Plugins

LESSONS.md (AI mistake notebook) visualizer panel for DeepSeek Harness Web UI — browse, search and review your AI mistake notebook entries by level and recurrence.

Active wait for background subagents in DeepSeek Harness: registers a wait_subagent model tool that blocks until a named background continuable subagent settles, then returns its stop reason and closing message — optional timeout, membership gate rejects unknown ids, event-driven with zero polling. Closes the gap between run_in_background fire-and-return and the async settlement notice; wait for a background subagent without polling list_agents.

Role-based subagent delegation for DeepSeek Harness: one delegate tool over a folder of role files, with a roster that ships and stays overridable

Native headless and visible Chromium browser automation agent for DeepSeek Harness with DOM tree extraction, screenshot capture, and built-in SSRF protection.

Persistent long-term memory for DeepSeek Harness: a JSON store of typed entries (fact, preference, entity, rule, episodic) exposed as the memory_remember and memory_recall agent tools, with recall ranked by keyword overlap, importance and access frequency.

A headless-first macOS Computer Use driver for DeepSeek Harness with AX-first observations, window-bound multimodal evidence, host-owned approval, and evidence-backed action receipts

Scene-awareness probe for DSH on macOS: a privacy-first, pull-model `look` tool that reads the frontmost non-self window (app info, AX title/selection, gated local OCR), plus a summon-hotkey snapshot captured the instant you press.

Personal-experience memory for DSH: turns solved tasks into sourced problem cases with condition-scoped claims, recalls them into new tasks via hidden pre-step injection, and makes corrections/deletes cascade to future recall.

Context compaction that keeps its receipts: a five-section handoff summary, a durable segment index, review tools that read compacted text back, optional working notes, and a read-only extraction exit. Mounts as the compaction-basic row's replacement; cha

Speaks your agent's reports in a voice you choose, compressing long reports before speaking. Character voices need no training - a 3-10 second reference clip clones one, and community-trained models work too - and no 6.4 GB GPT-SoVITS install: the plugin installs its own runtime and voice. An existing GPT-SoVITS can be used instead, and it is the same voice model.

One-line clock context for DeepSeek Harness: a Current time timestamp reading (weekday, date, time, UTC offset, IANA timezone) opens every conversation turn and a Turn ended reading closes it, so the model always knows the time, date and idle gap across turns without asking.

Humanized fork of @xmanrui/dsh-im (base 4.21.2): humanized message delivery with send-delay and typing two-phase, message_break + streaming coexistence, status reactions, reply quotes, per-bot humanize overrides, and a no_reply reclaim tool — across WeChat, Feishu, DingTalk, WeCom, QQ, Telegram, Slack and WhatsApp channels.

Zen Mode view tab and foreground time tracker for DeepSeek Harness: while the agent works, a calm conversation view shows running/done status, your latest user message, live activity hints and the final AI reply in markdown with one-line turn stats, plus screen-watching (focus) time tracking with daily/weekly Zen scores, a chat-hide toggle that hides tool calls and reasoning rows, auto enter/exit Zen on task start/complete, an Alt+Z shortcut and a Zen settings panel — pure client-side, stored in localStorage, no network.

Skill routing for DeepSeek Harness: embeds skills and each user task with a local model, keeps the clearly-relevant skills with a gap-based selection rule, and auto-injects their full bodies into the prompt.

On-demand memory for DeepSeek Harness: session logs are distilled into layered markdown (a summary, an index and per-topic files), and a mem_query tool returns only the matched entries rather than the whole index. Nothing is injected per turn, there are no dependencies, and every entry keeps a source pointer back to the conversation it came from.

端到端内容智能采集与调研工作流：多源嗅探→四维评分门控→4级深度抓取→键控事实槽矛盾检测（GA11）→网络边界门控（GA12）→跨源融合→结构化 Markdown 报告。DeepSeek Harness (dsh) skill bundle.

An Agent-safe context compressor for DeepSeek Harness. It semantically preserves critical tool outputs such as errors, file paths, JSON payloads and command results, instead of mechanically truncating the context.

Turn approved tracker tickets into review-ready pull requests with DeepSeek Harness.

Deny an AI agent access to .env files, credential stores, keys and any path you hide — across file tools, shell commands, search selectors and run_code. A DeepSeek Harness (dsh) plugin.

Automatic tier-based model routing for DeepSeek Harness: a virtual `smart` model classifies each request by difficulty (hard / normal / easy) and by vision need, then delegates it to the models you already configured. 三级难度 + 视觉自动路由，虚拟 smart 模型零配置接入。

Community DeepSeek Harness plugin: deterministic engineering orchestration with Commander, Executor and Smart Watchdog (CxService + cx_controller tool).

Deterministic engineering orchestration for DeepSeek Harness with Commander, Executor, Smart Watchdog, bounded recovery and durable execution state.

在 DeepSeek Harness 对话中以会话级 artifact 安全展示交互式 HTML 可视化。

XingTu 26 production-grade AI agent skills, packaged as a DeepSeek Harness (DSH) skills plugin — token compression, code review, safe refactor, migration, evidence review & more. 26 个生产级 SKILL.md 技能，DSH 一键安装即用。