context, author/date flag, and license placeholder flag.

Notation

Output explanation

• Generated comments, docstring, help block, TODO comments, or file header.
• Warnings for duplicate parameter names, invalid identifiers, and long context.
• Copy and download actions after successful generation.

Supported patterns

• Python simple comments, NumPy docstring, Google docstring, and file header
• MATLAB help block, section comments, TODO comments, and file header
• parameter, return, error, example, and note fields

Unsupported patterns

• semantic code analysis, automatic complexity review, auto-generated tests
• rewriting source files
• executing code context

Interpretation

• Treat generated code as a starting point that must be tested with representative data.
• Warnings identify cases where the rule-based helper cannot prove semantic equivalence.
• The visual summary is a checklist or structure preview, not an execution trace.

Code-helper guidance

• Explain why the code exists, not only what each line does.
• Keep examples small enough that readers can test them quickly.

Worked examples

Assumptions

• The metadata describes the real function behavior.
• The user will edit generated documentation after implementation changes.

Practical guidance

• Explain why the code exists, not only what each line does.
• Keep examples small enough that readers can test them quickly.

Common mistakes

• Documenting stale parameter names.
• Putting confidential project details into comments that may be shared.

Limitations

• The helper does not execute MATLAB, Python, NumPy, pandas, or Matplotlib code.
• Generated snippets may require imports, workspace variables, data cleaning, or environment-specific changes.
• The rule set does not replace code review, unit tests, validated numerical software, or qualified professional judgment.

Related workflow links