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dsh-agent-teams

Workflow Updated 2026.08.25

Run the following command in DeepSeek Harness:

dsh plugin install satan9394/dsh-agent-teams

Paste the following prompt into your AI chat to install this plugin:

Run dsh plugin install satan9394/dsh-agent-teams in DeepSeek Harness to install this plugin; the source is available at https://github.com/satan9394/dsh-agent-teams .

About this plugin

As multi-agent collaboration becomes a mainstream development paradigm, the question of how to organize a loose set of agents into a well-defined team with clear roles and a structured pipeline is one every developer eventually faces. dsh-agent-teams is a DeepSeek Harness plugin categorized under agent-workflow, built to help developers manage and coordinate multiple agents as a team rather than wiring up one-off calls every time.

At its core, the plugin introduces a team-level abstraction on top of the Harness runtime. Instead of hand-crafting coordination logic from scratch, developers can lean on the team and workflow concepts the plugin provides to assign tasks and chain processes between agents. The project is released under the MIT license, so it is free to use, fork, and contribute to.

If you are building multi-agent applications on DeepSeek Harness and want a more structured way to handle task distribution and process hand-off, dsh-agent-teams is worth exploring. The project is still in its early days with a small community, but its clear agent-workflow positioning and open license leave plenty of room for feature growth and community-driven development.

Use Cases

  • Organizing multiple agents into a team within DeepSeek Harness to execute complex tasks
  • Defining structured workflows and task distribution pipelines for multi-agent applications
  • Managing coordination and process hand-off between agents in the Harness environment

Best For

  • Developers building multi-agent applications on DeepSeek Harness
  • Engineering teams that need structured workflows to coordinate multiple agent collaborations
  • Indie developers or researchers looking to reduce the overhead of multi-agent coordination