agent-team
Multi-agent team management plugin for DeepSeek Harness
What it is
Multi-agent team management plugin for DeepSeek Harness
How to install
Run this in the DSH web profile, then refresh the page.
$ dsh plugin --profile web add @limuyang2/dsh-agent-team@0.1.4
DSH versions accepted
^0.1.1-rc.2
Author and traction
limuyang2 · ★ 51 · Updated 2026-08-26
About this plugin
Agent Team for DeepSeek Harness
English | 简体中文
Current release: 0.1.4
Build teams of independent AI agents inside DeepSeek Harness. Mix models and providers, assign one Leader, and let every member work in its own conversation while sharing the same Workspace.
Agent Team does not turn members into subagents. Every member is an independent root agent with its own model, session, context, permissions, reasoning mode, and tool activity. Team tasks, messages, and the shared Workspace provide the collaboration layer.
Why Independent Agents Instead of One Overloaded Agent?
Agent Team is designed around a simple idea: give specialized work to a specialized agent.
A common parent/subagent workflow reuses or inherits much of the parent runtime configuration. That is convenient, but it can make every task carry the same expensive model, broad tool catalog, and growing context. A small commit-message task, for example, may still run through the same high-capability model used for architecture and implementation.
Agent Team lets every member have an explicit, focused configuration: This separation keeps the Leader focused on planning and verification, keeps specialists focused on execution, reduces irrelevant tool choices, and prevents one agent's context from growing with every detail produced by the whole team. Members send tasks, progress, and results explicitly instead of sharing an ever-expanding conversation. Subagent behavior varies by framework. The comparison above describes the common parent-inherited pattern; Agent Team's advantage is that model, tools, permissions, and context isolation are explicit product-level choices for every member. Example: Use the Right Model for Each Job
Consider a software development team with three specialized members: The GPT Leader spends its context on decisions and verification instead of every implementation detail. GLM receives the codebase context and tools required for execution. DeepSeek Flash handles the narrow commit task quickly without paying for the Leader's higher-capability model or loading the coding agent's large tool catalog.
The collaboration flow is explicit:
What You Can Do Create reusable assistants for planning, coding, testing, review, documentation, or any other role. Mix providers and models in one team—for example, a Codex Leader with GLM coding members. Create assistants manually or describe a role to the built-in Team Agent Assistant. Add the same assistant more than once; every selection becomes an independent team member. Watch all members side by side with streaming output, Markdown, Think blocks, and tool calls. Let the Leader create tasks, assign members, track progress, and collect results. Send messages directly to the Leader or, when enabled, to regular members. Change a member's permission preset and reasoning mode for the current session. Inspect loaded Skills, context usage, token statistics, and cache hit rate. Browse shared Workspace files and preview Git changes and diffs. Add or remove members, change the Leader, reset all contexts, or dissolve a team. Screenshots Create an Assistant by Conversation
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