Coding agents · AI agent
Command Code: review, pricing, security and alternatives
Command Code is an open-source AI agent published by CommandCodeAI, in the coding agents family. Command Code is a terminal coding agent that uses open models to implement features, fix bugs, write tests, and refactor code. Its repository has 4,167 stars and its last commit is from October 23, 2026.
What Command Code does
Command Code belongs to the coding agents family: they read a repository, edit files, run the tests and fix things until everything passes, in a terminal or an editor. On our grid it ranks #53 of the 74 projects of this family listed in the directory.
You use it from: terminal (CLI). Usable models: DeepSeek, GLM (Zhipu), and Kimi (Moonshot). It can run on your own machine or server.
Who is Command Code for?
It is aimed at developers and technical teams who want to hand off part of the work on their codebase while keeping the final review. Typical tasks people give it:
- fix a bug from an issue or an error message
- write or extend tests
- migrate code to a new library version
- explain an unfamiliar codebase
It is a good candidate if you are comfortable in a terminal and your data must stay on your machines.
Access and human control
According to its documentation, Command Code can:
- run commands in a terminal
- read and edit files
We could not establish whether it asks for human approval before sensitive actions: test it first on an unimportant account or folder.
Command Code pricing
The code is public but the repository declares no licence: reuse is not formally allowed. The real cost comes from model calls: each loop step sends the whole context back to the model, and a task of several dozen steps can cost far more than a single question. The LLM price calculator estimates it for the chosen model.
Getting started with Command Code
- Install it by following the repository README.
- Create an API key with the model provider and put it in an environment variable, never in a shared or versioned file.
- Give it a first playground with nothing at stake: a test folder, a secondary account or a throwaway project. Only open your real accounts once you have seen how it behaves.
- Give it a short, checkable task, review the result and its action log, then raise the difficulty step by step.
Security: risk level
A coding agent runs commands on your machine: work on a Git branch, review the changes and isolate it in a container for long tasks.
Points found for Command Code:
- Sensitive access: it can run commands in a terminal, with no established default human approval.
- No licence: legally shaky for company use.
Three habits: least privilege (minimal rights, dedicated keys), human approval for irreversible actions, a sandbox for code execution. The AI agent security check reviews your setup in a few minutes.
Project activity and releases
Created on December 20, 2017, the CommandCodeAI/command-code repository has 4,167 stars, 371 forks and 379 open issues, with 51 commits in total. It received changes this month.
Over the last 52 weeks: 36 commits, an average of 0.7 per week.
1 releases in total; 0 in the last twelve months. Latest release: 1.0.0, on January 12, 2018.
Command Code vs other coding agents
GitHub stars of the best-rated open-source projects in the coding agents family. Stars measure attention, not quality: a heavily promoted project collects them fast, a specialised tool will have few.
Command Code and other coding agents at a glance
The 7 best-ranked agents in the same family, 7 of them open source. The score out of 100 only applies to open-source projects; for proprietary services we show the published entry price. A dash marks information the documentation does not state.
| Agent | Model | Score | Stars or entry price | Self-hostable | Human approval |
|---|---|---|---|---|---|
| Command Code | open source | 50 | 4.2K ★ | yes | – |
| OpenCode | open source | 95 | 221K ★ | yes | – |
| Cline | open source | 94 | 70.8K ★ | yes | yes |
| OpenHands | open source | 91 | 91.7K ★ | yes | – |
| Codex | open source | 89 | 130.8K ★ | yes | yes |
| Open Interpreter | open source | 89 | 68.7K ★ | yes | – |
| Qwen Code | open source | 89 | 28.7K ★ | yes | yes |
| Kilo Code | open source | 89 | 27.7K ★ | yes | yes |
How we rated it
Score: 50/100, computed only from public, verifiable data, with no subjective testing or partnership:
- Adoption 19/40: 4,167 stars on a log scale (40 points from about 200,000).
- Activity 16/30: last commit less than a month ago, 0 releases in six months, 36 commits in a year.
- Framework 15/30: licence, default human approval, self-hosting, model choice and documentation site.
The score does not say whether the agent will succeed at your tasks: it measures how solid the project is. The full grid is on the method page.
Verdict
Command Code is a project to watch: compare it with the alternatives before adopting it.
Strengths
- Very active development
- Can run on your side: data under control
- Free choice of model
Limitations
- Broad access without default approval
- No licence declared
Avoid if…
- You cannot isolate it (container, virtual machine)
Alternatives
Learn more
Frequently asked questions
Is Command Code free?
The software is public, with no declared licence. You still pay for the model calls, unless you use a local model.
Is Command Code safe?
Our risk level: high. Points found: sensitive access and no licence. Give it minimum rights and approve irreversible actions.
Which models does Command Code use?
According to its documentation: DeepSeek, GLM (Zhipu), and Kimi (Moonshot).
Can Command Code be installed on your own server?
Yes, from the CommandCodeAI/command-code repository. Data then stays with you, but security and updates are your job.
What are the alternatives to Command Code?
In the same family: OpenCode, Cline, OpenHands, and Codex.
Command Code or OpenCode: what is the difference?
Both belong to the coding agents family. Command Code has 4.2K stars against 221K for OpenCode. The right choice mostly depends on the access you are willing to give it.
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Neutrality. No affiliate links. No vendor pays to be reviewed, rated or ranked. Reviews are directed by François Chollet, neutral and factual, and every data point is dated and sourced. How we score