为 DeepSeek Harness 提供电脑控制插件：新鲜 Accessibility 观测、过期状态拒绝、作用域权限与安全输入（目前支持macos）｜Accessibility-first macOS Computer Use bundle for DSH with fresh observations, stale-state rejection, scoped permissions, and safe input.

Prompt enhancement for the dsh web GUI: rewrite the composer draft into a well-structured prompt through the harness LLM service, preview the before/after, then fill back, copy, or undo. Original draft is always preserved.

Manage DeepSeek Harness system-prompt sections from the Web GUI: enable, edit, and subscribe markdown prompt entries, switch named presets from the composer, feed them machine facts as {{variables}}, replace the instruction DSH sends when it compacts the

DSH 插件 · 注入式优化器 0.7（主线）：你照常说话，它在你发送后,AI接收前把"这一轮到底要什么"理清楚，再把这份理解交给工作 AI(上下文注入) —— 原话不改写，条条带逐字依据。含控制界面（档位/权限/模型/上下文/只读工具）、拦截浮层（思维层+产出层）与真实 token 用量。可明显提升大多数模型的发挥稳定性,尤其DeepSeek-V4.1-Flash,可有明显提升

DeepSeek Harness (DSH) 插件：✨ 提示词一键增强 + 💬 语音识别（说完自动停·云端/本地双引擎）· 附 🔁 服务异常一键重启

DeepSeek Harness plugin for insert custom prompt

DSH Web 输入体验增强插件：可配置发送/换行键位 + 自定义输入框右键菜单 + 面板尺寸记忆 + 快捷指令（分类 / 跨分类移动 / 关·每次·仅首次三种插入模式 / 存 ~/.dsh/quick-prompts.json）+ 提示词优化（0.11.1 起工具行有独立「优化」按钮、带秒表与斜杠命令保护、写回前比对草稿） + OpenCode 会话请求头 + Windows 默认终端切换（把模型的 PowerShell 工具换成 Git Bash）+ 官方持久终端六件套（terminal_open/r

DeepSeek Harness 破甲：让所有模型都能破甲，不同模型可换不同提示词；默认提示词面向国模「小码酱」。Jailbreak for every model — swap prompts per model. 求 Star 收藏 ⭐

Local security audit for AI API relays and LLM proxies: detects prompt injection, model substitution, tool-call rewriting, SSE anomalies, error leakage, and Web3 wallet risks.

AI image studio for DeepSeek Harness — generate, edit & compare images in chat, with 500+ prompts, gallery, multi-model workflows and ComfyUI.

在 dsh 里装上这个插件即可，无需登录、注册或填 API Key，就能使用包括 Muse Spark 1.3、MiMo V2.6 在内的前沿模型——完全免费，不限量。 All you do is install this plugin in dsh: no login, no sign-up, no API key — the frontier models are just there, Muse Spark 1.3 and MiMo V2.6 among them. Completely free, with no usage cap.

Desktop-native BigFish companion for DeepSeek Harness — real Agent status, always on top on Windows.

基本稳定可用 A context-compression plugin for small context windows (a 100K context is enough), token savings (5x fewer tokens), and month-long single sessions (billions of tokens).上下文压缩插件，兼顾小窗口(100k上下文足矣)省token(省5倍token)和超长会话(数月级别几十亿token单会话)。billion-context is all you need

Industry and company research domain pack for DeepSeek Harness: methodology skills, industry chain mapping, public-source policy/news tracking, company research cards, and auditable research reports. Research only - not investment advice.

Model-driven context management (Active Context Pruning / ACP) for the DeepSeek Harness — the model decides when and what to compress. Ported from billion-context-pi (ranxianglei); acp-kernel reused verbatim. CompactionEngine backend with compress/decompress/search_context/acp_status tools.

Prompt as Code | GPT Image 2 / 2.5 提示词与案例库，530+ 个案例、20+ 套工业级模板与可复用 Skills，新增 2.5 同提示词对比专区，附完整提示词与生成记录，持续更新。

让 Agent 的工作方式可组合、可审查、可持续改进，最终实现 Agent Self Evoling。 DeepSeek Harness Web plugin with composable task controls and isolated, human-reviewed self-evolution.

本项目整理了用于生成[炫酷 HTML 动画网页]的 AI Prompts，涵盖动画效果、3D 可视化、PPT 风格演示、UI 美化等多个类别。

Local first, desktop companion platform with animated pets, plugin SDK and coding-agent integrations.

Voice input for DeepSeek Harness: dictation chunked by pauses and voice messages, each with its own provider fallback chain (Deepgram, Groq, HuggingFace, local whisper.cpp, plus any OpenAI-compatible API of your own).

Fork of @deepseek-ai/dsh-agent-instructions that delivers the workspace instruction baseline as system-prompt sections, keeping the upstream mid-session reminder path.

DeepSeek Harness companion for ClineBot / ClinePass: dynamic subscription models sync, quota exhaustion warnings, session metrics, dedicated settings page, live usage limits, and /cline slash-command.

Custom modes and custom prompts for DeepSeek Harness (dsh): edit a mode's system prompt on the settings page (it takes effect on the next model step), pick its base mode, switch plugin rows one by one, and keep several assistants side by side — coding, ch

Compare multiple skills on the same task and pick the winner.