可转债分析技能：把 A 股转债估值与条款博弈写进 Agent 工作流
可转债分析技能是 SkillHub 社区 Skill @user_75cb66f4/convertible-bond（v1.0.0，professional），将 A 股转债的转股、纯债、期权三维估值，以及下修、强赎、回售博弈、双低与轮动选债思路写入 SKILL.md 框架，requires_api_key=false。文章说明其定位与核心能力，并给出按 skillhub.cn 安装文档使用 skillhub install 装入 Cursor、Claude Code、Codex 等 skills 目录的步骤，以及启用后的典型对话用法与合规注意。
Read More星耀数智因子分析 Skill：单因子检验与多因子合成的 Agent 工作流
中国银河证券在 SkillHub 发布的星耀数智因子分析 skill（@org-rwhv0nty/ad-factor-analysis，v1.0.9）封装单因子预处理与 IC、回归、分层、拥挤度分析，以及多因子共线性检测、正交化、八种加权与打分，并自动生成可视化 HTML 报告。文章说明 Skill 定位、核心能力、SkillHub CLI 与 AI 提示词两种安装方式、Cursor 等客户端 skills 目录，以及 requires_api_key 等使用注意，便于量化研究者在 Agent 中复用因子检验与合成流程。
Read More同花顺 Skill：用 thsdk 把分钟 K 线、盘口与多股对比交给 Agent
同花顺是 SkillHub 上基于 thsdk 的专业类 Agent Skill（@user_6b3ace61/straightflush，1.0.0），覆盖分钟K线、板块指数与成分股、盘口深度、大单流向、集合竞价异动、分时及多股表格对比与相关性分析。本文说明其定位、核心能力、skillhub 安装命令与 Cursor/Claude Code 等 skills 目录配置，以及 pip 安装 thsdk 后的典型对话触发方式与使用注意。
Read Moredsh-plugin-xquant: Integrating xquant quantitative research MCP into DeepSeek Harness
dsh-plugin-xquant is a DSH plugin maintained by codingDuan (MIT licensed), designed to seamlessly integrate the xquant quantitative research MCP into DeepSeek Harness, resolving the pain point of cumbersome configuration for external tools in dsh Web. After installation, users can directly query factor definitions, calculate factor time series, browse strategy logic, and view historical performance within dsh Web, organizing the results into readable research conclusions. This plugin is positioned as a research assistance tool and does not provide buy/sell recommendations or market forecasts. The prerequisite for use is configuring `XQUANT_API_KEY` in the dsh process environment; the plugin reads exclusively from environment variables and does not write to local files or perform uploads. It connects to the xquant.shop official MCP service by default and supports via...
Read Moredsh-quant: AI-native Quantification Toolkit for DSH
dsh-quant is a DSH quant plugin maintained by pengpengyi92, offering 59 quant_* tools that cover six domains: data, factors, ML, risk control, execution, and ecosystem. It connects end-to-end research through the PDAT→PET pipeline. Primarily designed for use with agents, the plugin is implemented in TypeScript with zero runtime dependencies, installed via npm, and enabled in cordis.yml. This article introduces its module paradigm, core capabilities, and usage instructions, while also explaining applicable scenarios and security considerations.
Read More