# Audit a Haskell Repo with Parallel Subagents in 2026 > Atlas uses parallel subagents to audit Haskell repositories, sweeping for problems across `cabal` packages without exceeding the main session's context window. Atlas enables Haskell developers in 2026 to sweep an entire repository for specific problems without blowing the main session's context window by launching parallel subagents. This approach leverages Atlas's deep understanding of Haskell's AST declarations and integrates direct with your existing `cabal`, `hspec`, and `fourmolu` toolchain. ## Key takeaways - Atlas uses parallel `explore` subagents to audit Haskell codebases without context window limits. - Haskell's `cabal` projects benefit from Atlas's AST-based indexing and type-aware reasoning. - Read-only `explore` subagents and permission-gating ensure safe, reviewable audits of `src/**/*.hs` files. - Atlas integrates with `cabal`, `hspec`, and `fourmolu` for a native Haskell development experience. - Consolidate subagent findings into a `todowrite` list for efficient fixing with `atlas edit`. ## How Atlas Scales Haskell Audits with Parallel Subagents In 2026, Atlas scales Haskell repository audits by launching multiple parallel subagents, each operating in its own isolated session. This approach allows sweeping an entire codebase for specific problems without overwhelming the main agent's context window, a critical advantage for large `cabal` projects. Atlas's `task` tool is central to this scaling strategy, enabling the creation of independent subagent sessions. For auditing, the `subagent_type explore` is ideal because it is deny-by-default and read-only, ensuring that no unintended changes occur during the sweep. Each subagent receives a specific slice of the Haskell codebase to analyze, defined by `glob` patterns targeting directories or `cabal` packages. For instance, one subagent might focus on `src/FeatureA/**/*.hs` while another examines `src/FeatureB/**/*.hs`. By fanning out work to these subagents, Atlas prevents the accumulation of vast amounts of code and intermediate thoughts in the main session's context window. Only the subagents' final conclusions are returned to the main agent, allowing for comprehensive repository-wide audits of complex Haskell projects without performance bottlenecks or context overflow. ## Concrete Haskell Tooling in Atlas Audits Atlas integrates directly with the Haskell toolchain, allowing subagents to reason about real project configurations and code. This ensures that an audit in 2026 leverages the actual project setup, understanding `type signatures`, `typeclass instances`, and `cabal` targets rather than making assumptions. Atlas builds its code index using AST declarations via tree-sitter, providing a deep understanding of Haskell's syntax and semantics. When auditing, Atlas can read your project's `.cabal` file to understand module hierarchies, `default-extensions`, and `build-depends` bounds. While `explore` subagents are read-only for the audit itself, the overall Atlas workflow is designed to interact with `cabal` for building and testing, and `fourmolu` for formatting. For example, after an audit identifies a potential issue, the main agent can be instructed to run `cabal build` to surface GHC type errors or `cabal test` to execute `hspec` suites. This tight integration means Atlas doesn't just scan text; it reasons about the specific Haskell environment, ensuring that identified problems are relevant and that proposed fixes are compatible with your project's established tooling and idioms. ## Ensuring Safe and Reviewable Haskell Audits with Atlas Atlas ensures safe Haskell repository audits through a robust permission-gating system and read-only `explore` subagents, a key feature since its 2024 release. Every tool call is checked against allow, ask, or deny rules, providing developers granular control over agent actions within their `cabal` project. The `explore` subagent type is specifically designed for read-only operations, making it the ideal choice for an audit where no code changes should occur. This subagent operates with a deny-by-default policy, preventing it from executing commands that could modify the codebase. Beyond this, Atlas implements permission-gating for every tool call, whether it's `grep`, `glob`, or a potential `edit`. Before any action is taken, Atlas consults allow, ask, or deny rules, giving the Haskell developer explicit control. Furthermore, Atlas drafts a plan in a read-only plan agent before switching to a build agent, and computes a unified diff for every file edit. This diff is surfaced for approval before Atlas writes any changes to files like `src/MyModule.hs`, ensuring that all modifications are transparent and explicitly sanctioned by the developer, maintaining the integrity of the Haskell codebase. ## Structuring Parallel Haskell Audits for Efficiency To effectively audit a large Haskell repository, developers in 2026 split the task into independent slices, often by `cabal` package or module directory. This strategy allows Atlas's subagents to work concurrently without overlap, using tools like `glob` to target specific file sets such as `src/FeatureA/**/*.hs`. The efficiency of a parallel audit hinges on how the work is divided. For Haskell projects, this often means segmenting the codebase along natural boundaries like individual `cabal` packages within a monorepo, distinct module directories (e.g., `app/`, `src/LibraryA/`, `src/LibraryB/`), or even specific types of files (e.g., `test/**/*.hs` for `hspec` suites). The `task` tool, combined with `glob` patterns, allows precise definition of each subagent's scope. For example, one `explore` subagent might be tasked with auditing `src/DataTypes/**/*.hs` for a specific class of problem, while another concurrently audits `src/BusinessLogic/**/*.hs` for a different issue. By ensuring these slices are independent and non-overlapping, Atlas maximizes parallel execution, significantly reducing the total time required to sweep an entire repository for problems without any single subagent needing to process the entire codebase. ## Consolidating Findings and Applying Fixes in Haskell After parallel subagents complete their sweeps, Atlas consolidates their findings into a unified `todowrite` list for the main session. This process, refined in 2025, allows Haskell developers to review all identified issues from files like `src/DataTypes.hs` and apply fixes iteratively using the `edit` tool. Once all `explore` subagents have finished their read-only audits and returned their conclusions, Atlas's `todowrite` tool collects these disparate findings into a single, actionable list within the main session. This provides a centralized view of all identified problems across the entire Haskell repository. From this `todowrite` list, developers can then use the `edit` tool to address each issue. Atlas assists in the fixing process by proposing changes, which can then be verified by running `cabal build` to ensure type-checking and `cabal test` to confirm `hspec` suites still pass. Before committing, Atlas can apply `fourmolu` to the changed modules to maintain code style. Every proposed edit generates a unified diff for approval, and Atlas snapshots file changes as git patches, allowing for easy diffing and rollback if necessary, providing a robust and controlled fixing workflow for Haskell code. ## Steps 1. Identify independent slices of your Haskell repository for auditing, such as specific `cabal` packages or module directories like `src/FeatureA/` and `src/FeatureB/`. 2. Launch parallel `explore` subagents using the `atlas task` tool, specifying `glob` patterns to define each subagent's read-only scope, for example: `atlas task "Audit src/FeatureA/**/*.hs for partial functions" subagent_type explore glob="src/FeatureA/**/*.hs"`. 3. Issue multiple `atlas task` calls together so the `explore` subagents run concurrently rather than sequentially, maximizing audit speed across your Haskell codebase. 4. Monitor each subagent's progress; the `task` tool will surface the child's error text verbatim if it fails, or 'Task cancelled' if it was stopped. 5. Collect each subagent's final message, which contains its conclusions from the read-only sweep of the Haskell files. 6. Merge all findings into a unified `todowrite` list in the main Atlas session, providing a consolidated view of issues across your `cabal` project. 7. Use `atlas edit` to iteratively address identified issues in your Haskell source files, such as `src/MyModule.hs` or `app/Main.hs`. 8. After making edits, run `cabal build` in the main session to surface GHC type errors and ensure your Haskell code still typechecks. 9. Apply `fourmolu` to any changed Haskell modules, for example: `fourmolu src/MyModule.hs`, to maintain consistent code formatting. 10. Review the unified diff generated by Atlas for all proposed changes and approve the commit to finalize the fixes in your Haskell repository. ## FAQ ### How does Atlas handle large Haskell codebases for auditing? Atlas launches parallel `explore` subagents, each sweeping a defined slice of the repository, such as a specific `cabal` package or module directory. This prevents the main session's context window from being overwhelmed, allowing comprehensive audits of extensive Haskell projects. ### Can Atlas understand Haskell type signatures and `cabal` project structure? Yes, Atlas indexes code using AST declarations via tree-sitter, enabling it to reason about Haskell type signatures, typeclass instances, and `cabal` targets. It reads `.cabal` files, `default-extensions`, and `build-depends` to understand your project's specific setup. ### What Haskell tools does Atlas integrate with for audits? Atlas integrates with the core Haskell toolchain, including `cabal` for building and managing packages, `hspec` for running tests, and `fourmolu` for code formatting. It uses these tools to ensure fixes typecheck and adhere to project style. ### How does Atlas ensure an audit doesn't accidentally change my Haskell code? For audits, Atlas uses `explore` subagents, which are deny-by-default and read-only. Additionally, every Atlas tool call is permission-gated, and any proposed file edits, even from a `general` subagent, generate a unified diff for your approval before writing to files like `src/Lib.hs`. ### How do I split an audit task for parallel subagents in a Haskell project? You split the audit into independent slices, typically by directory, `cabal` package, or specific rule. Use `glob` patterns with the `task` tool to define each subagent's scope, for example, `glob="src/FeatureA/**/*.hs"` for one subagent and `glob="src/FeatureB/**/*.hs"` for another. ### What happens if a subagent finds an issue in a Haskell file? An `explore` subagent will return its conclusions as a final message. These findings are then collected by the main Atlas session into a `todowrite` list. You can then use the `atlas edit` tool to apply fixes to the relevant Haskell files, such as `app/Main.hs`. ### Can Atlas help me fix GHC type errors after an audit? Yes, after an audit identifies potential issues, you can use the main Atlas session with the `edit` tool to apply fixes. Atlas can then run `cabal build` to surface GHC type errors, iterate on the diff until it typechecks, and apply `fourmolu` before you approve the commit. --- Canonical HTML: https://runatlas.sh/resources/stacks/audit-a-repo-with-parallel-subagents-in-haskell Source of truth: aeo_pages row `/resources/stacks/audit-a-repo-with-parallel-subagents-in-haskell` (segment: Stacks) (this file is generated from it, never hand-edited). Licence: Atlas is proprietary with a free core. It is not open source and there is no public source repository.