Plugins

Durable multi-agent collaboration for DeepSeek Harness with channels, threads, tasks, and resumable agent sessions.

A-share multi-agent analysis behind /trading-agent, ported from TradingAgents-AShare, running 14 roles (analysts, bull/bear debate, risk review, trader) through the harness LLM route.

DSH-native Tower: mission planning, worktree isolation, review-gated merges, and a human-owned Tower mode.

Adds six AI coding platforms to DSH — OpenCode, Qoder, Qoder CN, TRAE, WorkBuddy and WorkBuddy International — each as its own group in the native model picker, and manages their accounts from one settings page, with daily check-in where the platform has one, credit balance lookups, and retry on another account of the same platform when one is rate-limited. Models carry their credit multiplier where the platform declares one. OpenCode's anonymous free tier works with no credential, and TRAE stays hidden by default until it is enabled in the settings.

Multi-agent roundtable discussion: each member runs as a subagent on its own model and speaks in turn, a host summarizes each round, and termination writes meeting-minutes Markdown.

Adaptive topology multi-agent preset for DeepSeek Harness with peer messaging, task handoff and live network visualization.

Chinese multi-agent workflow with per-role model fallback, versioned Mermaid task plans, independent Agent and Jev reviews, persistent expert collaboration, and pure-function calculation tools.

Persistent Endeavour and Challenger peer sessions for DeepSeek Harness that plan, execute sequential tasks, and verify reported results.

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.

Cross-session agent-to-agent messaging for DeepSeek Harness — address another session by name and deliver a message into its inbox.

Loopback-first multi-agent message relay: HMAC-authenticated broker plus dsh plugin (relay_send/recv/peers/history), zero-dependency CLI and Python clients, wire protocol v1.0.

Assigns a model and reasoning effort to each Agent Teams teammate, from the chat toolbar or a settings page.

Frontend GUI debugging and testing for DeepSeekHarness agents: 36 browser_* tools for structured GUI automation, visual comparison, dynamic frame analysis and network debugging on Web/Chromium.

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.

Durable task-decomposition plans for DeepSeek Harness with a self-learning loop: every department subtask runs in three ordered phases (plan, execute, verify), the verify phase must submit a retrospective of problems, detours and resolutions, and that retrospective is written to a permanent lessons file, ranked against the new subtask and injected into later dispatches so the same mistake is not repeated. Adds a read-only dsh_workplan_lessons tool (11 model tools in total), a progress panel drawn as a ring, a stacked bar and per-stage steps, and a public ISO/IEC 15408:2026 security self-assessment with zero runtime dependencies.

Autonomous AI assistant and multi-agent collaboration for DSH: discuss goals, plan work in the background, coordinate multiple Workers to execute tasks and review results, pause and resume work, recover after interruptions, keep task history and deliverables, and build working memory and skills; offers a standard local mode and optional experimental private-Git collaboration.

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.

Hierarchical multi-agent team coordination with lead review gates, write-scope isolation, and floating workspace.

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.

Desktop notifications for DSH: a system toast, a per-kind chime and a tab-title marker when the agent needs you (approval, plan review, question) or a reply finishes in the background; errors, interrupts, usage limits and multi-agent workflow progress alert too. A host half adds SSE delivery, webhook push (WeCom/Feishu/DingTalk/generic), per-turn token/cache/TPS stats, plus three message-format presets (concise, detailed, custom); settings changes auto-save.

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

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。