How does Atlas prevent context window overflow when auditing large MATLAB repos?

Atlas prevents context window overflow by fanning out work to parallel subagents. Each subagent runs in its own session, processing a specific slice of the MATLAB codebase, and only its conclusions return to the main session.

Can Atlas modify my MATLAB code during an audit?

By default, for audits, Atlas uses the `explore` subagent type, which is deny-by-default and read-only, ensuring no modifications are made to your MATLAB .m files or classdef blocks.

How does Atlas ensure safety when running commands in MATLAB?

Atlas ensures safety by permission-gating every tool call against allow, ask, and deny rules. It drafts a plan in a read-only agent and asks for approval before executing any commands or writing to MATLAB files.

What MATLAB tools does Atlas integrate with for auditing?

Atlas integrates with core MATLAB concepts like .m function files, classdef blocks, and `matlab.unittest` test classes. It can also prompt to run `runtests` and apply `MATLAB Format Code` conventions.

How do I review the findings from multiple parallel MATLAB audit subagents?

Atlas collects the final message from each subagent, including any error text. These findings are then merged into a single `todowrite` list in your main Atlas session for consolidated review and action.

Can Atlas audit specific parts of my MATLAB project, like a +package folder?

Yes, Atlas allows you to split your MATLAB project into independent slices, such as specific directories like `src/`, `tests/`, or `+package` folders, enabling subagents to focus on targeted audits.

What happens if a subagent fails during a MATLAB audit?

If a subagent fails during a MATLAB audit, the `task` tool surfaces the child's error text verbatim, allowing you to diagnose and address the specific issue.

Audit a repo with parallel subagents in MATLAB with Atlas in 2026

Atlas enables MATLAB developers in 2026 to sweep an entire repository for a class of problems without blowing the main session's context window by fanning out work to parallel subagents. These subagents operate on .m files and classdef blocks, leveraging tools like matlab.unittest (runtests) and MATLAB Format Code for comprehensive, isolated audits.

How Atlas Audits MATLAB Repositories with Parallel Subagents

Atlas audits MATLAB repositories by launching multiple subagents in parallel, each focusing on a distinct slice of the codebase. This approach, available in 2026, prevents the main session's context window from being overwhelmed, allowing for a comprehensive sweep of .m files and classdef blocks.

Atlas streamlines auditing MATLAB repositories by fanning out work to multiple subagents, each operating in its own isolated session. This prevents the main Atlas session's context window from being overwhelmed, a critical advantage when sweeping large codebases containing numerous .m function files and classdef blocks. The `task` tool is central to this, launching subagents that can be configured as `explore` types for read-only operations. This read-only nature is ideal for initial audits where the goal is to identify problems without making any changes. Atlas leverages its ability to search code with hybrid semantic and keyword retrieval, fused by reciprocal rank fusion, to help subagents efficiently locate relevant sections within the MATLAB project structure. The code index, built by AST declarations using tree-sitter, ensures precise targeting of function signatures and class definitions, rather than relying on blind line windows.

How to Split MATLAB Codebases for Parallel Audits

To effectively audit a MATLAB repository, split the codebase into independent slices, such as by directory or matlab.unittest test package. This ensures subagents do not overlap, allowing 5 or more parallel tasks to run concurrently without contention, each focusing on specific .m files.

Effective parallel auditing in MATLAB requires a strategic division of the codebase. Instead of a monolithic sweep, the repository is split into independent slices. Common strategies include segmenting by directory, such as `src/` for core logic and `tests/` for `matlab.unittest` test classes, or by MATLAB's package structure, like `+myPackage/`. This ensures that each subagent has a distinct, non-overlapping scope. For instance, one subagent might focus on `grep`ing for specific patterns within `src/**/*.m` files, while another examines `tests/**/*.m` for outdated `matlab.unittest.TestCase` subclasses. Atlas's `glob` tool is instrumental here, allowing precise selection of file paths for each subagent's task, ensuring that 2 or more subagents can run concurrently without stepping on each other's findings.

Launching Read-Only MATLAB Audit Tasks with Atlas

Atlas launches read-only audit tasks using the `explore` subagent type, ensuring no changes are made to your MATLAB codebase. This is crucial for initial sweeps in 2026, where the goal is to identify problems in .m files or classdef blocks without modifying them, using the `task` tool.

To initiate a read-only audit in MATLAB, the `task` tool is used with the `subagent_type explore` flag. This configuration ensures that the subagent operates in a deny-by-default, read-only mode, making it the ideal choice for sweeping a repository for issues without any risk of accidental modification. For example, a developer might issue `atlas task --subagent_type explore --name "Check for deprecated functions in src" "grep -r 'deprecatedFunction' src/**/*.m"` and concurrently `atlas task --subagent_type explore --name "Review test setup in tests" "grep -r 'setupOnce' tests/**/*.m"`. By issuing these `task` calls together, Atlas fans out the work, allowing them to run in parallel background sessions. This concurrency significantly reduces the total audit time compared to sequential execution, providing findings from multiple parts of the MATLAB codebase simultaneously.

Reviewing and Merging MATLAB Audit Findings

After parallel subagents complete their sweeps of MATLAB .m files, Atlas collects each subagent's final message, including any error text. This process, typically involving 3 to 7 subagents, consolidates findings into a unified `todowrite` list for efficient review and subsequent fixes in the main session.

Once the parallel subagents have completed their designated sweeps of MATLAB .m files and classdef blocks, Atlas automatically collects their conclusions. The `task` tool is designed to surface each child subagent's final message directly. If a subagent encounters an issue or fails, its error text is presented verbatim, providing immediate insight into the problem. If a task was cancelled, "Task cancelled" is clearly indicated. These individual findings are then merged into a unified `todowrite` list within the main Atlas session. This consolidated list allows the MATLAB developer to review all identified problems, such as potential issues in `buildfile.m` or non-compliant `MATLAB Format Code` sections, in one place. The `edit` tool can then be used in the main session to systematically address each item.

Ensuring Safety and Permissions in MATLAB Audits

Atlas implements robust safety mechanisms to protect your MATLAB codebase during any audit or modification process. Every Atlas tool call is permission-gated against allow, ask, and deny rules, ensuring 100% control over changes to .m files.

Atlas implements robust safety mechanisms to protect your MATLAB codebase during any audit or modification process. Every Atlas tool call, including those that might interact with .m files or `buildfile.m`, is permission-gated against allow, ask, and deny rules. Before any potential change, Atlas drafts a comprehensive plan in a read-only plan agent. This plan, detailing proposed actions, is then presented to the user for explicit approval. Only after approval does Atlas switch to a build agent to execute the plan. Furthermore, for every file edit, Atlas computes a unified diff and surfaces it for approval before writing, ensuring 100% transparency and control. This meticulous process, combined with the `explore` subagent's deny-by-default, read-only nature for audits, provides unparalleled confidence when working with your MATLAB projects. Atlas also snapshots file changes as git patches, allowing edits to be easily diffed and rolled back if needed.

Step by step

01Initialize Atlas in your MATLAB project root: Run `atlas` in the folder containing your .m files and `buildfile.m` to allow it to index function signatures and `classdef` blocks.
02Define audit slices for your MATLAB codebase: Split your repository into logical units, such as `src/`, `tests/`, or specific `+package` directories, to assign distinct audit scopes to subagents.
03Launch parallel read-only audit tasks: Use the `task` tool with `subagent_type explore` for each slice, issuing calls together to run concurrently, for example: `atlas task --subagent_type explore --name "Audit src" "grep -r 'TODO' src/"` and `atlas task --subagent_type explore --name "Audit tests" "grep -r 'FIXME' tests/"`.
04Collect and review subagent conclusions: Atlas automatically surfaces each subagent's final message, including verbatim error text if a task fails, or "Task cancelled" if interrupted.
05Merge findings into a `todowrite` list: Consolidate the identified issues from all subagents into a single `todowrite` list within your main Atlas session.
06Address issues in the main session: Use the `edit` tool in your main Atlas session to fix the identified problems, applying `MATLAB Format Code` conventions to touched files before approval.
07Approve and commit changes: Review the unified diff for every file edit and approve changes. Atlas can then stage and create commits on your behalf, snapshotting file changes as git patches for rollback.

Frequently asked questions

How does Atlas prevent context window overflow when auditing large MATLAB repos?: Atlas prevents context window overflow by fanning out work to parallel subagents. Each subagent runs in its own session, processing a specific slice of the MATLAB codebase, and only its conclusions return to the main session.
Can Atlas modify my MATLAB code during an audit?: By default, for audits, Atlas uses the `explore` subagent type, which is deny-by-default and read-only, ensuring no modifications are made to your MATLAB .m files or classdef blocks.
How does Atlas ensure safety when running commands in MATLAB?: Atlas ensures safety by permission-gating every tool call against allow, ask, and deny rules. It drafts a plan in a read-only agent and asks for approval before executing any commands or writing to MATLAB files.
What MATLAB tools does Atlas integrate with for auditing?: Atlas integrates with core MATLAB concepts like .m function files, classdef blocks, and `matlab.unittest` test classes. It can also prompt to run `runtests` and apply `MATLAB Format Code` conventions.
How do I review the findings from multiple parallel MATLAB audit subagents?: Atlas collects the final message from each subagent, including any error text. These findings are then merged into a single `todowrite` list in your main Atlas session for consolidated review and action.
Can Atlas audit specific parts of my MATLAB project, like a +package folder?: Yes, Atlas allows you to split your MATLAB project into independent slices, such as specific directories like `src/`, `tests/`, or `+package` folders, enabling subagents to focus on targeted audits.
What happens if a subagent fails during a MATLAB audit?: If a subagent fails during a MATLAB audit, the `task` tool surfaces the child's error text verbatim, allowing you to diagnose and address the specific issue.

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