dsh-agent-team-presets
Reusable Agent Team presets for DeepSeek Harness: a captain plus members with their own prompt, model, reasoning effort, and tools.
一句话定位
Reusable Agent Team presets for DeepSeek Harness: a captain plus members with their own prompt, model, reasoning effort, and tools.
安装方式
在 DSH 的 web profile 中执行下面的命令;装完刷新页面即可。
$ dsh plugin --profile web add dsh-agent-team-presets@0.1.9
兼容的 DSH 版本
>=0.2.2-rc.1 <0.3.0
作者与热度
bloodarea · ★ 10 · 更新于 2026-11-07
关于这个插件
dsh-agent-team-presets
Concept illustration. See [Screenshots](#screenshots) for the plugin interface; the captain uses the conversation's selected model.
English | [中文]()
> Community plugin v0.1.9 · [Tag](https://github.com/bloodarea/dsh-agent-team-presets/tree/v0.1.9)
>
> This release targets DeepSeek Harness 0.2.2-rc.1 and adds individual member chat: hover a Team in the composer, then select one member to run the Session as that member with its own role card, tools, Team Skills, and model route. It also moves member routing to agent.model.select() and per-step tool admission. Requires Agent Teams; keep 0.1.8 on older hosts. Prebuilt artifacts are included.
What's new in 0.1.9
- Talk to one member directly. The composer's Team picker now shows a member panel on hover. Selecting a member injects its role card, tool policy, Team Skills, and model route into the current Session; selecting the captain keeps the Session model unchanged.
- DeepSeek Harness 0.2.2-rc.1. Member routes are recorded through
agent.model.select()and tool admission is evaluated per step. The plugin refuses an unusable member route before applying anything instead of falling back to the captain. - Custom tool policies are native-only. On PTC presets the plugin preserves the deployment's executor and explicitly refuses custom allow-lists; PTC still works with the all-tools mode.
- Built-in troubleshooting skill. The global
agent-team-presets-troubleshootingskill explains Team application, member creation, route evidence, Team Skill visibility, and install/upgrade failures.
Overview
dsh-agent-team-presets is a visual Team preset and private skill manager for [DeepSeek Harness](https://github.com/deepseek-ai/deepseek-harness). Configure a Team once, assign per-agent isolated skills, then select it from the conversation composer whenever you need it.
A Team contains a captain and any number of member roles:
- The captain uses the conversation's selected model, with its own role description, system prompt, and tool policy.
- Each member can have an independent provider, model, reasoning effort, system prompt, tool policy, and assigned Team Skills.
- The captain summons members through
spawn_team_member; native Agent Teams provides messaging, the shared task board, and runtime coordination.
This is a community plugin, not the Harness's bundled @deepseek-ai/dsh-experimental-agent-team-presets development package.
Why this plugin?
DeepSeek Harness already ships Agent Teams with multi-agent collaboration. In the Harness versions this plugin supports, per-Team configuration, skill isolation, and reuse are still left to the user, which is what this plugin addresses:
- Teams are hard to reuse. In those versions, native teams focus on runtime creation and collaboration, with no visual preset management; this plugin saves, duplicates, categorizes, and reuses named presets.
- Role setup is repetitive. Each role's name, description, system prompt, and tool policies are configured once instead of re-described every time.
- Splitting work across models is awkward. Every member picks its own model and reasoning effort, so one Team combines models by task, while the captain keeps leading on the Session's model.
- Tool permissions have no fine-grained entry point. In those versions the native tool surface offers no per-role allow-list; here the captain and each member carry their own, so roles differ in what they may use.
- Skills lack per-agent scope isolation. Shipped or user skills are typically registered globally, making all skills visible to every agent; this plugin provides a private Team Skill library where skills are discovered only by the specific Agent they are assigned to.
- Switching teams is inconvenient. Pick a preset Team directly from the composer instead of rebuilding roles by hand.
Design principle: native Agent Teams owns collaboration at runtime; this plugin owns configuring, managing, isolating, and reusing teams and their skills.
Features
- Reusable Teams: create, duplicate, edit, select, and delete named presets.
- Per-member model routes: assign models and reasoning effort to individual roles without changing the captain's model.
- Individual member chat: hover a Team in the composer to inspect its captain and members; select one member to inject that member's role card, tool policy, Team Skills, and model route into the current Session.
- Independent tool policies: choose all available tools or a custom allow-list for the captain and each member.
- Nine built-in presets across two series: three software development scale teams (Lightweight, Standard, Full-Stack) and six specialized work-mode teams (Discovery, Planning, Workflow, Engineering, Security Audit, Research).
- Display metadata: attach summary, tags, use cases, quick prompts (suggested tasks), and notes per Team. Strictly presentation-only: never injected into the runtime LLM context, saving context tokens.
- Local categories and search: organize presets into custom categories via a dedicated category manager; instantly search over name, summary, tags, and use cases in both Settings and the Composer picker.
- Private Team Skill library: import skill folders or ZIP archives into a plugin-owned store (
~/.dsh/agent-team-presets/team-skills), completely isolated from global host skills. - Per-agent skill isolation: a 3-column assignment grid on member pages assigns skills to specific roles. Assigned skills are registered strictly in that Agent's scope when summoned—never leaked globally.
- Official built-in skills & local overrides: ships two delivery skills (
github-repository-presentation,git-release-hygiene) and two method skills (grilling,research), materialized into the private library and pre-bound to engineering, discovery, and research roles. Create local editable overrides and o
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