How does Atlas understand my Haskell codebase in CI?

Atlas understands your Haskell codebase by indexing it with AST declarations using tree-sitter, rather than blind line windows. It reads your `.cabal` file or `stack.yaml`, module hierarchy, `default-extensions`, and `build-depends` bounds to reason about type signatures, typeclass instances, and Cabal targets.

What output format does `atlas run` provide for CI pipelines?

`atlas run` provides a machine-readable JSON event stream when invoked with the `--format json` flag. This output is designed for automated parsing by subsequent pipeline steps, allowing programmatic review of Atlas's actions and proposed changes.

How do I prevent Atlas from making unwanted changes in headless mode?

To prevent unwanted changes in headless mode, you must pre-approve all tools Atlas can use (e.g., `bash`, `read`, `edit`, `todowrite`) through its permission configuration. Atlas also drafts a plan in a read-only agent and computes a unified diff for every edit, which can be programmatically reviewed from the JSON output.

Can Atlas generate `hspec` tests for my Haskell modules?

Yes, Atlas can generate `hspec` tests for your Haskell modules. You can prompt it to add an `hspec` suite to a `test-suite` stanza in your `.cabal` file, leveraging its understanding of your module hierarchy and function signatures.

How can I resume a failed Atlas session in my Haskell CI?

You can resume a failed Atlas session in your Haskell CI using `atlas run --continue `. This allows Atlas to pick up exactly where it left off, building on the context of the previous run and avoiding redundant work in your pipeline.

Run Atlas Headless in CI for Haskell Projects in 2026

To run Atlas headless in CI for Haskell projects, invoke `atlas run` with `--format json` to get machine-readable output, enabling automated parsing of events. This allows Atlas to address `cabal` build failures, generate `hspec` test suites, or apply `fourmolu` formatting without human interaction, streamlining your Haskell pipeline in 2026.

How to run Atlas headless in a Haskell CI pipeline?

Running Atlas headless in a Haskell CI pipeline in 2026 is achieved by invoking `atlas run` with the `--format json` flag. This command sends a single prompt, streams events to standard output, and exits when the session goes idle, providing a structured, machine-readable event stream for subsequent pipeline steps.

To integrate Atlas into your Haskell CI workflow, begin by ensuring your project contains a `.cabal` file or `stack.yaml`, which Atlas uses to build its code index. When executing `atlas run` in your CI environment, specify your prompt as an argument. The crucial `--format json` flag ensures that Atlas emits raw event streams, which can be easily parsed by other tools in your pipeline, rather than human-readable prose. For instance, a CI job might execute `atlas run --format json "Refactor the `main` function in `src/MyModule.hs` to eliminate partial functions."`. This non-interactive mode is designed for automation, allowing Atlas to perform tasks like reasoning about your Haskell type signatures, typeclass instances, and Cabal targets without requiring manual input. You must also explicitly set the model using the `provider/model` form, as GitHub paths require this specific format.

Configuring Atlas for Haskell toolchain integration in CI.

Configuring Atlas for Haskell toolchain integration in 2026 involves letting it read your project's `cabal` file and pre-approving necessary tools. Atlas can then leverage its understanding of your module hierarchy, `default-extensions`, and `build-depends` bounds to interact with `cabal`, `hspec`, and `fourmolu` effectively.

Atlas is designed to deeply understand Haskell projects. When it indexes your code, it uses tree-sitter to parse AST declarations, allowing it to reason about specific elements like type signatures and typeclass instances, rather than relying on blind line windows. This enables Atlas to perform tasks such as eliminating a partial function or adding an `hspec` suite to a `test-suite` stanza within your `.cabal` file. For headless CI runs, you must pre-approve the tools Atlas needs through its permission configuration. Tools like `bash`, `read`, `edit`, and `todowrite` are commonly required. For example, Atlas can run `cabal build` to surface GHC type errors, then iterate on the diff until the code typechecks. After making changes, Atlas can apply `fourmolu` to the modified modules, ensuring your Haskell codebase remains consistently formatted before you approve the commit.

Ensuring safety and review for headless Atlas runs in Haskell CI.

Ensuring safety and review for headless Atlas runs in Haskell CI is paramount, especially in 2026, and is managed through permission-gated tool calls and unified diffs. Every Atlas tool call is permission-gated against allow, ask, and deny rules, preventing unauthorized actions in an unattended environment.

In a headless CI environment, there is no human to answer an 'ask' prompt, so pre-approving tools is a critical safety measure. You configure Atlas's permissions to explicitly allow tools like `bash`, `read`, `edit`, and `todowrite` for your CI runs. Before making any changes, Atlas drafts a plan in a read-only plan agent, which can be reviewed if you were running interactively, but in headless mode, it proceeds based on pre-approved permissions. Crucially, Atlas computes a unified diff for every file edit and surfaces it. While a human would typically approve this diff, in a headless setup, the diff is part of the machine-readable JSON output, allowing a subsequent CI step to programmatically review or apply it. Atlas also snapshots file changes as git patches, providing a robust mechanism for diffing edits and rolling back if necessary, adding another layer of safety to automated Haskell development.

Resuming or replaying Atlas sessions in Haskell CI pipelines.

Resuming or replaying Atlas sessions in Haskell CI pipelines is supported by `atlas run` with `--continue`, `--session`, or `--fork` flags, allowing for flexible workflow management in 2026. This capability is invaluable for multi-stage pipelines or debugging, where a job might need to build upon an earlier run's context.

The ability to resume or fork a prior Atlas session is a powerful feature for complex Haskell CI pipelines. If a previous CI step involving Atlas failed or completed partially, you can use `atlas run --continue <session_id>` to pick up exactly where it left off. Alternatively, `atlas run --session <session_id>` allows you to replay a specific session, which can be useful for debugging or re-running a task with slightly different parameters. The `--fork <session_id>` option creates a new session based on an existing one, enabling parallel experimentation or branching off a successful state. These options ensure that your CI pipeline can be resilient and efficient, avoiding redundant work and providing granular control over Atlas's execution within your Haskell development lifecycle. The machine-readable JSON output from `atlas run --format json` will include session IDs, making it straightforward to programmatically manage and reference past sessions.

Step by step

01Ensure your Haskell project includes a `.cabal` file or `stack.yaml` at its root, allowing Atlas to build its code index by AST declarations.
02Configure Atlas's permissions to pre-approve necessary tools like `bash`, `read`, `edit`, and `todowrite` for headless execution, as there is no interactive prompt in CI.
03Invoke `atlas run` in your CI script with your specific prompt and the `--format json` flag, for example: `atlas run --format json "Add an hspec test suite for the `MyModule` functions in `src/MyModule.hs`." `.
04Explicitly set the active model and provider using the `provider/model` format, such as `--model openai/gpt-4o`, as required for headless runs.
05Atlas will read your module hierarchy and language extensions, then run `cabal build` to surface GHC type errors, iterating on proposed diffs until the code typechecks.
06Atlas will apply `fourmolu` to any changed Haskell modules, ensuring consistent code formatting before proposing final edits.
07Parse the machine-readable JSON output from `stdout` in a subsequent CI step to review events, proposed changes, and session status.
08Optionally, use `atlas run --continue <session_id>` or `--fork <session_id>` in a later CI stage to resume or build upon a previous Atlas session.

Frequently asked questions

How does Atlas understand my Haskell codebase in CI?: Atlas understands your Haskell codebase by indexing it with AST declarations using tree-sitter, rather than blind line windows. It reads your `.cabal` file or `stack.yaml`, module hierarchy, `default-extensions`, and `build-depends` bounds to reason about type signatures, typeclass instances, and Cabal targets.
Can Atlas fix `cabal` build errors automatically in CI?: Yes, Atlas can automatically fix `cabal` build errors in CI. It can run `cabal build` to surface GHC type errors, then iterate on the diff until the code typechecks, all within a headless, non-interactive session, provided the necessary tools are pre-approved.
What output format does `atlas run` provide for CI pipelines?: `atlas run` provides a machine-readable JSON event stream when invoked with the `--format json` flag. This output is designed for automated parsing by subsequent pipeline steps, allowing programmatic review of Atlas's actions and proposed changes.
How do I prevent Atlas from making unwanted changes in headless mode?: To prevent unwanted changes in headless mode, you must pre-approve all tools Atlas can use (e.g., `bash`, `read`, `edit`, `todowrite`) through its permission configuration. Atlas also drafts a plan in a read-only agent and computes a unified diff for every edit, which can be programmatically reviewed from the JSON output.
Can Atlas generate `hspec` tests for my Haskell modules?: Yes, Atlas can generate `hspec` tests for your Haskell modules. You can prompt it to add an `hspec` suite to a `test-suite` stanza in your `.cabal` file, leveraging its understanding of your module hierarchy and function signatures.
Does Atlas support `fourmolu` formatting in CI?: Yes, Atlas supports `fourmolu` formatting in CI. After making code changes, Atlas can apply `fourmolu` to the modified modules, ensuring your Haskell codebase adheres to your project's formatting standards before you approve the commit.
How can I resume a failed Atlas session in my Haskell CI?: You can resume a failed Atlas session in your Haskell CI using `atlas run --continue <session_id>`. This allows Atlas to pick up exactly where it left off, building on the context of the previous run and avoiding redundant work in your pipeline.

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