deepseekplugins

DeepSeek Harness plugin

dsh-cluster

Cluster mode for DeepSeek Harness: canvas node-graph, multi-agent orchestration, and flow-constrained message routing

Workflow & Automation
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Source facts

Repository
Lanxi26/dsh-cluster
Latest update
Aug 14, 2026
Category
Workflow & Automation
GitHub stars
2
Format
plugin
Catalog evidence
Upstream dsh.bundle evidence
Evidence path
package.json#dsh.bundle
Checked against
0.1.0-rc.8
Upstream check date
2026-08-20

This evidence comes from the upstream catalog. This site has not installed, run, or security-reviewed the plugin.

Install

Start with a prompt that asks an agent to review the GitHub repository and source. Switch to the command if you want to install it yourself.

Copy this prompt into DSH, Codex, or another agent and ask it to review the GitHub repository and source first.

Do not install or run any commands yet. Read this plugin's GitHub repository, README, and relevant source code. Then answer the questions below clearly and directly so I can decide whether it fits my needs:

1. What is this plugin, and what problem does it solve?
2. Who is it for, and what are its typical use cases?
3. How is it used after installation? Include one minimal example.
4. What known limitations or privacy, security, compatibility, or maintenance risks does it have?
5. Give a clear recommendation: recommend, conditionally recommend, or do not recommend, with reasons.

Distinguish statements documented by the repository, inferences from source code, and unknowns. If evidence is insufficient, say so explicitly. Do not guess or simply repeat the README.

GitHub: https://github.com/Lanxi26/dsh-cluster
Plugin: dsh-cluster
Author: Lanxi26

Check the source files

Read the README and other files from this plugin directory before installing.

File explorer4 files
README.mdSource · read only
README language

DSH Cluster Plugin

Cluster mode for DeepSeek Harness — a canvas node-graph for orchestrating multi-agent collaboration and information flow. Every node is an agent (with its own name, persona, and mode); the directed edges between nodes decide who can message whom.

中文文档

![DSH Cluster Plugin](images/banner.png)

The canvas

![Cluster canvas](images/board_en.png)

The three tools

![Cluster tools](images/describe_en.png)

  • cluster_view — shows all running agent instances (sessions) and agent categories, so you can see who is available to receive messages.
  • cluster_spawn — creates a brand-new instance of an agent category and delivers a first message to it (each call makes a fresh, memory-less instance).
  • cluster_send — delivers a message into a specific running instance's inbox, which it processes like a new user message.

Features

  • Canvas node-graph — add nodes, connect edges (one-way / two-way / none), bind agents, rename.
  • Agent management — each agent has a name, prompt (persona), mode, and optional space; auto-saved to $DSH_HOME/cluster-agents/<id>/agent.json.
  • Information-flow constraints — edges are directed and deny-by-default: only declared flows may cluster_send/cluster_spawn; an empty graph is fully open.
  • Three agent modes:

- single — address it with cluster_send (its most recent running session). - multi — address it with cluster_spawn (a fresh instance each time). - any — either.

  • Export / load — export the graph and agent properties together (.txt JSON, v2), then load them elsewhere to restore agents and write them back to disk.
  • Identity space — optionally attach a disk directory to an agent; its persona is told to browse that space first. Since the Agent panel on the canvas is intentionally simple, richer materials — Skills, scripts, long-term memory, personality files, agent.md, etc. — can live in each agent's own space.

Install

Prerequisite: the profile already has the official @deepseek-ai/dsh-base + @deepseek-ai/dsh-web-app bundles.

dsh plugin --profile web add @lanxi266/dsh-cluster-plugin

Start it:

dsh --profile web web   # or `dsh web`

Quick start

1. Open dsh web and click the cluster icon in the bottom-left corner to open the canvas. 2. In the Agents bar, add an agent (e.g. id math_teacher), give it a name and persona, pick a mode. 3. Double-click the canvas to add a node, bind it to an agent, then connect nodes (drag A → B means A can message B). 4. Enter a node: the agent receives your persona plus a workflow hint, and uses cluster_view / cluster_send / cluster_spawn to collaborate. 5. The last link (whose cluster_view shows only itself) is told to produce the final result directly, so the pipeline terminates.

How information flows

  • An edge = an allowed flow. A → B means A can message B; B cannot message A back (unless the edge is two-way).
  • cluster_view only shows yourself + your downstream, so a downstream agent cannot see upstream — it can only pass messages further down.
  • No edges = fully open (handy to try things out before adding constraints).

Packages

PackageRole
@lanxi266/dsh-cluster-agent-fsHost filesystem service: reads/writes agent.json, persists the graph, exposes the Remote endpoints
@lanxi266/dsh-tool-clusterHost tools: cluster_view / cluster_send / cluster_spawn + persona injection
@lanxi266/dsh-client-ui-clusterBrowser canvas: cluster icon, node-graph, agent editor
@lanxi266/dsh-cluster-pluginbundle: just a cordis.patch.yml that inserts the three rows above into a profile

Requirements

  • Node ≥ 22.19 (official DSH requirement)
  • Official DSH runtime: @deepseek-ai/dsh-base, @deepseek-ai/dsh-web-app (the @deepseek-ai/dsh-* series is provided by DSH itself)

License

MIT

Note

The author is a Java programmer, so this project was completed by DeepSeek-V4-Pro-High, costing 36.62 RMB / 5.39 USD (before the price increase). There may be many bugs — please be understanding, and feel free to fix bugs locally with Vibe-Coding. This project is open-sourced under the MIT license.

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