Atlas empowers R developers in 2026 to meticulously plan multi-file changes, such as refactoring dplyr pipelines or updating roxygen2 documentation across a package, and secure review approval *before* a single line of code is modified. This process leverages Atlas's dedicated plan agent, ensuring that testthat suites, renv dependencies, and Air formatting are all considered in the design phase.
How Atlas's Plan Agent Secures R Codebase Changes
Atlas's dedicated plan agent, available in 2026, provides a read-only environment for R developers to design multi-file changes without risk. This agent strictly denies all edit tools for your R source files, allowing modifications only within a designated plan markdown file, typically located under .atlas/plans/*.md.
The core of Atlas's safe planning workflow for R projects lies in its plan agent. This specialized agent is configured with a stringent permission set that explicitly denies any write operations to your R source code, DESCRIPTION files, renv.lock, or tests/testthat/ directories. This means that while you are in plan mode, you cannot accidentally modify a single line of your R package. The only exception is the plan markdown file itself, which Atlas allows you to write to, for instance, at a path like .atlas/plans/my_refactor_plan.md. This read-only constraint ensures that your research and design phase remains entirely separate from implementation, providing a crucial safety net for complex changes that might touch dozens of files across your R package. Atlas's ability to index R code by AST declarations using tree-sitter, rather than blind line windows, further enhances the precision of its read-only analysis, ensuring a deep understanding of your R codebase without the risk of unintended modifications.
How to Research R Codebases with Atlas's Plan Agent
Within Atlas's plan agent, R developers can thoroughly research their codebase using powerful tools like codebase_search, grep, read, and lsp, all while maintaining a strict read-only posture. For instance, you can quickly locate all calls to a specific function across 100s of R files or inspect roxygen2 documentation blocks.
To effectively design a multi-file change in R, comprehensive research is paramount. Atlas's plan agent provides a suite of powerful read-only tools that are fully accessible. You can use codebase_search to semantically find related R functions or variables, leveraging Atlas's hybrid semantic and keyword retrieval fused by reciprocal rank fusion. For example, you might search for all functions that manipulate a data.frame in a specific way, even if they don't share a common name. The grep tool allows for traditional pattern matching across your R files, useful for finding specific string literals or devtools::test() calls within tests/testthat/ files. The read tool lets you inspect the contents of any R source file, DESCRIPTION file, or renv.lock file, providing direct access to code and configuration. Furthermore, the lsp tool exposes language server protocol capabilities, allowing you to query function definitions, usage, and type information for R objects, just as you would in your IDE. This deep introspection, combined with Atlas's AST-based indexing, ensures that your understanding of the R codebase is precise and complete before you commit to a design.
Drafting and Refining Your Multi-File R Change Plan
Once research is complete, R developers use Atlas's plan agent to draft their multi-file change plan into a markdown file, such as .atlas/plans/feature_x_refactor.md. This is the *only* location where the plan agent permits writing, ensuring that your design document is meticulously detailed and ready for review, often spanning 500+ lines for complex refactors.
With a solid understanding of the R codebase, the next step is to articulate your proposed multi-file change. Atlas's plan agent allows you to write your detailed design into a markdown file, for instance, .atlas/plans/update_api_calls.md. This plan should outline the specific R files to be modified, the functions or dplyr pipelines to be refactored, and the expected impact on testthat suites. You might specify changes to R/utils.R, R/data_processing.R, and corresponding updates to tests/testthat/test-utils.R. The plan can detail how renv.lock might need updates for new package dependencies or how roxygen2 documentation blocks will be regenerated. Atlas's ability to read git branches, status, and diffs means you can reference existing code or proposed changes within your plan. The plan agent's read-only nature for source code ensures that your focus remains solely on the design, preventing premature implementation. You can iterate on this plan, refining the strategy for converting a for loop to a purrr pipeline or adding new test_that blocks, until it comprehensively addresses the multi-file change.
Reviewing and Approving Your R Change Plan with Atlas
After drafting a comprehensive multi-file R change plan, Atlas facilitates its review and approval before any code is touched. Using the plan_exit tool, you signal the plan's readiness, prompting Atlas to ask for confirmation to switch to the build agent, a critical step in the 2026 development workflow.
Once your multi-file R change plan, detailing modifications across R/ files and tests/testthat/ directories, is complete and ready for review, you use the plan_exit tool. This action signals to Atlas that the design phase is finished. Atlas will then present a clear prompt: 'Plan at <path> is complete. Would you like to switch to the build agent and start implementing?' This explicit question, powered by the question tool, is a crucial safety gate. If you answer 'No', Atlas raises a Question.RejectedError, keeping you in the plan agent to further refine your design. This ensures that no implementation begins until the plan has received explicit approval, perhaps after a team review of the .atlas/plans/*.md file. Answering 'Yes' direct transitions you to the build agent, which has the necessary permissions to begin modifying your R source code, run devtools::test(), format with Air, and regenerate NAMESPACE with roxygen2. This structured hand-off guarantees that all stakeholders agree on the proposed changes before a single line of R code is altered, minimizing rework and ensuring alignment.
Step by step
- 01Initialize Atlas in your R package directory containing a DESCRIPTION file and an R/ directory.
- 02Switch to Atlas's plan agent to ensure read-only permissions for all R source files and configuration.
- 03Use codebase_search to find relevant R functions, grep for specific patterns in tests/testthat/, and read to inspect renv.lock or R/my_function.R.
- 04Draft your multi-file R change plan in .atlas/plans/my_feature.md, detailing proposed changes to R/, tests/testthat/, and roxygen2 documentation.
- 05Review the plan with your team, ensuring it addresses testthat coverage and renv dependencies.
- 06Execute the plan_exit tool within Atlas, which will prompt you to confirm switching to the build agent.
- 07Answer 'Yes' to the plan_exit prompt to transition to the build agent, enabling code modifications.
- 08Begin implementing the R changes, knowing they align with the approved plan.
Frequently asked questions
- How does Atlas prevent accidental edits to my R code during planning?
- Atlas's plan agent enforces strict permissions, denying all edit tools for R source files, DESCRIPTION, and renv.lock. It only allows writing to the plan markdown file, like .atlas/plans/my_plan.md.
- Can Atlas help me understand my R package's dependencies during planning?
- Yes, you can use the read tool to inspect renv.lock and DESCRIPTION files, and lsp to query package function usage, all within the read-only plan agent.
- What R-specific information should I include in my Atlas plan?
- Detail which R/ files, testthat blocks, roxygen2 documentation, or dplyr pipelines will be affected, and how renv dependencies might change.
- How does Atlas ensure my R plan gets reviewed before I start coding?
- The plan_exit tool explicitly asks for confirmation to switch to the build agent. Answering 'No' keeps you in plan mode, allowing for team review of your .atlas/plans/*.md file.
- Does Atlas understand R's testthat framework during planning?
- Yes, Atlas indexes R code by AST declarations, allowing it to understand testthat blocks and R/ functions, which you can research using codebase_search and grep.
- Can Atlas help me refactor for loops into purrr pipelines in the planning stage?
- While in the plan agent, Atlas helps you *design* such a refactor by researching existing code. The actual conversion would occur in the build agent after plan approval.
- What happens if I reject the plan_exit prompt?
- If you answer 'No' to the plan_exit prompt, Atlas raises a Question.RejectedError, keeping you in the plan agent to continue refining your multi-file R change plan.
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