Plugins

Preset engineering workflows for DeepSeek Harness: a dev_task tool that gates stage transitions, artifacts, verification, review and commit scope, plus a web workbench for installing project or user skills and rules.

DeepSeek Harness 智能看板：任务卡片 + 一次性 Worker/Verifier 派发 + 依赖调度 + 管线分档 + Team 模式（歧义上报主窗口裁决）

Persistent, cross-session multi-agent team rooms for DeepSeek Harness — members, a message bus, a shared task board, and a shared timeline that survive restarts.

Lifecycle orchestration engine for AI agent teams with task-scoped Git worktree isolation, state-gated delivery transitions, and off-context memory.

Graceful restart + client auto-reconnect + cross-restart goal continuation for DeepSeek Harness (dsh). After a plugin update dsh-phoenix restarts dsh at a safe idle boundary, keeps the browser page connected, and resumes a running goal so a task can keep

Multi-model orchestrator: the main brain decomposes complex tasks and dispatches subtasks to GLM / Kimi / Qwen sub-agents by each model's strengths, with per-model token usage.

Runs one-time and RFC 5545 recurring Agent tasks in fresh DSH sessions, with visual schedule editing and session-linked history.

DSH Desktop enhancement plugin: it puts verifiable facts on the table. Constraints are injected only when relevant, so idle chat costs no extra tokens; injection is layered (session-stable text in the system prompt, volatile content as a tail snapshot) and the prompt cache stays valid. Discipline: each turn is classified (question / research / discussion / diagnosis / execution) with boundaries enforced - no file edits on question turns, no unsolicited fixes on diagnosis turns; citing code lines not opened this session, negative claims about unseen symbols, requirements that do not match the deliverable, and dressing up “I did not check” as “waiting for your decision” are all called out; replies are written for humans - a code, field name or id must be explained in plain words the first time it appears. Memory and knowledge: 75%/90% context warnings plus an exported session recap (say "continue" in a new session); project knowledge accumulated across sessions by working directory, auto-captured and deletable by id. Inspectable artifacts: task contract / change record (auto-logged, unverified items flagged at delivery) / hypothesis record (conclusions must pass an evidence gate) / design decisions. Dashboard and personas: routing, trigger hits and block assembly are written to lume-metrics.jsonl and queryable via lume_metrics; personas are distilled from chat logs, novels, scripts or character sheets, with long-term and temporary memory, a memory star map and persona card export/import.

DeepSeek Harness plugin that aggressively saves tokens without affecting task quality: lossless head/tail truncation of tool results (default), grep-result folding, pressure-triggered dsh-compaction-basic delegation, and an LLM-summary CompactionEngine subclass for the aggressive mode. Saves 97.6% of input tokens on an 8-scenario synthetic suite, with all reductions routed through dsh event flow so model-visible = logged stays intact.

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.

Windows system and custom desktop notifications for DeepSeek Harness events: task completed, failed, running, awaiting approval, and awaiting answer. Click-to-jump to the session.

Proactive multi-model scheduling plugin: multi-source signal intake with dedup and urgency ranking, a four-way execute/defer/dismiss/ask-user decision engine, DAG plan generation with parallel model execution, quality reflection with automatic retry and model switch, long-term memory for task patterns and lessons, and strategy evolution via genetic algorithms with sandboxed evaluation and canary rollout.

Kanban board for DSH: task state machine with git branch isolation, agent auto-execution, and review-driven merge.

Per-workspace completion ringtones plus attention sounds for approval, question, plan-review, goal-blocked, and task-failure events, with built-in synth, voice (TTS), and custom audio.

Adds specification artifacts, skills, commands, goal-backed implementation, and task-progress context.

Embedded task management engine: decision-point protocol, idea capture wall, Linear-style issue store.

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

Pairs two DeepSeek Harness machines with a one-time code - directly on a LAN, or across networks through an end-to-end-encrypted relay with a zero-config official default - so one agent can run tasks and exchange files on the other while each machine keeps its own files in place.

Agent-structured prompt optimizer for DeepSeek Harness: rewrites composer drafts into role/task/context/constraint/format with normal, slim, and expand modes, a confirm modal with score, continue-optimize, and local, hybrid, DSH, or cloud-API engines.

Advisor reviews that converge over rounds, an engineering mode whose writes require a design token, escalation of a task to a stronger model, and parallel multi-model consultation; a settings page edits the model routes, timeouts and budgets.

DeepSeek Harness bridge/plugin for A2S with remote sessions, workspaces, approvals, tasks, and resilient reconnects.

Model switching and reasoning-effort control for DeepSeek Harness: set_model and list_models agent tools let the agent autonomously change its provider, model or thinking depth (reasoning effort) mid-task with a mandatory reason, a provider whitelist and a context-window token-pressure guard, the active model is injected into the runtime context, and Plan Mode auto-transition switches to a configured planning model on entering plan mode and restores the previous execution model on exit.

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

Feishu/Lark gateway for DeepSeek Harness with topic-persistent conversations, live execution cards, image and file inputs, in-chat approvals and questions, source allowlists, and durable one-time or recurring agent tasks created in natural language.