Assembly Code Documentation Generator - AI Docs & Docstrings

Generate Assembly documentation with AI: add comments and docstrings to your code, or create a README, API reference, architecture overview or usage guide — for a single file or an entire project.

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The Large Language Model (i.e. AI) to use for code generation.
Cost: 1 credit
Drop files, folders or a project .zip here — or click to select. If you want to upload to the sandbox environment, please enable the Code Execution in the "Advanced Tools" below before uploading.
Import from GitHub The AI clones the repository inside your code-execution sandbox and works on it there — Code Execution turns on automatically. A token is only needed for private repos: it is placed in the ephemeral sandbox and never stored in our database. Still, use a temporary fine-grained token scoped to just that repository, and revoke it after. Optional
Private repo? Create a fine-grained token scoped to just that repo.
Choose in-code documentation (comments & docstrings woven into your code) or a standalone document generated from your code, ready to drop into your repository.
Auto follows your language's standard convention (PEP 257 for Python, JSDoc for JavaScript, Javadoc for Java...). Pick a specific style to match your project's existing docs.
Your Code or Project Works on entire projects: drop a .zip or folder in the upload area above (parsed right in your browser into a file tree where you pick what to include) or import a GitHub repository — huge projects are handed to the AI's sandbox automatically. Or simply paste code here.
How detailed should the documentation be? Brief covers the essentials; In Detail explains purpose, behavior and edge cases thoroughly.
Brief
Moderate
In Detail
Optional: tell the AI about your audience, conventions, or sections you want included or skipped. Optional
Characters: 0
Advanced Tools ▼


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Learn more.

Assembly code documentation, generated — not hand-written

Most AI tools stop at sprinkling comments over a snippet. This documentation generator reads your Assembly code the way a new team member would — single file or entire project — and produces the documentation you actually need: docstrings and comments woven into the code itself, or standalone Markdown documents (README, API reference, architecture overview, usage guide) ready to commit to your repository.

Five kinds of documentation, one tool

Pick a type above
  • Comments & docstrings — your complete code returned with documentation added, in the docstring style you choose (Google, NumPy, reST/Sphinx, JSDoc, Javadoc, Doxygen, XML doc comments) or your language's default.
  • README.md — what the project does, features, installation, usage with real examples from your code.
  • API reference — every public class, function and constant: signatures, parameters, returns, errors, examples.
  • Architecture overview — components, responsibilities and data flow, with a Mermaid diagram.
  • Usage guide — a step-by-step tutorial for new users of your code.

Document a whole project, not one file at a time

Multi-file aware

Drop a project .zip or a folder into the upload area and it's parsed instantly in your browser — nothing is uploaded. You get a file tree that auto-skips the junk (node_modules, binaries, lockfiles) where you tick exactly which files to document, with a live character budget. The AI treats the selection as one codebase — it infers the project's purpose, entry points and structure, and documents how the pieces fit together instead of describing each file in isolation.

For the best result

  • Include the entry point (main, index, app) so the AI understands how the project is used.
  • Set the depth slider to match your audience — brief for experienced developers, in-depth for onboarding docs.
  • Use the instructions field for team conventions (tone, sections, what to skip).
  • Generating several documents? Run once per type — each produces a focused, complete document.

When to enable Web Access and Code Execution

These tools provide different kinds of context and verification. Enable them when they improve the task.

Web Access

Use for current docs

Enable Web Access when the task depends on current documentation, an external API, or a third-party package—especially a new, niche, or less familiar library.

For the best result

  • Paste the official documentation URL into your prompt.
  • Name the package and version you intend to use.
  • Ask the model to follow the linked API instead of relying on memory.
  • For multiple sources, say which source is authoritative.

Example: “Use version 4.x and follow the official documentation at https://docs.example.com/.”

Code Execution

Use for automatic checks

Enable Code Execution when you want the model to run the code, execute tests, reproduce an error, or compare the result with an expected output.

Particularly useful for

  • Algorithms with testable inputs and outputs.
  • Parsing, data transformation, and numerical tasks.
  • Debugging a reproducible error.
  • Checking that dependencies install and tests pass.

Credit note: Running and iterating on code may consume more credits than a single response alone. Leave execution off when you only need a small snippet you can inspect yourself.

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Browse public code generations for inspiration, or contact us if you have any questions.