How does Atlas run a single Zig test?

Atlas uses its `bash` tool to execute `zig build test` with the `--test-filter` flag, targeting only the specified test to minimize output and focus debugging efforts.

Can Atlas understand Zig's `comptime` and allocators?

Yes, Atlas indexes Zig code by AST declarations using tree-sitter, allowing it to understand `comptime` blocks, explicit allocators, and the overall architecture of a Zig project.

How does Atlas ensure my Zig code changes are safe?

Atlas drafts plans in a read-only agent, permission-gates all tool calls, and presents a unified diff for approval before writing any changes to your Zig files, ensuring full control.

Does Atlas use `zig fmt` to maintain code style?

Yes, after making code changes, Atlas can run `zig fmt` on the touched files to ensure adherence to Zig's formatting conventions and maintain codebase consistency.

Can Atlas add dependencies to my Zig project?

Yes, Atlas can add dependencies using `zig fetch --save` and wire them into `build.zig`, then present the `.zon` diff for your review and approval.

What if I need to add temporary logging to debug a Zig test?

Atlas can use its `edit` tool to insert `std.debug.print` statements into your Zig source code for temporary debugging, and then remove them after the issue is resolved.

How does Atlas handle large code changes in Zig?

For changes spanning several hunks, Atlas can use its `apply_patch` tool, which is designed for more robust and comprehensive modifications than chaining multiple `edit` commands.

Can Atlas commit my Zig code changes after a fix?

Yes, Atlas reads git branches, status, and diffs, and can stage and create commits on your behalf after you have reviewed and approved the proposed changes.

Debug a Single Failing Test in Zig with Atlas in 2026

Atlas empowers Zig developers in 2026 to debug a single failing test by leveraging the native Zig toolchain, including `zig build test`, and Atlas's intelligent code navigation and editing capabilities. This workflow focuses on identifying the root cause within the production code, not merely adjusting assertions.

How Atlas isolates a failing Zig test with `zig build test`

Atlas in 2026 uses its `bash` tool to run `zig build test` with specific filters, allowing developers to isolate a single failing test. This approach mirrors a manual debugging process, ensuring the output is concise and directly relevant to the problem at hand.

When a Zig test fails, the first step is to isolate it. Atlas achieves this by using its `bash` tool to execute the `zig build test` command with the `--test-filter` flag. For example, `atlas bash "zig build test --test-filter my_failing_test"` will run only the specified test. This capability is crucial for reducing noise and focusing on the specific failure. Atlas reads the output from `zig build test` to understand the assertion failure and the context provided by the Zig test runner. This direct interaction with the Zig toolchain ensures that Atlas operates within the familiar and expected environment of a Zig developer, providing a concrete and specific debugging experience.

Navigating Zig code with Atlas's LSP and AST indexing

Atlas indexes Zig code by AST declarations using tree-sitter, not blind line windows, allowing precise navigation through `comptime` blocks and explicit allocators in 2026. This deep understanding of Zig's structure is vital for effective debugging.

After isolating a failing test, Atlas leverages its advanced code indexing, built on tree-sitter, to understand the Zig codebase. This allows Atlas to navigate complex Zig idioms like `comptime` blocks and explicit allocators with precision. Using the `lsp` tool, Atlas can perform operations like `goToDefinition` to jump from a failing assertion in a test to the exact function or variable definition in the production code it exercises. Subsequently, `findReferences` helps trace the call graph, revealing how data flows through different functions and modules. This detailed code exploration is essential for understanding the context of the bug, especially in Zig projects where `build.zig` and custom allocators are integral to the architecture.

Forming and testing hypotheses in Zig with Atlas's `edit` tool

To form a hypothesis in 2026, Atlas can add temporary logging to Zig source files using its `edit` tool, or re-run `zig build test` with verbose flags. This iterative process helps confirm or refute theories about the bug's origin.

Once Atlas has navigated the relevant Zig code, it can form a hypothesis about the bug's cause. To test this hypothesis, Atlas can use its `edit` tool to insert temporary `std.debug.print` statements directly into the Zig source code. This allows for runtime inspection of variable values or execution paths. Alternatively, Atlas can re-run `zig build test` via its `bash` tool with additional verbose flags, if the test runner supports them, to gather more diagnostic information. This ability to quickly modify code, run tests, and observe results is a core part of the debugging loop, enabling Atlas to iterate on solutions efficiently and concretely within the Zig environment.

Applying fixes and ensuring Zig code quality with `zig fmt`

Atlas computes a unified diff for every file edit and surfaces it for approval before writing, ensuring code quality and developer oversight in 2026. After fixing, Atlas runs `zig fmt` to maintain style consistency.

When the root cause of the failing Zig test is identified, Atlas proceeds to fix the production code. For minor, targeted changes, Atlas uses its `edit` tool. If the fix involves more extensive modifications spanning several hunks, Atlas can utilize `apply_patch` for a more robust and less brittle application of changes. Before any changes are written to disk, Atlas computes a unified diff and presents it to the developer for approval, ensuring full transparency and control. After applying the fix, Atlas re-runs the single failing test, then the entire `zig build test` suite to confirm the bug is resolved and no regressions were introduced. Finally, Atlas ensures code style consistency by running `zig fmt` on all touched files, adhering to Zig's community standards.

Atlas's safety and review mechanisms for Zig development

Every Atlas tool call is permission-gated against allow, ask, and deny rules before it runs, providing a secure and controlled debugging experience for Zig developers in 2026. This includes `zig build test` and `zig fmt` commands.

Atlas is designed with developer safety and control as paramount concerns. Before executing any action, Atlas drafts a comprehensive plan in a read-only plan agent and seeks explicit approval. All tool calls, whether it is `bash` to run `zig build test`, `lsp` to navigate code, or `edit` to modify Zig source files, are permission-gated. This means a Zig developer must explicitly allow, ask for confirmation, or deny any operation. Furthermore, Atlas computes a unified diff for every proposed file edit and presents it for review. This allows developers to scrutinize every change before it is applied, ensuring that Atlas's actions align perfectly with their intentions and maintain the integrity of their Zig codebase.

Step by step

01Ask Atlas to run just the failing Zig test: `atlas bash "zig build test --test-filter <test_name>"`
02Instruct Atlas to read the test file and the module it exercises: `atlas read <test_file.zig>` and `atlas read <module_file.zig>`
03Use Atlas's LSP tool to trace the call graph from the test to the production code: `atlas lsp goToDefinition <symbol>` then `atlas lsp findReferences <symbol>`
04Have Atlas add temporary `std.debug.print` logging to form a hypothesis: `atlas edit <file.zig> --insert "std.debug.print(\"Debug value: {any}\n\", .{my_variable});"`
05Re-run the single Zig test with Atlas to check the hypothesis: `atlas bash "zig build test --test-filter <test_name>"`
06Approve Atlas's proposed fix to the production Zig code: `atlas edit <file.zig> --replace "old_code" "new_code"` (or `atlas apply_patch` for larger changes)
07Verify the fix by running the single test, then the full `zig build test` suite: `atlas bash "zig build test --test-filter <test_name>"` followed by `atlas bash "zig build test"`
08Ask Atlas to remove any temporary `std.debug.print` logging: `atlas edit <file.zig> --delete "std.debug.print(\"Debug value: {any}\n\", .{my_variable});"`
09Ensure Zig formatting consistency on touched files: `atlas bash "zig fmt <file.zig>"`

Frequently asked questions

How does Atlas run a single Zig test?: Atlas uses its `bash` tool to execute `zig build test` with the `--test-filter` flag, targeting only the specified test to minimize output and focus debugging efforts.
Can Atlas understand Zig's `comptime` and allocators?: Yes, Atlas indexes Zig code by AST declarations using tree-sitter, allowing it to understand `comptime` blocks, explicit allocators, and the overall architecture of a Zig project.
How does Atlas ensure my Zig code changes are safe?: Atlas drafts plans in a read-only agent, permission-gates all tool calls, and presents a unified diff for approval before writing any changes to your Zig files, ensuring full control.
Does Atlas use `zig fmt` to maintain code style?: Yes, after making code changes, Atlas can run `zig fmt` on the touched files to ensure adherence to Zig's formatting conventions and maintain codebase consistency.
Can Atlas add dependencies to my Zig project?: Yes, Atlas can add dependencies using `zig fetch --save` and wire them into `build.zig`, then present the `.zon` diff for your review and approval.
What if I need to add temporary logging to debug a Zig test?: Atlas can use its `edit` tool to insert `std.debug.print` statements into your Zig source code for temporary debugging, and then remove them after the issue is resolved.
How does Atlas handle large code changes in Zig?: For changes spanning several hunks, Atlas can use its `apply_patch` tool, which is designed for more robust and comprehensive modifications than chaining multiple `edit` commands.
Can Atlas commit my Zig code changes after a fix?: Yes, Atlas reads git branches, status, and diffs, and can stage and create commits on your behalf after you have reviewed and approved the proposed changes.

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