Plugins

Six engineering skills for Claude Code and DSH: research, architecture scouting, implementation orchestration, three-axis diff review, complexity audit and mutation testing. Skills delegate through the host’s generic subagent tools when available.

Supervisor-style workflow orchestration over top-level sessions: confirmation-gated batch dispatch, team workstreams, steering running tasks, idle-wait collection and live model-route discovery across 11 task_* tools plus a /tasks slash command.

Commander mode for the dsh web GUI: a one-click session header button injects a protocol brief into the session, then parses and auto-executes task blocks in the model reply — separating the strategist loop from worker loops via a visible badge.

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.

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.

Host-side orchestrator for DSH agent teams. Every turn it injects an 11-section orchestration methodology into the system prompt and backs it with a counting tool-layer gate, so parallel dispatch, task-board tracking, cross-session handoff, employee-pool reuse and preset routing become the default in any preset and any session instead of something you have to ask for. The gate counts real dispatches (subagent / subagent_fork / spawn_teammate) rather than words: a todo listing N unmarked items only needs the base threshold, items explicitly marked as parallel must be launched in one batch up to a configurable cap, and a genuine single-step task is exempt by writing one marker. Read-only tools (read, glob, grep, context-management tools) are never gated. Team members are woken up and reused before new ones are hired, and subagents are reserved for work that must run under a specific preset. Local-only settings (preset routes, domain keywords, profile name, active tier) live in <DSH_HOME>/team-orchestrator.local.json and never ship inside the package. Status is exposed on a loopback-only HTTP route. Zero telemetry, no hosted service, no account. Adapts DSH kernel 0.2.2-rc.1.

HarmonyOS delivery orchestration for DSH: freezes a four-dimension acceptance pack whose measurable criteria carry machine-checkable assertions, runs an adversarial pre-review before dispatch, hands the work to DevEco Code in Goal mode, then audits the delivery with independently gathered evidence (screenshots, UI tree, logs, hashed evidence bundle), recomputing assertion verdicts against measured values and filing rework orders; includes a cited rule catalog, a user-confirmation state and a gate calibration ledger.

Multi-agent agent team of employee AI subagents for DeepSeek Harness — dsh-company: employee management, CEO bidding, n8n workflow orchestration, drag and drop canvas. DeepSeek Harness plugin with seven built-in roles (project director, product manager, tech lead, engineer, data analyst, QA, reviewer), each with its own persona, model and tool whitelist. Broadcast a mission and the employees bid for it themselves — the first line of their answer must be 【accept】 or 【decline】 — so accepted work runs in parallel instead of down a pipeline. The workflow canvas wires employee nodes with the start node, references each upstream result with {{input}}, and runs the graph in topological layers: parallel across employees, serial per employee, downstream skipped when upstream fails. Ships a web panel for the employee management tab, the mission board and each employee's transcript, the /dsh-company slash command, a live mirror into the built-in agent-team panel, deletable missions, and a private memory directory per employee.

Control plane for the harness's own Agent Teams: members are ordinary independent sessions created through the same seam the GUI uses, each with its own model, so they open and continue like any other conversation while a sidecar roster and task board coordinate them. Task entries carry a definition of done, a member's completion is submitted and waits for the Lead's review, and availability tells idle apart from awaiting-review or a failed last turn. With delegationEngine=auto it uses independent sessions, continuable subagents, or the kernel roster depending on what the composition provides.

Agent plugin for major harnesses — DeepSeek Harness (DSH), OpenCode, Pi and Codex: define custom AI agent roles with per-role prompts, models, skills, permissions, memory and multi-agent orchestration.

Route each task to one model and its review to a different one, with qualification evidence, failover and a durable journal.

dsh plugin + agent preset that replicates opencode + oh-my-openagent (omo): opencode's toolchain and system prompt, omo's multi-role subagent orchestration, and browser-side omo role selection + per-role model/fallback settings.

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。

OMC-style multi-agent orchestration for DeepSeek Harness: 29 omd-* skills and 12 /omd-* slash commands over the plan-execute-review-verify pipeline and team/autopilot/ralph modes.

An RTS-style orchestration dashboard where commands replace chats: a resident commander agent decomposes each order into task briefs with acceptance criteria, typed subagent troops (recon/engineer/medic/scribe) execute them across isolated workspaces, and every session is indexed by the order that started it.

Conversation Flow observability for DeepSeek Harness swarms, with topology, routed-message inspection, HITL pauses, Live follow, and child-session navigation.

Config-driven development-task orchestration for DSH: graph workflows (task/gateway/human nodes) with per-stage persistence, plus an in-editor AI assistant that configures workflows through conversation with live validation. Hand documents to nodes as generic attachments (no declaration needed): files land in the task workspace and ${inputs.附件} gives the newline-joined absolute paths, so a node parses them with its own prompt.

Multi-agent orchestration for DeepSeek Harness -- specialized agents, task orchestration, workflow skills

Local-first AI project orchestration workbench and CLI plugin for DeepSeek Harness: approval-gated planning, Git worktrees, task execution, Issues, and auditable evidence.

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

Rigorous open mathematics research suite: four agent skills (rigorous-open-math-research, manage-math-research-program, math-research-workflow, lean-verify) for theorem solving with adversarial audit, research program management, pipeline orchestration, and Lean 4 formalization audit; CI-verified tests and mechanical upstream sync.

The unofficial Simplified Chinese fork of the tri-agent agent preset (Atlas orchestration plus Prometheus planning), packaged for DeepSeek Harness as a Cordis bundle; the vendored upstream content is licensed under SUL-1.0.

Picks each subagent model from the local catalog by task category, unless the caller already named one. Free and quota tiers are ranked together by per-model capability tags; a pricier model is used only when no cheap model is tagged as good at that kind of work. Only providers whose remaining balance is readable, or that are account-backed, enter the candidate pool; the rest stay listed but are not routed. A panel adds per-model manual priority above the automatic order plus allow/revoke controls.

Picks each subagent model from the local catalog by task category, unless the caller already named one. Free and quota tiers are ranked together by per-model capability tags; a pricier model is used only when no cheap model is tagged as good at that kind of work. Only providers whose remaining balance is readable, or that are account-backed, enter the candidate pool; the rest stay listed but are not routed. A panel adds per-model manual priority above the automatic order plus allow/revoke controls.