Analogues of Claude Code: terminal agent, editor with model and add-on in IDE

What does this solve?

Analogs Claude Code It is wise to choose based on one feature that is not immediately visible: who in the group runs the commands and reads their output. On this basis, tools are divided into three classes - a terminal agent, an editor with a built-in model, and an addition to someone else's IDE - and within a class they are more similar than between classes. A comparison like “Cursor vs. Claude Code” goes across the axes and therefore rarely leads to a solution. The cost of a mistake is measured not by a subscription, but by a month of work in a tool that does not do what you bought it for.

How it works

Class 1. Terminal agent

Examples: Claude Code, OpenAI Codex CLI, Gemini CLI, Aider, OpenCode.

Lives in a shell. Work cycle: received a task - read the files - changed - ran a test, linter or build - read the output - corrected. The key here is that the commands are executed by the tool itself and read the result itself, so the chain goes without a person in the middle.

Mechanical consequences:

• The interface is text, which means the tool can be called from CI, via SSH, from cron, from a script;
• project is visible as a file system and git, not as editor index: work grep, find, git log, make;
• multi-file visits happen naturally - renaming throughout the repository, API migration, editing hundreds of templates;
• everything that the shell can do, the tool can too, including dangerous things. Rights are limited from the outside.

Class 2. Editor with built-in model

Examples: Cursor, Windsurf, Zed.

An entire editor with a model built into its core: project index, auto-completion as you type, editing the selected piece on the spot, chat with links to files, agent mode inside the window. Edits are shown as diff and applied by button.

Mechanical consequences:

• shortest loop on minor edits - highlighted, asked, accepted;
• the person remains in the loop at every step, which is good for control and bad for long autonomous runs;
• project index speeds up answers to “where is it” questions;
• The tool is inseparable from the editor: leaving it means losing the tool along with your habits and hotkeys.

Class 3. IDE Supplement

Examples: GitHub Copilot, Continue, Cline, JetBrains AI Assistant.

Plugin for someone else's editor - VS Code, JetBrains, Vim. It works inside the host extension API: what the editor gives to the plugin, the plugin can do - buffer, selection, sometimes terminal and file operations.

Mechanical consequences:

• The familiar editor and corporate standard remain in place, no need to relearn;
• The depth of capabilities is set by the owner, and the same plugin behaves differently in different IDEs;
• autonomy is usually lower: the “corrected - checked” loop is often closed by a person.

Axis comparison

The data line is checked according to the policy of a specific product: where the index is stored, how long queries last, whether the code is included in training. Under NDA, this is the first question, not the last.

The classes are not mutually exclusive

Auto-completion from the IDE add-on and the terminal agent for multi-file calls work smoothly in the same repository. The conflict arises not between tools, but in the working tree: two agents editing the same files at the same time produce a difference that no one can understand later. Breed by branches or by time.

How to connect

The test run for all three classes takes place in one evening.

1. Take a reference problem from your repository. Not “write a function”, but “find the reason why test X failed and fix it”, where the readiness criterion is a green run. The task must require reading someone else's code.
2. Terminal class: set the CLI as specified for a specific tool (usually npm i -g <пакет> or installer), run from the root of the repository, give access to read and run tests, run the task.
3. Editor: open the same repository, wait for indexing, run the same task in agent mode.
4. Addition: install the plugin in your IDE, grant access, run the same task.
5. Keys and accounts - in the secrets manager, in the process through environment variables. Not a file in the repository and not in the settings that are committed.
6. Permissions are set equally strictly everywhere: a separate branch, pushing is prohibited, tests are allowed, deployment is prohibited.
7. For each run, write down three numbers: how many times you had to intervene, how many extra files were in the diff, how many runs before the green light.

Useful scripts

• Mass editing of hundreds of files - renaming, API migration, template updating: terminal agent.
• Spot edit inside a function with auto-completion and instant diff: editor with model.
• Night run, MR review, scheduled report: terminal agent in headless mode.
• Corporate IDE standard that cannot be changed: addition.
• Working via SSH on a server without graphics: only the terminal class.
• Unfamiliar repository, a review is needed before editing: an editor with an index or a terminal agent with a read-only scout.
• A student or new employee who needs to see every step: an editor or an addition, where editing takes place through a person's eyes.

Limitations

Terminal agent. There is no visual analysis of the diff piece by piece - you have to accept or roll back through git. More expensive in terms of tokens: files are read in their entirety, the accumulated context is re-sent at each step. It's easy to give out unnecessary rights and get an action you didn't expect. Requires problem formulation skills: a vague formulation is worked out literally and to the end.

Editor with model. Linking to a specific editor with all its habits. The project index goes to the service side, which is subject to NDA and internal policies. Long autonomous chains perform worse than the terminal class, because a person is needed for each edit application.

Addition to IDE. The ceiling is set by the editor API: what the owner does not provide will not appear. Often there is no running commands and reading their output, and the verification loop is closed by a human. Behavior varies between IDEs, so the experience of a colleague in another environment does not transfer completely.

Common to all three. No class checks the result for a person: tests, linter and review remain mandatory. And none of them can save you from a poorly posed task - the wrong job done confidently is worth more than the job not done.

How to check the result

• Run the same reference ticket in all three classes and compare by three measures: the number of human interventions, the amount of excess in the diff (git diff --stat), number of visits to green tests.
• Test autonomy directly: give a task where you need to run the test and read the output. A tool that asks you to copy output manually does not belong to the terminal class, no matter what it calls itself.
• Test behavior on an unfamiliar stack or on a module that is not found in popular training examples. The gap between the demo and your repository is visible there.
• Check the boundaries of rights: ask to do something prohibited - push to a protected branch, edit the environment file. Refusal at the mechanism level is more reliable than refusal at the polite level.
• Read the data policy: what goes outside, where the index is stored, whether the code gets into training. The answer should be in the product documentation, not in a paraphrase.
• Check in a week git log and honestly count how many commits are actually made with the tool. The feeling of acceleration and the number of completed tasks diverge more often than desired.

One line rule: a tool is chosen based on who runs the commands in conjunction and reads their output.