pengpengyi92/dsh-quant

Name: pengpengyi92/dsh-quant
Author: pengpengyi92

Plugin插件 Native原生 ⭐ 47 MIT Models & Routing模型与路由 Data & Analysis数据与分析

🐳 Dsh-Quant：全能型AI原生量化操作系统

Project Overview项目介绍

Edited by Zhiwei Agent (zhiwei)由知微Agent(zhiwei)编辑

dsh-quant is a native DSH plugin built exclusively for the DeepSeek Harness ecosystem, focused on AI-native algorithmic trading and quantitative research. It ships 59 tools across six core domains, including market data, alpha factors, machine learning models, risk management, trade execution, and ecosystem management. It follows DSH’s "everything is a plugin" philosophy, splitting core functionality into five separate pluggable modules that users can extend or replace to fit their own research needs. To install, you can get it via one-click install from the DSH marketplace, or pull it directly from npm into your existing DSH installation.

This plugin is designed for quantitative researchers and AI agent developers who want to build an end-to-end quant research pipeline with AI support. Because it is AI-native by design, all tool schemas are written from the LLM agent’s perspective, allowing agents to automatically load workflows and call tools in parallel without state conflicts. Users can start with the default open framework, plug in their own private data, custom alpha factors, trained machine learning models, and custom risk limits to build a paper trading or live trading system that fits their personal research goals.

dsh-quant is written entirely in TypeScript and runs on DSH’s built-in Node.js runtime, with zero runtime dependencies. All core numerical calculations are implemented as pure functions, and every method includes hand-computed baseline tests that can be run offline to verify correctness. It is released under the permissive MIT license, and is available via npm as well as the DSH plugin marketplace for one-click installation. Only the framework and modular design rules are open-sourced; users keep their own internal research strategies and private data completely confidential.

dsh-quant 是专为 DeepSeek Harness (DSH) 开发的原生量化投资插件，提供覆盖数据、阿尔法、机器学习、风险、执行、生态六大领域的 59 个工具，遵循 DSH「一切皆插件」的设计哲学，将核心功能拆分为五个可插拔模块，支持用户接入自定义数据、阿尔法因子、模型、风险限额和交易系统，整体设计为 AI 原生，所有工具Schema都针对 LLM 代理优化而非面向普通人类用户。

它面向量化研究者和AI代理开发人员，用户可以基于该插件框架，端到端搭建从因子挖掘、模型训练到回测验证再到模拟/实盘交易的完整量化投资工作流。所有核心数值计算都作为无共享状态的纯函数实现，支持AI代理并行调用多个工具，用户也可以开发自定义插件接入框架，还可将自己开发的模块贡献到dsh-quant的开源生态中。

该插件使用TypeScript开发，运行在DSH的Node.js运行时中，零运行时依赖，所有数值方法都有手动计算的基准测试，可离线验证正确性，采用MIT许可证开源，托管在npm上，可通过DSH市场一键安装。框架仅开放范式和模块组合规则，用户自行保留内部研究策略和私有数据。

View on GitHub在 GitHub 查看

Send to your DSH发给你的 DSH 安装

请帮我安装这个 DSH 插件。安装前先完成【兼容性检查 + 安全性检查】，检查通过再动手。

插件：dsh-quant（pengpengyi92/dsh-quant）
仓库：https://github.com/pengpengyi92/dsh-quant
本站详情页：https://www.yhbd.top/plugins/pengpengyi92-dsh-quant/
本站登记：类型 plugin · 归类 原生 DSH 插件 · 许可证 MIT · ⭐ 47 · 最近提交 2026-10-03 · 主语言 TypeScript

按下面顺序执行，每步先把结论告诉我，再进入下一步：

【1 兼容性检查】
① 我这边：DSH 版本、Node 版本、操作系统、当前 profile（web / desktop）。
② 读它的 README、package.json、插件 manifest，列出它要求的 DSH 版本 / Node 版本 / 操作系统 / 外部依赖 / 需要另外先装的运行时。
③ 逐条比对，结论只写「满足 / 不满足 / 未知」三种；不满足的给出可行替代方案。
④ 检查是否和我已装的插件冲突：命令名重复、skill / tool 重名、端口占用、重复注册的 MCP server。

【2 安全性检查】
① 仓库可信度：和上面「本站登记」是否一致；star / fork 数、创建时间、最近提交，是否归档或长期停更。
② 安装脚本：逐行看 package.json 的 preinstall / install / postinstall，以及 install.sh、setup.ps1 之类脚本。出现 curl|bash、下载后直接执行、混淆代码、访问与插件功能无关的域名，立刻停下来告诉我，不要继续装。
③ 依赖：列出新增依赖，标出无人维护、或与知名包拼写近似的可疑包（typosquatting）。
④ 权限与副作用：它会读写哪些目录、访问哪些域名、需要哪些 DSH 权限（filesystem / network / shell / clipboard 等），以及怎么卸载和回滚。
⑤ 如果它要求 sudo / 管理员权限，或权限明显超出功能所需，先停下来问我。

【3 安装】
上面两步没有「不满足」和「高危项」时才执行；用官方推荐方式安装，不要自行提权。

【4 汇报】
用表格输出：检查项 / 结论 / 依据 / 是否需要我决策。拿不准的一律写「未知」并说明要我怎么确认——不要猜，也不要替我决定。

Send this message to DSH in your current session: it verifies compatibility and security first (answering met / not met / unknown item by item) and only installs once everything checks out — it will stop and ask you if it finds a high-risk item. The box scrolls; the copy is the full prompt. CLI install commands may not be accurate across systems, so DSH is the safer route.把上面这条消息直接发给当前会话里的 DSH：它会先核对兼容性与安全性（逐条给「满足 / 不满足 / 未知」），确认没问题再安装，有高危项会停下来问你。框内可滚动，复制到的是完整提示词；安装命令不一定准确，发给 DSH 更稳。

Pre-install check安装前体检Compatibility · Security兼容性 · 安全性 1 note1 项提示

47 stars - an early-stage project星标 47，属于早期项目

DSH walks through these 9 checksDSH 会逐条核对这 9 项

Compatibility兼容性

DSH, Node, OS and profile requirementsDSH 版本 / Node 版本 / 操作系统 / profile 是否满足要求
External dependencies and runtimes (Electron / Python / Docker, ...)外部依赖与运行时（Electron / Python / Docker 等）是否齐备
Conflicts with installed plugins: command names, skill / tool names, ports, duplicate MCP registration与已装插件是否冲突：命令名、skill / tool 重名、端口占用、重复 MCP 注册

Security安全性

Repo matches the facts registered here; archived or abandoned?仓库是否与页面登记一致，是否归档或长期停更
Safety of preinstall / install / postinstall and install.sh / setup.ps1preinstall / install / postinstall 与 install.sh、setup.ps1 是否安全
curl|bash, download-then-execute, obfuscation, unrelated domains → stop immediatelycurl|bash、下载即执行、混淆代码、无关域名 → 立刻停止
Typosquatting or unmaintained packages among the new dependencies新增依赖里有没有 typosquatting 或无人维护的包
Requested permissions vs. what the feature actually needs申请了哪些权限、是否超出功能所需（filesystem / network / shell / clipboard）
Any sudo / admin requirement, plus uninstall and rollback是否要求 sudo / 管理员权限，以及卸载与回滚方式

Anything uncertain must be marked unknown with a note on how to confirm it. This site's signal screen is a static snapshot, not a security audit.拿不准的必须标「未知」并说明要我怎么确认。本站的信号筛查是静态快照，不能替代安全审计。

Or use CLI install (for developers)或使用命令行安装（适合开发者）

CLI Install命令行安装

dsh plugin --profile web add github:pengpengyi92/dsh-quant

把 pengpengyi92/dsh-quant 加入你的 DSH 配置（web profile）即可启用。

READMEREADME

37.9 KB · 缓存于 2026-09-18 19:38:46 · 37.9 KB

🐳 dsh-quant — The Everything-Plugin Quant OS

dsh-quant open-source quant research hero

📣 Announcement archive: 2026-09-01 X open-source launch copy

🌐 Site: https://dsh-quant-site.pages.dev · ✅ Listed in awesome-dsh-plugin (one-click install via dsh-market)

AI-native & DSH-native quant toolkit for every quant aspect — 59 tools · 6 domains (data / alpha / ML / risk / execution / ecosystem) · one end-to-end PDAT→PET research pipeline. Methods open, secrets internal.

🧩 Core Philosophy: Everything is a Plugin (quant edition)

dsh's philosophy is everything is a plugin; dsh-quant brings it to quant — open-sourcing the internal five-team paradigm (PDAT → PAAT → PCPT → PRT → PET) as five pluggable modules:

data plugin   dsh-data      market data / sources / quality  ← plug in Binance or your own data
alpha plugin  dsh-alpha     indicators / factors / eval      ← write your own alpha (internal alpha stays private)
model plugin  dsh-ml        backtests / ML/DL/RL framework   ← train your own models (internal research stays private)
risk plugin   dsh-risk      VaR / drawdown / options / bonds ← set your own risk limits
exec plugin   dsh-execution sim execution / fund / report    ← build your own trading system (paper or live)

Showing the opening section of the README — the full document lives in the repository以上为 README 开头摘要，完整文档在仓库内 · View the full README on GitHub →在 GitHub 查看完整 README →

渲染基于仓库 pengpengyi92/dsh-quant 的 README.md。在 GitHub 查看原文 →