How does Atlas ensure MATLAB documentation is up-to-date?

Atlas ensures MATLAB documentation is always current by generating READMEs directly from your `.m` source files. It uses the `lsp` tool to enumerate the actual public API and `read` and `codebase_search` to understand current implementation and usage, guaranteeing the documentation reflects what the code does today, not what it was intended to do a year ago.

Can Atlas document `classdef` blocks in MATLAB?

Yes, Atlas is fully capable of documenting `classdef` blocks in MATLAB. It uses the `lsp` tool's `documentSymbol` operation to identify class definitions, properties, and methods, ensuring that the public interface of your MATLAB classes is accurately represented in the generated README.

What MATLAB tools does Atlas integrate with for documentation?

Atlas integrates direct with core MATLAB tools. It understands `.m` files, `classdef` blocks, and can be prompted to run `matlab.unittest (runtests)` for verification. Additionally, Atlas can apply `MATLAB Format Code` conventions to any files it modifies, ensuring consistency with your existing MATLAB development practices.

How does Atlas handle code examples in MATLAB READMEs?

Atlas rigorously handles code examples in MATLAB READMEs by verifying every single one. After drafting the documentation, Atlas uses the `bash` tool to execute each code sample, confirming its functionality and accuracy. This process ensures that all examples provided are reliable and work as described for MATLAB developers.

Is my MATLAB code safe when using Atlas for documentation?

Yes, your MATLAB code is safe with Atlas. Every Atlas tool call is permission-gated, requiring your explicit approval. Atlas drafts plans in a read-only agent, computes a unified diff for all proposed file edits, and surfaces it for your review before writing any changes. It also snapshots file changes as git patches for easy rollback.

Can Atlas use local embeddings for MATLAB code indexing?

Yes, Atlas can build its code index for MATLAB projects with local Ollama embeddings. This capability ensures that your MATLAB code remains off third-party servers, enhancing privacy and security while still enabling Atlas's powerful hybrid semantic and keyword retrieval for code search and analysis.

How does Atlas find existing READMEs in a MATLAB repository?

Atlas uses the `grep` tool to search your MATLAB repository for an existing README.md file. This allows Atlas to identify and match the established heading structure and tone of your project's documentation, ensuring that any new or updated READMEs maintain consistency with your existing project standards rather than inventing a new format.

Document a module with a README in MATLAB with Atlas in 2026

Atlas helps MATLAB developers in 2026 produce accurate, up-to-date documentation for modules by reading `.m` files, enumerating public APIs with the `lsp` tool's `documentSymbol` operation, and verifying code samples with `bash`, ensuring the README reflects current code behavior, not outdated specifications. This process guarantees that every claim in your documentation is traceable to the actual implementation.

How Atlas generates accurate MATLAB READMEs from source code

Atlas generates accurate READMEs for MATLAB modules in 2026 by directly analyzing your `.m` files, ensuring the documentation reflects the code's current state rather than outdated specifications. This process involves several Atlas tools working in concert to capture the module's public API and its real-world usage.

To produce documentation that describes what the code actually does today, Atlas employs a robust workflow. First, it uses the `lsp` tool's `documentSymbol` operation to enumerate the real exported surface of your MATLAB module, ensuring no function or class definition is missed or invented. This means Atlas reads your `.m` function files and `classdef` blocks to understand the public interface. Next, Atlas uses the `read` tool to examine the implementation of each export. To understand how these exports are actually used in practice, Atlas leverages `codebase_search` across your repository. This combination allows Atlas to draft a README with the `write` tool, quoting real MATLAB signatures and real file paths, making the documentation traceable and reliable. The entire process is designed to provide a precise, current description of your MATLAB code's functionality.

Enumerating MATLAB module APIs and analyzing usage with Atlas

Atlas precisely enumerates a MATLAB module's public API using the `lsp` tool's `documentSymbol` operation, ensuring 100% coverage of exported functions and classes. This capability is crucial for generating comprehensive documentation that accurately reflects the module's interface in 2026, preventing omissions or invented features.

For MATLAB projects, Atlas begins by running in a folder containing your `.m` files and any `buildfile.m`. It then uses the `lsp` tool's `documentSymbol` operation to identify all public functions, class definitions, and properties within your MATLAB module. This ensures that the generated README covers every part of the module's external interface. After enumerating the API, Atlas uses the `read` tool to delve into the implementation details of each identified export. To provide context on how these functions and classes are actually utilized, Atlas performs a `codebase_search`. This search identifies real-world call sites and usage patterns within your codebase, allowing the documentation to describe not just what a function is, but how it is practically applied. This approach ensures that the README provides concrete, specific examples relevant to your MATLAB development environment.

Verifying MATLAB code samples in documentation with Atlas

Atlas verifies every code sample included in your MATLAB documentation by running it with `bash`, ensuring that all examples are functional and accurate in 2026. A code sample that was never executed is a liability, and Atlas eliminates this risk by actively testing the provided snippets.

A critical step in producing high-quality MATLAB documentation is ensuring the accuracy of code examples. Atlas addresses this by using the `bash` tool to execute every code sample it includes in the README. This verification step confirms that the examples are syntactically correct and produce the expected output, preventing the inclusion of broken or misleading code. For instance, if your documentation includes a snippet demonstrating a `matlab.unittest.TestCase` subclass, Atlas will attempt to run it. This rigorous verification process means that when a MATLAB developer reads your README, they can trust that the code samples provided will work as described. This commitment to executable examples significantly enhances the utility and reliability of the generated documentation for any MATLAB project.

Ensuring safety and review for MATLAB documentation updates with Atlas

Atlas prioritizes safety and developer control in 2026 by making every tool call permission-gated and presenting a unified diff for all proposed MATLAB file edits. This ensures that documentation updates are transparent and require explicit approval before any changes are written to your `.m` files or README.

Atlas is designed with multiple layers of safety and review, crucial for any MATLAB development workflow. Every Atlas tool call, including `lsp`, `read`, `codebase_search`, `grep`, `write`, and `bash`, is permission-gated against allow, ask, and deny rules before it runs. This means Atlas will ask for your permission before performing actions like reading your `.m` files or writing to a README. Atlas drafts a plan in a read-only plan agent and asks for approval before switching to a build agent to execute changes. Furthermore, Atlas computes a unified diff for every file edit it proposes, such as changes to a README.md or even applying `MATLAB Format Code` conventions to touched `.m` files. This diff is surfaced for your approval, allowing you to review and accept or reject changes before they are written to disk. Atlas also snapshots file changes as git patches, so edits can be diffed and rolled back, providing an additional safety net for your MATLAB codebase.

Integrating Atlas with the MATLAB toolchain for documentation

Atlas direct integrates with the standard MATLAB toolchain in 2026, recognizing `.m` files, `classdef` blocks, and leveraging tools like `matlab.unittest (runtests)` and `MATLAB Format Code`. This integration ensures that documentation generation aligns with your existing MATLAB development practices.

Atlas is built to understand and interact with the MATLAB ecosystem. When you run Atlas in a folder containing your `.m` files and any `buildfile.m`, it automatically recognizes your function signatures, `classdef` blocks, and the toolboxes your code calls into. This deep understanding allows Atlas to accurately enumerate your module's public API and read its implementation. For quality assurance, Atlas can be asked to run `matlab.unittest (runtests)` behind a permission prompt, allowing you to review failing assertions and ensure your code is robust before documentation is finalized. After generating or updating documentation, Atlas can apply the `MATLAB editor Format Code` conventions to any touched files, ensuring consistency with your project's style guidelines before you approve the changes. This tight integration means Atlas enhances your MATLAB workflow without requiring significant changes to your existing setup.

Step by step

01Run Atlas in your MATLAB project folder containing `.m` files and any `buildfile.m`.
02Atlas uses the `lsp` tool's `documentSymbol` operation to enumerate the public API of your MATLAB module, including functions and `classdef` blocks.
03Atlas employs the `read` tool to examine the implementation of each MATLAB export and uses `codebase_search` to find how callers actually use it in practice across your repository.
04Atlas uses the `grep` tool to search for an existing README.md file in your MATLAB project to match its heading structure and tone.
05Atlas drafts the README using the `write` tool, quoting real MATLAB function signatures, `classdef` definitions, and real file paths from your `.m` files.
06Atlas verifies every MATLAB code sample included in the drafted documentation by running it with the `bash` tool, ensuring its functionality and accuracy.
07Review the unified diff presented by Atlas for the proposed README.md changes and approve them to write the documentation to disk.
08Optionally, ask Atlas to apply `MATLAB Format Code` conventions to any `.m` files it touched during the process before final approval.

Frequently asked questions

How does Atlas ensure MATLAB documentation is up-to-date?: Atlas ensures MATLAB documentation is always current by generating READMEs directly from your `.m` source files. It uses the `lsp` tool to enumerate the actual public API and `read` and `codebase_search` to understand current implementation and usage, guaranteeing the documentation reflects what the code does today, not what it was intended to do a year ago.
Can Atlas document `classdef` blocks in MATLAB?: Yes, Atlas is fully capable of documenting `classdef` blocks in MATLAB. It uses the `lsp` tool's `documentSymbol` operation to identify class definitions, properties, and methods, ensuring that the public interface of your MATLAB classes is accurately represented in the generated README.
What MATLAB tools does Atlas integrate with for documentation?: Atlas integrates direct with core MATLAB tools. It understands `.m` files, `classdef` blocks, and can be prompted to run `matlab.unittest (runtests)` for verification. Additionally, Atlas can apply `MATLAB Format Code` conventions to any files it modifies, ensuring consistency with your existing MATLAB development practices.
How does Atlas handle code examples in MATLAB READMEs?: Atlas rigorously handles code examples in MATLAB READMEs by verifying every single one. After drafting the documentation, Atlas uses the `bash` tool to execute each code sample, confirming its functionality and accuracy. This process ensures that all examples provided are reliable and work as described for MATLAB developers.
Is my MATLAB code safe when using Atlas for documentation?: Yes, your MATLAB code is safe with Atlas. Every Atlas tool call is permission-gated, requiring your explicit approval. Atlas drafts plans in a read-only agent, computes a unified diff for all proposed file edits, and surfaces it for your review before writing any changes. It also snapshots file changes as git patches for easy rollback.
Can Atlas use local embeddings for MATLAB code indexing?: Yes, Atlas can build its code index for MATLAB projects with local Ollama embeddings. This capability ensures that your MATLAB code remains off third-party servers, enhancing privacy and security while still enabling Atlas's powerful hybrid semantic and keyword retrieval for code search and analysis.
How does Atlas find existing READMEs in a MATLAB repository?: Atlas uses the `grep` tool to search your MATLAB repository for an existing README.md file. This allows Atlas to identify and match the established heading structure and tone of your project's documentation, ensuring that any new or updated READMEs maintain consistency with your existing project standards rather than inventing a new format.

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