Kun Workspace
A shared desktop and terminal workspace for taking local project tasks through reviewable, testable delivery.
What does this agent do, and when should you use it?
Kun is a local-first AI agent workspace for code, writing, design, research, and automation. Its Electron desktop GUI and terminal TUI connect to one local `kun serve` runtime and share threads, plans, approvals, and task history. The Code workspace supports local-project search and editing, command execution, diffs, tests, and review, while Write and Design can produce documents, exports, HTML prototypes, and design-system material. Its experimental Agent Graph lets a Lead Agent coordinate constrained subagents through dependency-based tasks and explicit handoff checks. It is aimed at people and teams that want local-workspace execution evidence while retaining a choice of model providers.
A user opens a local project in the GUI or TUI and submits a task; both interfaces use the same kun serve runtime. Kun can search and edit files, run Terminal commands, manage Plans and Todos, inspect Git / Worktree state, show inline Diffs and a Changes panel, and use /plan to break down a goal or /review to produce review findings. It accepts image and PDF inputs for research, while Write can export Markdown, HTML, PDF, DOCX, and editable PPTX; Design can create HTML prototypes and DESIGN_SYSTEM.md. Automation uses Schedule, Loop, Hook, MCP, Skills, Extensions, and a local runtime API. Agent Graph creates dependency graphs, dispatches subagents within the parent task's permissions, retains execution history, and supports pause, resume, retry, editing, and stopping.
- A developer fixing a cross-file issue in a local TypeScript project who needs code search, file edits, test execution, and a diff review in one task.
- A technical lead coordinating a verifiable multi-stage change through experimental Agent Graph nodes for research, implementation, and validation.
- A writer turning an outline, source material, or draft into a polished deliverable that can be exported as PDF, DOCX, or editable PPTX.
- A product designer exploring an interface from requirements or reference images, producing an HTML prototype and `DESIGN_SYSTEM.md` for implementation.
- A researcher extracting and organizing evidence from PDFs, images, and web leads into structured conclusions and continuing task context.
- An individual or team documenting a recurring workflow with Schedule, Loop, Hook, MCP, and Skills while keeping recoverable execution records.
What are this agent's strengths and limitations?
- The desktop GUI and terminal TUI share one `kun serve` runtime, including threads, plans, approvals, usage, and background tasks.
- It keeps local-project file work, Terminal execution, Git / Worktree state, diffs, tests, and `/review` findings within one task record.
- It supports subscriptions, Coding Plans, Token Plans, APIs, OpenAI Chat Completions / Responses, Anthropic Messages-compatible services, and self-hosted models instead of a single provider.
- Agent Graph adds dependency scheduling, constrained subagents, evidence follow-up, and Lead Agent acceptance for complex tasks, with resumable history.
- Agent Graph is explicitly experimental; its coordination and acceptance flow is better suited to complex work, while Direct mode is faster for simple changes.
- Source use requires Node.js 22.19+, and practical use requires a supported subscription, API, or custom provider configuration.
- Local-first does not mean data never leaves the machine: prompts, attachments, and task context are sent to a selected cloud Provider when one is used.
- Media generation, higher-permission features, and available models depend on the version, operating system, Provider, model capability, and user authorization.
- The README identifies the license as PolyForm Noncommercial 1.0.0; commercial use, distribution, SaaS, hosting, resale, or commercial-product integration requires separate written authorization.
How do you install or deploy this agent?
Download the desktop release for macOS (Apple Silicon or Intel), Windows x64, or Linux x64; the desktop package includes the TUI. To run from source:git clone https://github.com/KunAgent/Kun.gitcd Kunnpm cinpm run dev
You need Node.js 22.19+, npm, and at least one supported model subscription, API, or custom provider. For slower mainland-China network access, use: npm ci --registry=https://registry.npmmirror.com.
How do you use this agent?
At first launch, choose a UI language, sign in to a model subscription or configure an API key, Token Plan, or custom Provider; then open a local project or create a workspace and submit a scoped, verifiable task. Run kun from a project directory to start the bundled TUI, which connects automatically to the same local runtime as the GUI. For source development, use npm run dev:tui for the TUI and npm run typecheck, npm run lint, and npm run test for validation.
How does this agent compare with similar options?
Compared with a chat interface that only generates answers, Kun is designed to keep requirements, plans, file changes, tool results, tests, review evidence, and delivery in one continuous workflow; Direct mode remains the lighter option for simple tasks.