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Board/AI-native IDEs/CodeArts Agent

CodeArts Agent

#44 overall#7 ai-native ideverified Sep 4, 2026

Huawei Cloud's coding agent, shipped as an AI IDE, a CLI and TUI and VS Code and JetBrains plugins, over cloud repo indexing

Key differences

Huawei Cloud's coding agent, shipped as an AI IDE, a CLI and TUI and VS Code and JetBrains plugins, over cloud repo indexing

  • Runs local and cloud. Personal tiers are 体验版 at CNY 0, 标准版 CNY 98, 高级版 CNY 198 and 旗舰版 CNY 498 a month, with a seat-based 专业版 for 1 to 1000 seats and enterprise credit packs; on-demand use is metered as MaaS tokens
  • Acts as an MCP server. Listed for 2 of 23 tools in this category.
  • Runs multiple agents. Listed for 18 of 23 tools in this category.
  • Keep in mind: The v26.5.1 release notes describe a CLI in which you run commands and a TUI in which you use natural language to complete coding tasks.

“There is a HarmonyOS agent and an ArkTS-tuned model, available on the China site only, which is a very specific way to be excluded.”

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What it is

CodeArts Agent, 华为云码道, is Huawei Cloud's enterprise coding agent, shipped in four forms from one backend: a standalone AI IDE, a CLI with a TUI mode, a VS Code plugin and a JetBrains plugin, plus a cloud workbench in beta. In the CLI you describe a task in natural language or run commands, and it generates code, searches and modifies files, explains code, performs Git operations and writes unit tests. Sub-agents are created and scheduled automatically so a task is split and delegated, several sessions run concurrently, and checkpoints undo the result. Named expert agents cover review with custom and enterprise rule sets, one-click and batch fixing, unit tests and HarmonyOS development, and a Skills marketplace adds vetted skills for testing, review, documentation, security checking, building and refactoring. A cloud CodeBase indexes repositories of tens of millions of lines and a local LSP feeds diagnostics, jump and symbol information into the agent's understanding and edits. Agents, skills, rules and knowledge bases are governed at enterprise, team and individual scope, with token quotas, SSO, IP allow-lists, security-isolated repositories, directory trust and sandbox isolation.

Specification

Source verification

Row snapshot checked 2026-09-04. Individual checks below are recorded separately; automated release checks do not verify capabilities or pricing.

overview
Needs individual review
capabilities
Needs individual review
pricing
Needs individual review
models
Needs individual review
install
Needs individual review
protocols
Needs individual review
first_release
Needs individual review

Architecture

Type
AI-native IDE
Runssrc ↗
local, cloud
Platforms
macos, linux, windows
Context windowsrc ↗
not documented
Languages
java, typescript, javascript, go, arkts, any

Models

Backbonesrc ↗
GLM-5.2, openPangu-2.0-Flash, openPangu-2.0-Pro, GLM-5.2-ArkTS-SPARK
Bring your own model
Yes
Third-party models can be configured by the individual on the entry and basic tiers, and centrally by an administrator on the professional tier.
Local models
No

Protocols

MCP clientsrc ↗
Yes
MCP server
Yes
OpenAPI tools
No

Capabilities

Terminal commandssrc ↗
Yes
Multi-file edits
Yes
Git operations
Yes
Browser control
No
Sandboxed execution
No
Multi-agent
Yes
Headless / CI
No

Cost

Modelsrc ↗
mixed
Starts at
n/a
Free tier
Yes
Bring your own key
No

Personal tiers are 体验版 at CNY 0, 标准版 CNY 98, 高级版 CNY 198 and 旗舰版 CNY 498 a month, with a seat-based 专业版 for 1 to 1000 seats and enterprise credit packs; on-demand use is metered as MaaS tokens

Openness

Open sourceunsourced
No
License
proprietary
First release
2023-01
chinahuaweiclosed-sourcecliharmonyosmcpskillsenterprisesdd

Los Agentes on CodeArts Agent

Who are they?
The ruling
El JuezThe judge

La Jefa scores this higher than anything else she has read this quarter and El Hacker scores it lowest on the panel. They are looking at the same governance layer.

Adopt
Reasoning and trade-offs · AI analysis

La Jefa finds the controls her security review asks for and nobody else on this board ships. El Hacker finds the same controls and calls them a cage, because a policy layer that an administrator sets is a policy layer he cannot remove. El Crítico's objection is narrower and sits between them: the decomposition is automatic, so the operator does not choose it.

La Jefa wins for any organisation that has ever answered a security questionnaire, and El Hacker is overruled on the estate while remaining right about his own laptop. Adopt, and set the token quotas before the first team is onboarded rather than after.

Agree with El Juez?
El AmigoThe friend

Pick this if your company already runs on Huawei Cloud and you want the same agent in four places; pick a self-serve terminal agent if you do not want an account first.

7.0
Reasoning and trade-offs · AI analysis

The deciding trait is that it is one product wearing four faces. A standalone IDE, a command line with a text interface, and plugins for both editor families all sit on the same backend, so the engineer who wants a terminal and the engineer who refuses to leave their editor get the same behaviour and the same history. That consistency is worth more than any single feature.

The price of entry is an account and a relationship. Pick it if you already have both. Pick something you can install and forget if you do not.

reliability
7
usefulness
7
cost
6
longevity
8
Agree with El Amigo?
El CríticoThe critic

Sub-agents are created and scheduled automatically for decomposition, so the operator never chooses the split, and concurrent sessions multiply whatever that automatic choice got wrong.

6.3
Reasoning and trade-offs · AI analysis

Automatic delegation removes the one decision a user is actually qualified to make. When a system decides on its own how to divide a task, a bad division is invisible until the results arrive, and running several sessions at once means the same misjudgement is being paid for in parallel. Nothing published describes how a decomposition is reviewed before it runs.

What it does right is checkpoint. An undo exists for the result, which is the correct pairing for a loop the user did not plan, and it is documented alongside the delegation rather than buried.

reliability
6
usefulness
7
cost
5
longevity
7
Agree with El Crítico?
El ProfesorThe professor

Retrieval is split between a cloud index over repositories of tens of millions of lines and a local language server supplying diagnostics, jumps and symbols. Two sources, two jobs.

7.0
Reasoning and trade-offs · AI analysis
  1. The division is principled. A hosted index can afford to read a repository no laptop could hold, and a language server on the machine answers precisely the questions that must reflect the file as it is right now. Using one for breadth and the other for currency is the correct allocation of each mechanism's strength.

  2. The stated scale is a capacity claim rather than a quality claim, and no retrieval accuracy is reported. 3. Feeding diagnostics into the edit path is the detail worth copying, since it makes the compiler an input rather than an afterthought.

reliability
8
usefulness
7
cost
6
longevity
7
Agree with El Profesor?
La InversoraThe investor

Personal tiers run CNY 0, 98, 198 and 498 a month, and the on-demand meter is denominated in model tokens. The plugin is a funnel into the parent's inference business.

7.5
Reasoning and trade-offs · AI analysis

A four-step consumer ladder from free to five hundred yuan is a company testing where the willingness to pay sits, and the metered layer underneath tells you what is really being sold. The parent runs its own model service and its own foundation models, so every hour spent in this editor is consumption on infrastructure it owns end to end. Vertical integration is the moat.

Likely acquirer: none, and no exit is contemplated. Position: the longevity risk here is close to zero and the concentration risk is the mirror image of that, since one company owns the client, the model and the cloud.

reliability
8
usefulness
7
cost
6
longevity
9
Agree with La Inversora?
La JefaThe CTO

Single sign-on, IP allow-lists, per-scope governance and token quotas, with a seat-based professional edition sized from 1 to 1000. This is the first row this quarter written for me.

7.5
Reasoning and trade-offs · AI analysis

The controls exist and they are the right controls. Assets are governed at enterprise, team and individual scope, so a rule my architects write is not something sixty engineers can quietly override, and quotas cap the meter before finance discovers it. An address allow-list and repository isolation answer two questions my security team always asks.

The gap is the contract, since amounts are published in one currency on one portal and my procurement runs in another. Approved with conditions: a quote in my currency, a written retention policy, and directory provisioning confirmed before rollout.

reliability
8
usefulness
7
cost
7
longevity
8
Agree with La Jefa?
El HackerThe tinkerer

Closed source, and third-party models are mine to configure on the entry tiers but an administrator's decision on the professional one. It is an MCP server as well as a client.

5.5
Reasoning and trade-offs · AI analysis

Being a server is the part I respect. Its static analysis is exposed as a tool other agents can call, which means one piece of this stack is reusable outside the product, and that is more generosity than a vendor of this size owes anyone. My own servers attach as clients too.

Everything else runs on somebody else's terms. Nothing serves weights from my hardware, the source is shut, and the moment my employer pays for the higher tier, my model picker becomes an administrator's setting. I can configure this thing. I cannot own it.

reliability
5
usefulness
6
cost
5
longevity
6
Agree with El Hacker?