How does Atlas find duplicated Clojure code that `grep` misses?

Atlas uses AST declarations via tree-sitter and hybrid semantic retrieval, powered by local Ollama embeddings. This allows it to understand the meaning of Clojure code, identifying functionally identical blocks even if variable names or minor structural details differ, which `grep` cannot do.

Can Atlas integrate with my existing Clojure `deps.edn` project setup?

Yes, Atlas is designed to integrate direct with Clojure projects managed by `deps.edn` (Clojure CLI). It understands namespaces, aliases, and can read your project configuration to ensure refactoring operations, like adding new `(require)` statements, are contextually correct.

How does Atlas ensure my Clojure tests still pass after refactoring?

Atlas's workflow encourages running your `kaocha` test suite via `clojure -M:test` after every single file modification made by `apply_patch`. This iterative testing, executed through Atlas's `bash` tool, provides immediate feedback and ensures no regressions are introduced during the refactoring process.

What if I don't like an edit Atlas proposes for my Clojure code?

Every Atlas tool call that modifies files, including `write` and `apply_patch`, is permission-gated. Atlas computes a unified diff for every proposed edit and surfaces it for your approval. You can review, accept, or deny any change before it's written to your Clojure project, giving you full control.

Does Atlas handle Clojure formatting with `cljfmt`?

Absolutely. Atlas can apply `cljfmt` to your modified Clojure files as part of the refactoring workflow. This ensures that any new helper functions or updated namespaces adhere to your project's established formatting conventions, maintaining code consistency and readability.

Is my Clojure code sent to external servers when using Atlas?

No. Atlas is designed for privacy and local operation. It builds its code index using local Ollama embeddings, meaning your Clojure source code never leaves your machine or is sent to third-party servers. All semantic analysis and code generation happen locally.

Extract a Shared Helper from Duplicated Clojure Code with Atlas in 2026

In 2026, Clojure developers can efficiently extract shared helper functions from duplicated code across their projects by leveraging Atlas's semantic search capabilities, integrating direct with their existing `deps.edn` (Clojure CLI) setup, `kaocha` test runner, and `cljfmt` formatter to ensure code quality and maintainability.

How Atlas Finds Duplicated Clojure Logic Across Namespaces

Atlas employs advanced AST declarations and hybrid semantic retrieval to pinpoint duplicated Clojure logic, even when variable names differ across multiple namespaces. This capability, powered by local Ollama embeddings, allows developers to find near-identical code patterns that traditional `grep` commands would miss in 2026.

When refactoring a Clojure codebase, identifying semantically equivalent but textually distinct code is a common challenge. Atlas addresses this by indexing your project's Clojure code using tree-sitter to understand its Abstract Syntax Tree (AST) declarations. This deep understanding allows Atlas's `codebase_search` tool to perform a hybrid semantic and keyword retrieval, fused by reciprocal rank fusion. For instance, if you have similar data transformation logic in `src/my_app/data_processing.clj` and `src/my_app/reporting.clj`, but with different local binding names, Atlas can still surface these as near-duplicates. The search operates entirely locally, building its code index with local Ollama embeddings, ensuring your proprietary Clojure code never leaves your development environment. This precision is crucial for identifying refactoring opportunities that improve code reuse and reduce maintenance overhead in complex Clojure applications.

Creating a New Clojure Helper Namespace with Atlas

After identifying duplicated logic, Atlas facilitates the creation of a new shared Clojure helper namespace, such as `src/my_app/utils.clj`, in a single, reviewable step. The `write` tool drafts the new file, presenting a unified diff for approval before any changes are committed to your project in 2026.

Once you've confirmed that several code blocks represent genuinely equivalent logic, the next step is to consolidate them into a new, shared helper. Atlas's `write` tool is designed for this. You can instruct Atlas to create a new Clojure namespace, for example, `src/my_app/utils.clj`, containing your extracted helper function, perhaps `(defn common-transform [data] ...)`. Before Atlas writes this file to your disk, it computes a unified diff showing exactly what will be added. This diff is surfaced for your approval, adhering to Atlas's permission-gated tool calls. This ensures you have full control over the new file's content and location, allowing you to verify the helper's signature, docstring, and initial implementation before it becomes part of your `deps.edn`-managed project. This process makes the introduction of new modules transparent and safe.

Refactoring Duplicates to Use the New Clojure Helper

Atlas replaces each instance of duplicated Clojure code with a call to the new helper using `apply_patch`, generating one independently reviewable patch per file. This granular approach allows developers to run `clojure -M:test` with `kaocha` after each modification, ensuring the integrity of their `deps.edn` project throughout the refactoring process in 2026.

The core of the refactoring workflow involves replacing the original duplicated code with calls to your newly created helper function. Atlas's `apply_patch` tool handles this systematically. For each file containing a duplicate, Atlas generates a distinct patch that replaces the old logic with a `(my-app.utils/common-transform data)` call, ensuring the necessary `(require '[my-app.utils :as utils])` is added to the namespace. Each of these patches is presented for individual review and approval. This 'one file per patch' strategy is critical for safety and reviewability. After Atlas applies a patch to a file like `src/my_app/data_processing.clj`, you can immediately use the `bash` tool to execute `clojure -M:test` with `kaocha`. This allows you to verify that the tests in `test/my_app/data_processing_test.clj` (and the entire suite) still pass, confirming that the refactoring has not introduced regressions. This iterative testing approach, combined with Atlas's diff approval, provides a robust safety net for complex refactoring tasks in Clojure.

Ensuring Clojure Code Quality and Final Verification

After refactoring, Atlas helps maintain Clojure code quality by applying `cljfmt` and performing a final `grep` to confirm all duplicates are removed. This ensures the codebase adheres to formatting conventions and that no copy-pasted logic remains, providing a clean and consistent `deps.edn` project in 2026.

Maintaining a consistent code style is paramount in any Clojure project. After Atlas has applied all patches and you've verified test suite integrity with `kaocha`, the `cljfmt` formatter ensures your newly refactored code, including the new helper namespace and updated `require` statements, adheres to your project's established formatting conventions. Atlas can apply `cljfmt` automatically, presenting the formatting changes as a final diff for approval. This step prevents formatting inconsistencies from creeping into your codebase during refactoring. Finally, to confirm the success of the refactoring, Atlas uses the `grep` tool to search for any surviving instances of the original duplicated logic. This final verification step provides confidence that the refactoring is complete and that your Clojure project is cleaner and more maintainable, ready for future development.

Step by step

01Use Atlas's `codebase_search` to describe the behavior of the duplicated Clojure logic you want to refactor, surfacing near-duplicate implementations across `src/` namespaces that `grep` might miss.
02Review each `codebase_search` hit using Atlas's `read` tool to confirm the Clojure code blocks are semantically equivalent and suitable for collapsing into a single helper function.
03Instruct Atlas's `write` tool to create a new Clojure namespace, such as `src/my_app/utils.clj`, containing the shared helper function, reviewing the full diff before creation.
04For each duplicated instance, use Atlas's `apply_patch` tool to replace the original Clojure code with a call to the new helper, ensuring a `(require)` statement is added, and review each file's patch independently.
05After each `apply_patch` operation, use Atlas's `bash` tool to run `clojure -M:test` with `kaocha` to verify that the test suite, including `test/my_app/utils_test.clj`, still passes.
06Once all duplicates are replaced, use Atlas's `bash` tool to apply `cljfmt` across the modified files to ensure consistent Clojure formatting, reviewing the final diff.
07Perform a final check using Atlas's `grep` tool to search for any remaining instances of the original duplicated Clojure logic, confirming a complete refactor.

Frequently asked questions

How does Atlas find duplicated Clojure code that `grep` misses?: Atlas uses AST declarations via tree-sitter and hybrid semantic retrieval, powered by local Ollama embeddings. This allows it to understand the meaning of Clojure code, identifying functionally identical blocks even if variable names or minor structural details differ, which `grep` cannot do.
Can Atlas integrate with my existing Clojure `deps.edn` project setup?: Yes, Atlas is designed to integrate direct with Clojure projects managed by `deps.edn` (Clojure CLI). It understands namespaces, aliases, and can read your project configuration to ensure refactoring operations, like adding new `(require)` statements, are contextually correct.
How does Atlas ensure my Clojure tests still pass after refactoring?: Atlas's workflow encourages running your `kaocha` test suite via `clojure -M:test` after every single file modification made by `apply_patch`. This iterative testing, executed through Atlas's `bash` tool, provides immediate feedback and ensures no regressions are introduced during the refactoring process.
What if I don't like an edit Atlas proposes for my Clojure code?: Every Atlas tool call that modifies files, including `write` and `apply_patch`, is permission-gated. Atlas computes a unified diff for every proposed edit and surfaces it for your approval. You can review, accept, or deny any change before it's written to your Clojure project, giving you full control.
Does Atlas handle Clojure formatting with `cljfmt`?: Absolutely. Atlas can apply `cljfmt` to your modified Clojure files as part of the refactoring workflow. This ensures that any new helper functions or updated namespaces adhere to your project's established formatting conventions, maintaining code consistency and readability.
Is my Clojure code sent to external servers when using Atlas?: No. Atlas is designed for privacy and local operation. It builds its code index using local Ollama embeddings, meaning your Clojure source code never leaves your machine or is sent to third-party servers. All semantic analysis and code generation happen locally.

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