The core philosophy of DeepSeek Harness is “everything is a plugin.” When building visual interfaces or design systems, developers typically need to handle the full cycle from ideation and direction to output and review. Existing design tools may have mature workflows but often rely on cloud services or expensive APIs. The following is a localized solution for this scenario.

Deep Design is a design-mode plugin for DeepSeek Harness, maintained by developer temidayoxyz. It turns a local Harness into a design studio, recreating the complete closed design loop from brief to delivery.

Core Capabilities

The plugin includes three main components:

  1. Deep Design agent preset: A complete design agent, including shell, file operations, web research, skills, planning, subagents, and workflows, focused on executing the design loop.
  2. deep-design-principles skill pack: Provides first-principles briefs, design language, composition guidance, motion suggestions, and anti-slop audits.
  3. deep-design-qa skill pack: Implements headless rendering (desktop and mobile), structured visual critique, targeted fixes, re-rendering, and comparison. Provides a pixel sampling fallback for models that do not support image input.

These two skill packs are registered globally, so any agent mode can load them from the skill directory, not just Deep Design sessions.

Installation and Activation

  1. Run the installation command:
    dsh plugin --profile web add dsh-deep-design

*(Note: You can also run `dsh plugin --profile web add ./deep-design` from a local checkout directory)*
  1. Restart the DeepSeek Harness Web UI.
  2. Open the new session interface.
  3. Select Deep Design in the agent preset chip.

After installation, the preset is placed in the $DSH_HOME/.agent-presets/design/ directory. The installation process is idempotent and does not overwrite existing files or directories.

Typical Usage

The plugin executes a fixed design loop:

brief → direction (.design/direction.md) → design system → artifact
     → render (headless, desktop + mobile)
     → critic pass (structured visual diagnosis)
     → fix → re-render → compare → deliver

Design memory accumulates across sessions: the loop reads the .design/ directory at the start of a session and records lessons learned at the end. This means the design improves with use, rather than relying solely on a more powerful model.

Applicable Scenarios and Notes

  • Model requirements: It is recommended to use a model with vision capabilities for Deep Design sessions so that the critique step can “see” the visuals. If the model does not support image input, the pixel sampling fallback can maintain the integrity of the loop.
  • Web research: Web research is enabled in the preset (fetch: true). Ensure that Harness has a web provider configured to obtain references.
  • Data privacy: Deep Design runs entirely locally. Unless you actively choose a cloud model, no data leaves the local environment.
  • License: The plugin is released under the MIT license. Check the source code and license before installation.