v0.1.0 · MIT
Harness engineering beginner tutorial, from 0 to 1
v3.11.2 · MIT
An omni-plugin for harness engineering workflows with multi-agents, programmatic gates and skills.
v3.26.5 · MIT
The first vision plugin for DeepSeek Harness, and the vision bridge for every text-only coding agent. Paste an image, get structured JSON evidence (OCR, layout, semantics). | 全网最强 DeepSeek Harness 外挂视觉插件,为 DeepSeek、GLM 等纯文本模型外挂视觉能力,粘贴图片即得结构化 JSON 证据(OCR、版面、语义)。
v5.10.5 · MIT
🥇 The strongest free web search plugin for DeepSeek Harness, and the search bridge for every model without native web access. Free, no signup, no API key. Ask the web or X, get structured JSON evidence. | 🥇 全网最强的 DeepSeek Harness 免费联网搜索插件,免费免注册免 API key。为不能联网的模型补上搜索,问网页或 X,拿回结构化 JSON 证据(搜索、抓取、引用)。
v0.3.8 · Apache-2.0
Local-first, self-hosted AI agent runtime and MCP bridge with sandboxed sessions, memory, credentials, audit/replay, and a local Console.
v1.0.0-rc.2 · Apache-2.0
官方 DeepSeek Harness 的交互式终端 UI 插件:自研 ANSI 极简交互渲染、流式 Markdown/工具卡、16+ 主题、slash 命令与选择器、输入历史与本地偏好持久化、LSP 诊断、memory记忆,很丝滑的开发体验。
v0.2.5 · MIT
A portable memory protocol for AI agents — load it as standing rules; a curation discipline + reference spec + optional cap hook.
v1.0.0 · MIT
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。
v0.0.0 · Apache-2.0
A control plane with a durable state kernel for long-horizon agents and teams. Keep work moving and improving across sessions, with less human attention.
v0.8.0-preview · BSD-3-Clause
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
v0.4.1 · MIT
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.
v0.1.0 · MIT
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。
v1.11.5 · MIT
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
v0.3.0 · MIT
Claude Code-style auto-memory plugin for DeepSeek Harness (dsh): typed memory files + MEMORY.md index auto-injected into the system prompt. File-only, no external services.
v1.0.0 · MIT
AI skills大全 mcp ai知识库 Agent 全维度 AI 资源百科,DSH插件 收录大模型、智能 Agent、RAG 检索增强、多模态、MLOps、AI 应用工具、AI面试集、Vibe coding 大全、零基础学习路线,持续更新前沿 AI 开源项目,开发者一站式 AI 导航库
— · AGPL-3.0
Memory library for building stateful agents
— · MIT
Agent OS: the agent gets smarter on its own. We just hold the line: Interview-gated, staged evaluation, budgeted evolution loop. MCP server, 14 runtimes: Claude Code, Codex CLI, Gemini CLI, OpenCode, Copilot, Kiro and more.
— · Apache-2.0
Intelligent Skill routing and workflow orchestration for AI agents — +21.12 pp reward, −29.6% tokens on SkillsBench with DeepSeekV4Flash-VE.
v0.1.0 · MIT
Your thinking deserves a map: an infinite canvas where LLM conversations grow into an editable thought graph. Wires are the context.
— · MIT
为纯文本模型"看图“设计更好的视觉工具箱和技能,支持多图理解,图片问答,前端UI还原、GUI 自动化等,并可选无缝接入多个主流agent,直接识别粘贴图片| A vision toolkit and skill designed for text-only llms — image Q&A, long-screenshot OCR, frontend UI restoration, and GUI automation, with optional seamless integration for Codex, Claude Code, Pi, Oh My Pi, and OpenCode
— · Apache-2.0
ANOLISA (Agentic Nexus Operating Layer & Interface System Architecture) | Agentic OS with runtime, security, observability, and Tokenless response compression for lower token usage and cost.
v3.1.0 · MIT
Reverse engineer anything with agents, from app behavior down to native binaries.
v0.4.5 · MIT
Cross-agent plugin for manually excluding and editing AI conversation context, with search, filtering, hide/restore, undo, and original Session preservation.
— · MIT
Runtime evidence that helps agents trace, profile, and burn down hotspots in application and native code, GPU kernels, and inference stacks.