DeepSeek Harness

What it does

DeepSeek Harness is an open-source agent environment. You describe a task in plain language, add files and conversation context in a workspace, and an agent carries it out. Output includes edited code with diffs, Word, Excel, PDF, HTML and Markdown files, cited research answers, and results from scheduled or background jobs. It runs as a desktop app or as a Web UI launched from the command line.

Typical uses include preparing reports and slide decks, analysing spreadsheets, fixing issues and running tests in a code repository, and running long scripts or batch file jobs with progress tracking. Everything is built as a plugin: install existing plugins, or describe a new one in creation mode. Developers can inspect execution traces and tool-call details. Agent teams, automated tasks, auto-authorization review and voice input are marked experimental.

It suits knowledge workers, developers and plugin authors comfortable with an early release. The product is a preview and developer preview, and the repository warns of compatibility-breaking changes. The desktop app supports macOS (Apple silicon, macOS 13 or later) and Windows. You can also run it through Node.js with npx or build it from source. The source code is MIT-licensed. For model access and usage costs, check with DeepSeek. Interface text is mainly in Chinese.

What it can do

• Handle everyday work such as organising material, analysing spreadsheets, drafting documents and building presentations
• Write and modify code in a repository: understand the project, fix issues, build features and run tests
• Search and cross-check sources and give answers with cited sources
• Run scripts and batch file jobs in the background with progress tracking, including scheduled recurring tasks
• Extend with plugins, including creating a plugin through conversation in creation mode
• Inspect execution traces and tool-call details in developer tools

Example workflows

Weekly project report on a schedule

Input: project records in a workspace and a prompt to compile a weekly report. Steps: describe the recurring task and time, let the agent create a scheduled task, and wait for the trigger. Output: a report generated each week at the set time (automated tasks are experimental).

Fix a bug in a code repository

Input: a repository and a description of the problem. Steps: open the project as a workspace, ask the agent to diagnose and edit the code, review the shown diffs, and have it run tests. Output: modified source files and test results.

Before you choose

• Labelled preview and developer preview; the repository warns of compatibility-breaking changes and includes a safety notice to read before running.
• Agent teams, auto-authorization review, automated tasks and voice input are marked experimental.
• The code is open source under the MIT licence, but model usage costs and model requirements should be confirmed with DeepSeek before relying on it.

Listed under

• Coding

Get started

Or clone the GitHub repository and build from source

1. Download the desktop app for macOS or Windows from the download page.
2. Alternatively, install Node.js and run npx @deepseek-ai/dsh web to start the local Web UI.
3. Open a workspace, then install plugins or use creation mode to build your own.

The source code is available under MIT. Model access and compute are separate.

Source: github.com/deepseek-ai/deepseek-harness, checked 28 Oct 2026. Prices can change; check before you buy.

Sources for this overview

Product pages, documentation, and pricing checked 28 Oct 2026. Each source supports part of the overview; availability and prices can change.

• DeepSeek Harness｜共探智能上限 ↗www.deepseek.com
• DeepSeek | Download DeepSeek ↗www.deepseek.com
• GitHub - deepseek-ai/deepseek-harness: DeepSeek Harness: Everything is a Plugin. · GitHub ↗github.com

Company website

deepseek.com: product, pricing and policy pages

Web search

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Human review

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knowledge_base

Last checked 28 Oct 2026. Every field keeps its source and date; unknown means we couldn’t confirm it.