Golutra AI Workspace
A desktop orchestration layer that turns existing AI CLIs into a parallel, observable agent workspace.
- Source repo
- golutra/golutra
- Stars
- ★ 3.9k
- Last updated
- 1mo ago
- License
- NOASSERTION
- Primary language
- Rust
- FA score
- 21/100 · Major gaps
At a glance
- How it runs
- Works with
- Universal · cross-platformCodex · Claude Code
- Cost
- Free software; you pay for model usage
- Setup effort
- Medium · a few setup steps
- You'll need
- Typical use
- A solo developer using Codex CLI who wants implementation, testing, and regression work to proceed in parallel with one status view.
- Not a fit if
- Teams wanting a hosted service or public API; only a desktop app and source are offered
- Legal-sensitive adopters needing clear licensing; metadata and README license claims conflict
- Source review
- 21/100 · Major gaps 8 safety controls not found
What does this agent do, and when should you use it?
Golutra is a multi-agent desktop workspace built with Vue 3, Rust, and Tauri, with stated support for Windows, macOS, and Linux. It places Claude Code, Gemini CLI, Codex CLI, OpenCode, Qwen Code, OpenClaw, and other CLIs behind one visual orchestration layer. Users can run agents in parallel, inspect status and logs, and inject prompts into terminal streams while work is running. The repository describes custom workflows plus one-click workflow-template import and export for long-running automation. Its documented delivery boundary is a desktop application distributed through repository releases; no hosted service or public API is defined in the supplied material.
Golutra coordinates existing CLI sessions from one desktop interface: it runs multiple agents, tracks their status, and hands results into subsequent workflow stages. A user can select an agent avatar to inspect logs or use Direct Injection to send a prompt into that agent's terminal stream. It supports custom workflows and workflow-template import/export, and the README says it can consolidate test, build, and regression output into one delivery path. EverOS is named as an optional memory-layer project, while golutra-mcp is named as a related project for connecting external tools and agents through golutra-cli; the supplied evidence does not document concrete commands or APIs for either integration.
- A solo developer using Codex CLI who wants implementation, testing, and regression work to proceed in parallel with one status view.
- An engineer who alternates between Claude Code and Gemini CLI and wants to keep existing commands while reducing terminal switching.
- A team setting up long-running automation that needs reusable custom workflows and importable or exportable templates.
- A developer supervising active agents who needs to inspect execution logs and add instructions directly to a terminal stream.
- An engineering workflow owner who wants test, build, and regression information consolidated into one delivery path.
How do you install or deploy this agent?
The README provides a Releases page as a download destination, but it does not provide package names, installation steps, runtime prerequisites, build commands, configuration, or a first-launch command. A copyable installation procedure cannot be established from the supplied evidence.
How do you use this agent?
No end-to-end first-run tutorial is documented. The described operating model is to retain a supported CLI, run agents in parallel through Golutra, select agent avatars to inspect logs, use Direct Injection when a running terminal needs new input, and create custom workflows or import/export workflow templates for long-running work.
What are this agent's strengths and limitations?
- It explicitly lists Claude Code, Gemini CLI, Codex CLI, OpenCode, Qwen Code, OpenClaw, and Any CLI compatibility, which is useful for teams retaining established CLI habits.
- It combines parallel agent execution, status tracking, log inspection, and direct terminal prompt injection in a desktop interface.
- Custom workflows and template import/export are positioned for long-running automation rather than only short interactive sessions.
- The stated Vue 3, Rust, and Tauri implementation includes declared support for Windows, macOS, and Linux.
- No copyable installation, build, configuration, first-run, or workflow-authoring instructions are supplied, so practical adoption requires independent validation.
- The product is positioned around existing CLIs; the documentation does not establish a bundled model, credential-management approach, or standalone mode without a CLI.
- EverOS and golutra-mcp are described only as related integrations, without repository-level setup, stability guarantees, or operational boundaries.
- Repository metadata says NOASSERTION while the README claims BSL 1.1, so adopters should verify the actual license file and commercial terms.
- Claims about unlimited parallel execution and large efficiency gains are not accompanied by benchmarks, resource requirements, or recovery behavior.
How does this agent compare with similar options?
The README contrasts traditional IDE work as “single-threaded + manual context switching” with Golutra's parallel multi-agent execution and automated orchestration. It is presented as a layer above, rather than a replacement for, Claude Code, Gemini CLI, Codex CLI, OpenCode, Qwen Code, and OpenClaw.
Key facts side by side with the most closely related agents.
| Agent | Source review | Form / cost | Stars | Updated | Language | Full support on |
|---|---|---|---|---|---|---|
| Golutra AI Workspace This agent | 21 · Major gaps | Desktop appFree + model costs | ★ 3.9k | 1mo ago | Rust | Codex · Claude Code |
| oh-my-agent | 48 · Major gaps | CLIFree + model costs | ★ 1.4k | 1d ago | TypeScript | Codex · Claude Code |
| hcom | 69 · Some gaps | CLIFree + model costs | ★ 635 | 16d ago | Rust | Codex · Claude Code |
| Agent Skills Library | 67 · Some gaps | Agent plugin / skillFree + model costs | ★ 240 | 2mo ago | Python | Codex · Claude Code |
How does FollowAgents rate this agent?
Why each dimension lost points
Evidence shows: The repository provides no documentation or code for permission model, user confirmation, data flow transparency, sensitive data handling, dependency security, external effects control, rollback, or source attribution. All trust criteria are unsupported, hence score 0.
Evidence shows: README and tests are broadly consistent in feature description, but tests only cover chat utility functions, not core orchestration. Dependencies are listed in package.json but no lockfile or integrity checks are provided. No failure messages or error handling documentation. Thus self-consistency scores 1, dependency availability 1, failure messages 0.
Evidence shows: README identifies target audience (one-person companies, software teams) and multiple scenarios (automated writing, Xiaohongshu publishing, etc.), but capability boundaries are vague, no explicit trigger conditions or environment requirements. Hence audience and scenarios 2, capability boundaries 1, trigger precision 0, environment fit 1.
Evidence shows: README provides basic information architecture and install notes (download via releases), but lacks naming stability, known limitations, versioning/changelog. License is BSL 1.1 but metadata is NOASSERTION, and maintenance responsibility is by an individual developer. Thus information architecture 1, install notes 1, naming stability 0, examples and FAQ 1, known limitations 0, license 2, versioning/changelog 0, maintenance responsibility 1.
Evidence shows: README describes output usability (logs, result tracking) and marginal value (multi-agent parallel, automated orchestration), but lacks cost-benefit analysis. Hence output usability 1, marginal value 2, cost-benefit 1.
Evidence shows: Claims in README (e.g., support for multiple CLIs) lack verifiable details or test evidence, and no external sources corroborate. However, README distinguishes facts (feature list) from inferences (future plans). Thus claim traceability 1, cross-source corroboration 0, fact-inference separation 1.
- Not found in source: least-privilege scopingGrant only what the task needs: a dedicated account or read-only token, scoped to specific directories and repos.
- Not found in source: confirmation before actingTurn on (or add) a confirmation step before it acts, and try it in a sandbox or test environment before real data.
- Not found in source: data-flow disclosureWatch which external services it contacts (proxy or firewall logs) and keep sensitive data out until you know where it goes.
- Not found in source: sensitive-data handlingUse dedicated, low-privilege, revocable API keys — never production credentials — and keep secrets out of logs.
- Not found in source: dependency securityPin versions and run a dependency audit (npm audit, pip-audit) before installing; prefer running it in a container.
- Not found in source: disclosed external effectsEstablish which external systems it writes to, sends to or changes, and verify with test accounts or repos before production.
- Not found in source: rollback or recovery pathBack up first, or work on a git branch or snapshot, so its changes can be undone.
- Not found in source: verifiable attributionInstall from the official repo or registry and check the publisher and URL to avoid look-alike packages.
- The repository provides no security or permission documentation; assess risks before use.
- Test coverage is limited; core functionality is not verified by tests.
- License metadata is NOASSERTION, actual is BSL 1.1; note commercial use restrictions.
Recent releases
Latest entries from the project's GitHub Releases. Notes are quoted from upstream as written, not rewritten or tested by FollowAgents.
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Release notes excerpt
中文 更新说明 - Golutra 0.3.4 重构远程控制能力，优化终端显示，并升级 Golutra Agent。 版本亮点 - 重构远程控制，优化远程交互流程与稳定性。 - 优化终端显示，改善内容呈现与使用体验。 - 升级 Golutra Agent，增强智能代理能力。 桌面端下载 - Windows aarch64 MSI: golutra_windows_aarch64.msi - Windows aarch64 签名: golutra_windows_aarch64.msi.sig - Windows x86_64 MSI: golutra_windows_x86_64.msi - Windows x86_64 签名: golutra_windows_x86_64.msi.sig - macOS aarch64 DMG: golutra_darwin_aarch64.dmg - macOS aarch64 更新包: golutra_darwin_aarch64.app.tar.gz - macOS aarch64 更新签名: golutra_darwin_aarch64.app.tar.gz.sig - macOS x86_64 DMG: golutra_darwin_x86_64.dmg …View on GitHub ↗ -
Release notes excerpt
中文 更新说明 - Golutra 0.3.3 重构桌面端，新增 Golutra Agent，并优化界面显示与终端窗口流畅性。 版本亮点 - 重构 Golutra 桌面端，优化整体架构与使用体验。 - 新增 Golutra Agent，扩展智能代理能力。 - 优化 UI 显示，提升界面清晰度与一致性。 - 优化终端窗口的渲染与交互流畅性。 桌面端下载 - Windows aarch64 MSI: golutra_windows_aarch64.msi - Windows aarch64 签名: golutra_windows_aarch64.msi.sig - Windows x86_64 MSI: golutra_windows_x86_64.msi - Windows x86_64 签名: golutra_windows_x86_64.msi.sig - macOS aarch64 DMG: golutra_darwin_aarch64.dmg - macOS aarch64 更新包: golutra_darwin_aarch64.app.tar.gz - macOS aarch64 更新签名: golutra_darwin_aarch64.app.tar.gz.sig …View on GitHub ↗ -
Release notes excerpt
中文 更新说明 - Golutra 0.3.2 对整体代码进行了全面重构，优化内部结构与实现方式。 版本亮点 - 全面重构整体代码，改善代码组织和内部实现。 - 增强运行稳定性，提升复杂场景下的可靠性。 - 提升代码可维护性，为后续功能迭代和跨平台维护奠定更稳固的基础。 桌面端下载 - Windows aarch64 MSI: golutra_windows_aarch64.msi - Windows aarch64 签名: golutra_windows_aarch64.msi.sig - Windows x86_64 MSI: golutra_windows_x86_64.msi - Windows x86_64 签名: golutra_windows_x86_64.msi.sig - macOS aarch64 DMG: golutra_darwin_aarch64.dmg - macOS aarch64 更新包: golutra_darwin_aarch64.app.tar.gz - macOS aarch64 更新签名: golutra_darwin_aarch64.app.tar.gz.sig - macOS x86_64 DMG: golutra_darwin_x86_64.dmg …View on GitHub ↗