How does Atlas ensure new R tests match my project's testthat style?

Atlas uses its `grep` tool to scan your `tests/testthat/` directory for existing test files. It analyzes the structure, naming conventions, and import styles of your current `test_that` blocks. This allows Atlas to generate new `testthat` specifications that direct integrate with your R project's established testing practices, ensuring consistency and ease of review.

What R commands does Atlas use to run testthat tests?

Atlas leverages the `bash` tool to execute the standard R command `devtools::test()`. This command runs all `test_that` blocks within your `tests/testthat/` directory. Atlas presents the output from `devtools::test()` and allows you to iterate on test failures using its `edit` tool until your R test suite is green.

Can Atlas handle R package dependencies managed by renv when writing tests?

Yes, Atlas is designed to work within R package environments. It reads your `DESCRIPTION` file and the `renv.lock` file to understand and respect your project's package dependencies. This ensures that when Atlas runs `devtools::test()`, all necessary R packages are correctly managed and available, preventing dependency-related issues during test execution.

How does Atlas ensure I approve changes before they are written to my R files?

Atlas employs a robust permission-gated system. When it drafts new `testthat` code using its `write` tool, it first computes a unified diff of the proposed changes. This diff is presented to you for explicit approval before any modifications are written to your R files in `tests/testthat/`. This allows you to review every `test_that` block and assertion.

What if my R module is very large and needs many new tests?

For large R modules requiring extensive testing, Atlas can help manage the workflow. It allows you to use a `todowrite` list to keep track of pending test creation tasks. This feature helps break down the work into manageable chunks, ensuring that all public R functions eventually receive comprehensive `testthat` coverage without overwhelming the developer.

Does Atlas format the R code it writes for testthat?

Yes, after generating or modifying `testthat` files, Atlas can format the changed R code. It uses the `Air` formatter, which is a standard tool in the R ecosystem, to ensure that all new `test_that` blocks and R code adhere to your project's formatting standards. This step can be performed behind a permission prompt before Atlas commits the changes.

How does Atlas identify which R functions need tests?

Atlas uses a precise method to identify R functions for testing. It first `read`s the R source files, typically in the `R/` directory. Then, it employs the `lsp` tool with its `documentSymbol` operation, which leverages AST declarations, to enumerate all exported symbols. This ensures that every public function or object within your R package is considered for `testthat` coverage.

Write unit tests for untested code in R with Atlas in 2026

In 2026, R developers leverage Atlas to efficiently add `testthat` unit tests to previously untested code modules, ensuring robust code quality by matching existing repository conventions. Atlas integrates directly with the R toolchain, reading `DESCRIPTION` files and `renv.lock` for package dependencies, then generating `test_that` blocks within `tests/testthat/` directories. It uses the `bash` tool to execute `devtools::test()` behind a permission prompt, providing a verified workflow for bringing comprehensive test coverage to R packages.

How Atlas identifies R code for testing

Atlas in 2026 identifies R code for testing by first reading the `DESCRIPTION` file and then enumerating exported symbols. This process ensures that every public function within an R package, typically located in the `R/` directory, is considered for test coverage.

Atlas begins its workflow by using the `read` tool to ingest the target R module's source code. For R packages, this involves parsing files within the `R/` directory. Following this, Atlas employs the `lsp` tool with its `documentSymbol` operation to precisely enumerate all exported symbols. This method, which leverages AST declarations indexed by tree-sitter, guarantees that no public function or object within the R package is overlooked when generating new `testthat` test specifications. This detailed understanding of the R codebase is fundamental to creating comprehensive and accurate unit tests.

Adopting existing testthat conventions with Atlas

To ensure new `testthat` files direct integrate, Atlas in 2026 first `grep`s the repository for existing test conventions. This step allows Atlas to replicate the specific framework, import styles, and naming patterns already established in `tests/testthat/` directories.

A critical aspect of adding tests to an existing R project is maintaining consistency. Atlas achieves this by using the `grep` tool to search for existing `testthat` files within the `tests/testthat/` directory. This search helps Atlas understand the repository's established testing framework, including how `test_that` blocks are structured, common helper functions are imported, and test files are named (e.g., `test-my_function.R`). By copying these conventions, Atlas ensures that any new test files it generates, such as `tests/testthat/test-new_module.R`, will match the project's existing style, making them indistinguishable from manually written tests and easier for R developers to review.

Writing new testthat specs and reviewing changes

Atlas in 2026 drafts new `testthat` specifications using its `write` tool, presenting a unified diff for approval before any changes are committed. This ensures R developers have full control over the `test_that` blocks and assertions added to `tests/testthat/` files.

Once Atlas has identified the R functions to test and understood the repository's `testthat` conventions, it proceeds to write the new test specification file. Using the `write` tool, Atlas generates `test_that` blocks and appropriate assertions, placing them in a new file like `tests/testthat/test-my_module.R`. Before any changes are written to disk, Atlas computes a unified diff for every file edit. This diff is surfaced for approval, allowing the R developer to review the proposed `testthat` code, ensuring its correctness and adherence to R idioms. This permission-gated process, where Atlas drafts a plan in a read-only agent and asks for approval, provides a robust safety mechanism.

Executing R testthat suites with Atlas

Atlas in 2026 executes the R `testthat` suite using the `bash` tool, specifically running `devtools::test()` to verify new tests. This direct execution ensures that any newly written `test_that` blocks are functional and correctly identify issues within the R codebase.

A test that is never executed is not a test. Atlas understands this fundamental principle and, after writing the new `testthat` spec, immediately proceeds to run the entire test suite. It uses the `bash` tool to execute the R command `devtools::test()`, which in turn runs all `test_that` blocks found in the `tests/testthat/` directory. This execution happens behind a permission prompt, giving the R developer explicit control. If the output from `devtools::test()` exceeds 2000 lines or 50 KB, Atlas truncates it in the terminal but saves the full log to a file for detailed review. This iterative process of writing and running tests is crucial for achieving a green test suite.

Iterating on R tests and managing dependencies

Atlas in 2026 facilitates iterative test development for R modules, using the `edit` tool to refine `testthat` blocks until the suite is green. It also respects `renv.lock` for dependency management, ensuring a stable testing environment.

Achieving a fully passing `testthat` suite often requires iteration. Atlas supports this by allowing R developers to use the `edit` tool to refine the newly written `test_that` blocks based on the output from `devtools::test()`. For large R modules, Atlas can maintain progress in a `todowrite` list, ensuring all identified testing tasks are completed. Furthermore, Atlas is designed to work direct within R package environments managed by `renv`. It reads the packages locked in `renv.lock` and respects the `DESCRIPTION` file, ensuring that the testing environment is consistent and that all necessary dependencies for running `devtools::test()` are correctly managed, preventing common R dependency issues during test execution.

Step by step

01Atlas `read`s the R module under test, typically files in the `R/` directory, to understand its structure and functions.
02Atlas uses the `lsp` tool's `documentSymbol` operation to enumerate all exported R symbols, ensuring no public function is missed for `testthat` coverage.
03Atlas `grep`s the `tests/testthat/` directory for an existing `testthat` file to copy the repository's framework, import style, and naming convention.
04Atlas `write`s the new `testthat` spec file, such as `tests/testthat/test-new_feature.R`, showing a unified diff for approval before writing to disk.
05Atlas uses the `bash` tool to run the R test suite with `devtools::test()`, executing all `test_that` blocks and reading the failures.
06Atlas `edit`s the `testthat` files iteratively until the `devtools::test()` suite is green, using a `todowrite` list for large R modules.
07Atlas can format the changed R files with `Air` and regenerate `NAMESPACE` with `roxygen2` before committing.

Frequently asked questions

How does Atlas ensure new R tests match my project's testthat style?: Atlas uses its `grep` tool to scan your `tests/testthat/` directory for existing test files. It analyzes the structure, naming conventions, and import styles of your current `test_that` blocks. This allows Atlas to generate new `testthat` specifications that direct integrate with your R project's established testing practices, ensuring consistency and ease of review.
What R commands does Atlas use to run testthat tests?: Atlas leverages the `bash` tool to execute the standard R command `devtools::test()`. This command runs all `test_that` blocks within your `tests/testthat/` directory. Atlas presents the output from `devtools::test()` and allows you to iterate on test failures using its `edit` tool until your R test suite is green.
Can Atlas handle R package dependencies managed by renv when writing tests?: Yes, Atlas is designed to work within R package environments. It reads your `DESCRIPTION` file and the `renv.lock` file to understand and respect your project's package dependencies. This ensures that when Atlas runs `devtools::test()`, all necessary R packages are correctly managed and available, preventing dependency-related issues during test execution.
How does Atlas ensure I approve changes before they are written to my R files?: Atlas employs a robust permission-gated system. When it drafts new `testthat` code using its `write` tool, it first computes a unified diff of the proposed changes. This diff is presented to you for explicit approval before any modifications are written to your R files in `tests/testthat/`. This allows you to review every `test_that` block and assertion.
What if my R module is very large and needs many new tests?: For large R modules requiring extensive testing, Atlas can help manage the workflow. It allows you to use a `todowrite` list to keep track of pending test creation tasks. This feature helps break down the work into manageable chunks, ensuring that all public R functions eventually receive comprehensive `testthat` coverage without overwhelming the developer.
Does Atlas format the R code it writes for testthat?: Yes, after generating or modifying `testthat` files, Atlas can format the changed R code. It uses the `Air` formatter, which is a standard tool in the R ecosystem, to ensure that all new `test_that` blocks and R code adhere to your project's formatting standards. This step can be performed behind a permission prompt before Atlas commits the changes.
How does Atlas identify which R functions need tests?: Atlas uses a precise method to identify R functions for testing. It first `read`s the R source files, typically in the `R/` directory. Then, it employs the `lsp` tool with its `documentSymbol` operation, which leverages AST declarations, to enumerate all exported symbols. This ensures that every public function or object within your R package is considered for `testthat` coverage.

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