agent-team

Agent Team for DeepSeek Harness

English | 简体中文

Current release: 0.1.2

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:

Concern	Common parent/subagent setup	Agent Team
Model	Often reuses the parent model or one shared model policy	Choose a different provider and model for every member
Skills and MCP	A broad catalog may be inherited or exposed everywhere	Give each role only the Skills and MCP Servers it needs
Context	Planning, execution, tool output, and results accumulate together	Every member has an isolated Session and context window
Cost	Simple work may still consume an expensive general model	Route routine work to smaller or specialized models
Permissions	One broad permission policy can spread across the workflow	Set least-privilege defaults and runtime permissions per member

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:

Role	Model	Focused configuration
Architecture Leader	GPT	Understand the requirement, design the solution, split work, coordinate members, and verify results
Coding Agent	GLM	Load coding Skills and development MCP tools, modify the Workspace, and run tests
Commit Assistant	DeepSeek Flash	Read Git status and diffs, then generate a Conventional Commit message with read-only permission

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:

User goal → GPT Leader plans and assigns work
          → GLM Coding Agent implements and reports test results
          → GPT Leader verifies the result
          → DeepSeek Flash Commit Assistant summarizes the Git diff

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

Describe the role you need. The built-in assistant collects missing settings, prepares the long-term instructions, and creates the assistant only after your confirmation.

Reusable Assistant Library

Manage assistants under Settings → Agent Team. Each assistant can use a different provider, model, preset, default permission, reasoning mode, Skills, MCP Servers, and role instructions.

Skills and MCP scope: Agent Team uses Skills and MCP Servers exposed through the standard DeepSeek Harness interfaces. This plugin does not provide installation, updates, or lifecycle management for Skills or MCP Servers. Install the appropriate Harness plugins to manage those resources first; Agent Team only lets an assistant select and use the resources already available in the active Profile.

Build a Team

Select members, assign exactly one Leader, choose a Workspace, and decide whether direct communication with regular members is allowed.

Floating Team Launcher

A compact floating button opens the full-screen Team workbench without competing with sidebar extensions from other Harness clients. Hover over it or drag it to reveal the label. Drop it at either screen edge to collapse it toward that edge; the last position is remembered locally. Create teams and switch between them from the workbench navigator.

Requirements

• Node.js 22.19.0+ or 24.0.0+
• DeepSeek Harness 0.1.0-rc.7
• pnpm available on PATH (Harness uses it to manage Profile plugins)

Install pnpm if necessary:

npm install -g pnpm

Installation

Install Agent Team into the Harness web Profile:

npx @deepseek-ai/dsh plugin --profile web add @limuyang2/dsh-agent-team

Start Harness:

npx @deepseek-ai/dsh web

Open the URL printed by Harness, normally http://127.0.0.1:3080/. Restart Harness after installing or replacing the plugin.

Uninstallation

Stop Harness with Ctrl+C, then remove Agent Team from the web Profile:

npx @deepseek-ai/dsh plugin --profile web remove @limuyang2/dsh-agent-team

Restart Harness after the command completes. Removing the plugin does not modify DeepSeek Harness source code or delete files from your team Workspaces.

Quick Start

1. Configure Models in Harness

Configure the providers, models, and credentials you want to use in Harness first. Agent Team reads the model catalog from the active Profile and never stores provider API keys.

Tip: enable Thinking Mode for GLM-5.3

Add the following configuration to ~/.dsh/settings.yaml. It exposes the available reasoning levels for GLM-5.3 and sets high as the Provider default:

llm-pi-ai:
  providers:
    zai-coding-cn:
      reasoning: high
      modelOverrides:
        glm-5.3:
          reasoningEfforts:
            off:
            minimal: minimal
            low: low
            medium: medium
            high: high
            xhigh: xhigh
            max: max
          compat:
            thinkingFormat: zai
            supportsReasoningEffort: true

Merge this block into an existing llm-pi-ai section instead of adding a second one. If your ZAI Provider uses a different ID, replace zai-coding-cn. Restart Harness, then select the desired Thinking Mode from the assistant conversation toolbar; that runtime selection overrides the Provider default for the conversation.

2. Create Assistants

Open Settings → Agent Team and choose one of the following:

• Start Conversation to design an assistant through chat.
• Create Manually to configure all fields directly.

A practical first team usually contains:

• A Leader that understands goals, plans work, delegates tasks, and verifies results.
• One or more members focused on implementation, testing, review, or documentation.

3. Create a Team

Click the floating Team button, then click + in the workbench navigator:

1. Add assistants from the list. You may add the same assistant multiple times.
2. Select exactly one member as the Leader.
3. Enter a team name and choose a Workspace.
4. Choose whether users may chat directly with regular members.
5. Click Create and Start.

The team starts automatically and opens in the full-screen workbench.

4. Give the Leader a Goal

Send the complete objective to the Leader. The Leader can split it into tasks, assign members, receive progress updates, and verify the final output. You can also talk to an individual member directly when the team policy allows it.

Workbench Guide

Each visible column is a real, independent Harness session.

• Member tabs: show or hide conversations. Hover a non-Leader tab to remove that member.
• Conversation header: shows role, provider, model, reasoning mode, and live status. Double-click it to enlarge the conversation.
• Composer: send messages, attach local files, mention Workspace files, stop generation, and change runtime settings.
• Permission: applies to the selected member's current session. The assistant template only supplies the initial default.
• Reasoning mode: applies from the next turn and only shows options supported by the selected model.
• Info: displays the Skills loaded for the member.
• Context ring: displays context usage, input/output tokens, and cache hit rate.
• Workspace: browse files, refresh manually, watch file changes, and preview Git diffs.

Team Collaboration

The Leader and members communicate through explicit team tools and messages:

• The Leader creates tasks and assigns them to member instances.
• Assigned members receive the task in their own session.
• Members report running, completed, or failed status with a result.
• Status and result updates automatically reach the Leader.
• Members can send direct team messages when clarification is needed.
• Membership changes are delivered to the Leader with stable member IDs.

Members share a Workspace, but they do not share conversation history. This keeps roles and model contexts isolated while allowing them to work on the same files.

Team Management

• Add member: starts a new independent member from an assistant snapshot and notifies the Leader.
• Remove member: stops and archives that member's session, removes it from the team, and notifies the Leader.
• Change Leader: changes the role without replacing the member's current session.
• Clear tasks and context: stops all members, clears team tasks and queued messages, and gives every remaining member a new session. Team settings and Workspace files stay unchanged.
• Dissolve team: permanently removes the team, its tasks, and team messages. Assistant templates and Workspace files are not deleted.

Assistant settings are snapshotted when a member joins a team. Editing an assistant later does not hot-update existing members; remove and add the member again to apply the new configuration.

Important Behavior

• The assistant's permission setting is only the member's initial default.
• Reasoning options come from Harness model capabilities; unsupported options are not invented by the plugin.
• MCP credentials remain in the Harness Profile. Assistant templates only store allowed server names.
• Files selected from outside the Workspace are copied to .agent-team/uploads/ so agents can access them reliably.
• The Changes view requires a Git Workspace. Normal folders still support file browsing.
• Harness currently has no public API for physically deleting one session log. Reset or dissolved sessions are no longer restored or used by Agent Team, but old logs may remain in Harness storage.

Troubleshooting

pnpm not found on PATH

Run npm install -g pnpm, verify pnpm --version, and install the plugin again.

Port 3080 is already in use

Another Harness process is already running. Stop the old process with Ctrl+C, then run npx @deepseek-ai/dsh web again.

A model or reasoning option is missing

Refresh the assistant catalog and verify the model configuration in Harness. Reasoning modes only appear when the provider reports that capability.

An assistant cannot be deleted

The assistant is still referenced by a team member. Remove those members or dissolve the related teams first.

No Git changes are displayed

Confirm that the selected Workspace itself is a Git repository. A repository nested inside a non-Git Workspace is not treated as the Workspace repository.

User Documentation

The detailed user guide is available in Chinese:

• Documentation index
• Installation and startup
• Assistant library
• Creating teams
• Workbench and collaboration
• Workspace and Git changes
• Team management
• Troubleshooting

Links

• npm package
• GitHub repository
• Issue tracker

License

MIT