Plugins

baro as a DeepSeek Harness subagent provider: delegate a multi-story goal, get parallel execution, independent review and a verified outcome back — with a live run panel in the sidebar

Agent Teams for DeepSeek Harness: hand work to a team of agents that carries it end to end while you set the direction and hold the gates. Agents claim Tasks, hand work to each other, and have someone other than the builder verify it.

A persistent agent team for long-running collaboration in DeepSeek Harness: durable agent identities, per-project Workspaces, responsibility-bearing Channels, and Task Threads chaining session agents.

Role-based multi-agent team for DeepSeek Harness — your digital workforce. One goal assembles a team of product, architect, frontend, backend, reviewer and QA roles that deliver through a nine-phase gated pipeline, plus a persistent team you can keep directing across sessions. Zero runtime dependencies, no build step.

Coordinate independent DSH Sessions and provider-backed members without merging their histories, using persistent native Rooms with identity-bound leading `@` mentions, direct delivery, broadcasts, and leader-scoped controls.

femo (Flow Emerges Mag Opus) — 用写剧本的方式编排多智能体世界。dsh 插件版：引擎、桥接器、可视化编辑器全在一个文件夹里，自包含，整个文件夹搬走即用。

Runs AItelier pipelines from DSH over MCP: 39 tools (22 read, 17 write) to generate, run, inspect, edit, export and import multi-step SkillFlow pipelines. The steps execute in AItelier rather than in the DSH session and are polled by run_id, pause at engine-enforced checkpoints answered with answer_checkpoint, and leave per-step traces and step outputs to read afterwards; add_provider / map_model / edit_role point an individual role at a local or cheaper endpoint. Bundles an aitelier-pipelines skill.

Adds persistent execution contracts, recursive work graphs, critical clarification, and evidence gates for long or underspecified Harness tasks.

Use AItelier as a subagent from DeepSeek Harness: generate, edit, run, export and import SkillFlow pipelines. Client only — requires a running AItelier backend (Docker; see README).