How to Make an AI Agent Write Code in Your Style Without Endless Prompt Tweaking

Familiar situation: a utility like Cursor or Claude Code delivers something that looks functional, but you immediately rewrite half of it? The variable name seems off, the logic is scattered across three tiny functions instead of one, and instead of the familiar async/await they gave you .then() chains. You add rules to text files like .cursorrules, but over time this list grows, and the neural network starts mixing them up or simply skipping them.

Developers from CommandCodeAI approached the problem from a different angle. Their command-line tool Command Code attempts to capture your preferences on the fly. Every accepted or rejected change, every manual edit generates a signal for the internal model taste-1. As a result, the tool accumulates what's called the developer's—or the entire team's—"taste".

Why Another CLI Agent

Most existing AI assistants operate in a single-query mode. You provide context, get a response, and make manual edits. When you run it again, the agent starts from a blank slate, repeating the same coding style mistakes.

Command Code is positioned as an agent that builds software while simultaneously remembering how you do it. According to the authors' vision, rigidly defined text instructions eventually become outdated, while an accumulated preference profile works more flexibly and accurately.

What Command Code Can Do

The project targets those who prefer working in the console and dislike being distracted by heavy interfaces.

Learning from Your Actions

The taste-1 model analyzes how you interact with proposed changes. Press accept — the feature is counted. Perform reject or edit a file manually — the system adjusts your local style profile. The more you work with the utility, the fewer manual corrections you need to make.

Convenient Interactive Mode

The tool launches in the terminal with a short command cmd. Within a session, familiar hotkeys and special characters are available:

• You can send a command or call the settings menu via /
• Switch to Bash command execution mode — via !
• Quickly finding and mentioning a file in dialogue is assisted by autocomplete via @

Synchronizing "Taste" Within a Team

The accumulated coding profile doesn't have to stay only with you. Commands npx taste push and npx taste pull allow you to share it with colleagues. This helps maintain a consistent code writing style in a project, even when different people with different habits work on it.

How It Works Under the Hood

The foundation is a neurosymbolic approach combining large language models and context processing rules. The repository lists support for multiple providers — from OpenAI and Anthropic to DeepSeek, GLM, and Kimi. You can plug in your own keys and select the model that best fits the specific task.

The actual workflow centers on a feedback loop. The agent makes an edit, you provide a verdict, and the utility logs the changes into a local preferences database.

To get started quickly, just run the standard installation:

npm i -g command-code

After that, navigate to your code directory and open a session:

cd your-project
cmd

Where the Tool Shines

• Routine refactoring. Code needs to be standardized, but writing a long prompt feels tedious. You do a couple of examples manually, and then the agent picks up the logic.
• Test coverage. Writing unit tests often hits project-specific conventions (structure describe/it, mocks, library choices). Command Code remembers this structure after the first two or three tests.
• Quick onboarding for newcomers. Instead of reading lengthy style guidelines, a new developer downloads the team profile via npx taste pull and gets an agent already configured to the company's internal standards.

Is It Worth Trying

The project is still young: the repository has gathered just over 3.5 thousand stars on GitHub and has around a hundred and fifty open issues. The documentation in the README itself is quite sparse, with the authors directing readers to their website for detailed tutorials.

Nevertheless, the idea of a neurosymbolic style profile seems far more viable than constantly expanding .cursorrules files. If you work extensively in the terminal and are tired of correcting code written by language models, the utility is definitely worth testing on a small pet project.