NanmiCoder/dsh-agent-teams

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One prompt. A working team.

dsh-agent-teams turns the current DeepSeek Harness session into a captain that can assemble durable sub-agents, split a goal into dependency-aware tasks, and coordinate work through direct messages.

Ask in natural language. The plugin provides the team protocol, ten coordination tools, persistent state, an automatic shared-task scheduler, and a live Web UI—without requiring a separate workflow engine.

Why AgentTeams?

Install

[!NOTE] Requires an existing DeepSeek Harness installation.

npm

dsh plugin --profile web add @nanmicoder/dsh-agent-teams

Build from source

git clone https://github.com/NanmiCoder/dsh-agent-teams.git
cd dsh-agent-teams
pnpm install
pnpm build
dsh plugin --profile web add .

Run pnpm build again after changing the source. The local plugin install remains linked to this checkout.

Validate the composed profile, restart DSH, and refresh the Web UI:

dsh --profile web --dump-config
dsh web

Then ask for a team directly:

Use AgentTeams to review the commits after v0.5.3 from performance, security, and product perspectives. Return one consolidated report.

How it works

1. The current session creates a team and becomes its captain.
2. The captain adds role-specific members backed by continuable sub-agents.
3. The goal becomes tasks with owners and explicit dependencies.
4. The shared scheduler uses real running / idle / ready state to atomically claim one ready task per idle member and wake it. If an idle/ready member still owns an open task after an interrupted turn or process restart, the scheduler retries it with a fresh attempt.
5. Members update with the current attempt_id; reassignment or captain takeover revokes the old attempt and waits for the old worker to quiesce before a new attempt starts.
6. The captain presents the combined result, then archives the complete team record.

Team state is stored under <workspace>/.agent-teams/; the Web panel reads that disk truth and combines it with live sub-agent activity.

Member creation is zero-interaction by default: a member on the captain’s current LLM route snapshots that provider, model, and reasoning effort, while a member on a requested alternative route snapshots the target model’s default effort; later continuations restore the resolved snapshot. Only an explicit heterogeneous-team request (for example, “backend on provider A/model X, frontend on provider B/model Y”) supplies a member-specific provider + model; there is no per-member model or reasoning prompt.

Slash command

No “use AgentTeams” phrasing required. The plugin registers the closed-namespace /agent-teams host command, so the Web GUI slash menu shows an agent-teams placeholder with an input hint: pick it (or type the command), describe the goal, and press Enter.

/agent-teams research the pricing pages of three competitors

The line is claimed by the command pipeline and never reaches the model as plain text — the handler queues one deterministic activation message as an ordinary follow-up turn, so the captain protocol starts immediately. The invocation is durably logged (command/run / command/done).

Surfaces without command adjudication (for example the headless CLI) get the same deterministic activation through a gesture boundary: any genuine user message starting with /agent-teams activates the protocol for the rest of the text. Mid-sentence mentions stay ordinary prose.

Configuration

Defaults work without extra setup. A trusted profile can override member behavior:

- id: agent-teams
  config:
    stateDir: .agent-teams
    memberProvider: spawn
    memberModel: deepseek-v4
    memberMaxDepth: 1
    maxMembers: 8

memberProvider is the sub-agent runtime backend (spawn / fork), not an LLM provider. Cross-LLM-provider routing uses the optional provider + model fields of agent_teams_add_member; memberModel is only a model default for all members. A member on the captain’s current provider/model inherits the captain’s reasoning effort, while a changed provider or model automatically uses the target model’s default. To request a particular effort, pass the optional reasoning_effort field — one of the target model’s supported effort ids, or "default" to force the model’s own default.

slashCommand: false disables the deterministic /agent-teams activation surfaces (slash command and gesture boundary), leaving the natural-language trigger as the only entry point.

Boundaries

• One captain leads one active team at a time.
• Idle members are automatically reused for ready work; messages that cannot be delivered live remain durable and are retried at a later status boundary.
• State is file-backed and serialized within one DSH process; concurrent processes editing the same team are not coordinated.
• The activity panel reports persisted state as-is. Models may occasionally finish work without performing the expected task-state update.

See docs/usage.md for the full tool reference, state model, Web UI behavior, configuration, and known limits.

Plugin development Skill

The repository also ships the open Agent Skills package dsh-plugin-development:

npx skills add NanmiCoder/dsh-agent-teams --skill dsh-plugin-development

Documentation

Development

pnpm install
pnpm build
pnpm verify

License

MIT