Atlas empowers Java developers in 2026 to generate precise, current README documentation for any module, ensuring the documentation reflects the code's actual behavior today, not its historical intent. By integrating directly with your Java toolchain, including `Maven` for dependency management, `JUnit 5 via mvn test` for verification, and `Spotless` for formatting, Atlas produces traceable documentation grounded in your codebase's current state.
How Atlas enumerates Java module APIs for README generation
Atlas begins documenting a Java module by precisely enumerating its public API using the `lsp` tool's `documentSymbol` operation, ensuring no exported class or method is overlooked. This process, critical for accurate documentation in 2026, prevents omissions or invented interfaces, providing a complete surface area for the README.
To create a comprehensive and accurate README for a Java module, Atlas first identifies every public-facing component. It leverages the `lsp` tool's `documentSymbol` operation, which queries the Language Server Protocol to retrieve a structured list of all declarations within your Java source files, typically found in `src/main/java`. This includes public classes, interfaces, enums, methods, and fields. By relying on the actual Abstract Syntax Tree (AST) declarations, Atlas guarantees that the documented API surface is exactly what the Java compiler sees, eliminating any guesswork or reliance on outdated specifications. This foundational step ensures that the generated README covers the entire public contract of your Java module, making it a reliable reference for other developers.
How Atlas understands Java code behavior and usage
To describe what Java code actually does, Atlas employs a two-pronged approach: it `read`s the implementation of each public API and then uses `codebase_search` to find real-world usage examples. This ensures the documentation reflects how developers use the module in 2026, not just its theoretical design.
Understanding the practical behavior of a Java module goes beyond just its API signatures. Atlas uses the `read` tool to delve into the implementation details of each public Java method and class, analyzing the logic and dependencies. Concurrently, the `codebase_search` tool scans your entire Java project to find concrete examples of how these public APIs are invoked by other parts of the application or within `JUnit 5` test cases in `src/test/java`. This hybrid semantic and keyword retrieval, fused by reciprocal rank fusion, allows Atlas to identify common patterns, typical input parameters, and expected outputs. By observing actual usage, Atlas can generate documentation that accurately describes the module's runtime behavior and common idioms, providing insights that a developer would gain from extensive code review.
Matching existing README style in Java projects
Atlas ensures new READMEs integrate direct into your Java project by first using the `grep` tool to locate and analyze existing `README.md` files. This step, crucial for maintaining consistent documentation standards in 2026, allows Atlas to adopt the established heading structure, tone, and formatting conventions rather than inventing a new style.
Consistency is key for maintainable documentation. Before writing a new `README.md` for a Java module, Atlas employs the `grep` tool to search the repository for any existing `README.md` files. This allows Atlas to learn the project's preferred documentation style, including heading levels (e.g., `# Module Name`, `## Usage`), code block formatting, and overall tone. For instance, if existing READMEs use specific formatting for Java code snippets or link to `pom.xml` for dependency information, Atlas will emulate these conventions. This approach ensures that the newly generated documentation feels native to your Java codebase, reducing friction for developers and maintaining a unified documentation experience across your projects.
Writing and verifying Java code samples in READMEs
After gathering all necessary information, Atlas uses the `write` tool to generate the `README.md` content, incorporating real Java signatures and file paths directly from the source. Crucially, every Java code sample included in the documentation is verified by running it with `bash`, ensuring 100% accuracy and preventing outdated or non-functional examples.
The `write` tool is responsible for composing the final `README.md` content, synthesizing the API enumeration, behavioral insights, and stylistic preferences. Atlas meticulously quotes real Java method signatures, class names, and file paths (e.g., `src/main/java/com/example/MyClass.java`) directly from the source code, ensuring absolute accuracy. A critical safety feature is the verification of all code samples. Before the `README.md` is finalized, Atlas uses the `bash` tool to execute each Java code snippet or command line instruction presented in the documentation. This might involve compiling a small Java file, running a `Maven` command, or invoking a `JUnit 5 via mvn test` command. This rigorous verification process guarantees that every example provided in the README is functional and reflects the current state of the Java codebase, preventing the common problem of documentation drifting out of sync with the code.
Safety and review for Atlas-generated Java documentation
Atlas prioritizes safety and developer control throughout the documentation process for Java modules, especially in 2026. Every Atlas tool call is permission-gated, and a read-only plan agent drafts a strategy before any changes are made. All proposed edits, including the final `README.md` content, are presented as a unified diff for explicit approval.
Developer control and safety are paramount when Atlas interacts with your Java codebase. All Atlas tool calls, such as `lsp`, `read`, `codebase_search`, `grep`, `write`, and `bash`, are permission-gated, requiring explicit allow, ask, or deny rules. Before any modifications are considered, Atlas's read-only plan agent drafts a detailed strategy for documenting the Java module, which you can review. Only after approval does the build agent proceed. When Atlas proposes changes to your `README.md` or any other file, it computes a unified diff, clearly highlighting every addition, deletion, and modification. This diff is presented for your review and explicit approval before Atlas writes any changes to your file system or stages them for a `git` commit. This robust review mechanism, combined with the ability to snapshot file changes as `git` patches for easy rollback, ensures that you maintain full oversight and control over your Java project's documentation.
Step by step
- 01Initialize Atlas in your Java project: Run `atlas` in a project with a `pom.xml` or `build.gradle`.
- 02Allow Atlas to index your Java codebase: Let Atlas read your packages, classpath, and build configuration, including `Maven` dependencies.
- 03Enumerate the module's public Java API: Use the `lsp` tool's `documentSymbol` operation to list all public classes and methods in your Java module, ensuring no export is missed.
- 04Analyze Java implementation and usage: Employ the `read` tool to examine the implementation of each Java export, then use `codebase_search` to find how callers actually use it in practice across your project.
- 05Identify existing README style: `Grep` your repository for an existing `README.md` file to match its heading structure and tone, ensuring consistency with your Java project's documentation.
- 06Draft the Java module README: Instruct the `write` tool to generate the `README.md`, quoting real Java signatures and file paths from your source code.
- 07Verify Java code samples: Execute every Java code sample within the drafted README with `bash`, confirming its functionality and accuracy before finalization.
- 08Review and approve changes: Review the unified diff of the proposed `README.md` and approve Atlas's changes to your Java module documentation.
Frequently asked questions
- How does Atlas ensure Java documentation is up-to-date?
- Atlas generates documentation directly from the current Java source code using tools like `lsp` and `read`, ensuring it reflects the code's actual state in 2026, not outdated assumptions or historical intent.
- Can Atlas document a Java module that uses Maven?
- Yes, Atlas is designed to work direct with Java codebases managed by `Maven`, reading `pom.xml` files to understand packages, classpaths, and build configurations for accurate documentation.
- How does Atlas verify Java code examples in the README?
- Atlas uses the `bash` tool to execute every Java code sample it includes in the `README.md`, confirming that the examples are functional and accurate before they are written to the file.
- What if my Java project already has a README.md?
- Atlas uses the `grep` tool to find and analyze existing `README.md` files, learning your project's preferred heading structure and tone to ensure new documentation is consistent with your Java project's style.
- Does Atlas invent Java API details for the documentation?
- No, Atlas enumerates the real exported surface of your Java module using the `lsp` tool's `documentSymbol` operation, ensuring every claim is traceable to actual code, not invented interfaces or methods.
- How do I review changes Atlas proposes for my Java README?
- Atlas computes a unified diff for every file edit, including the `README.md`, and surfaces it for your approval before writing, giving you full control over the changes to your Java project's documentation.
- Can Atlas work with JUnit 5 tests in my Java project?
- Yes, Atlas understands the Java testing ecosystem, including `JUnit 5 via mvn test`, and can use test code in `src/test/java` to understand how your module's public API is used in practice.
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