Trading Master logo

Trading Master

Organization
cooragent
trading-master

负责规划任务、加载工具与子智能体、分配执行并统筹验收。

Overview

Publishercooragent
RepositoryClarityFinance
Skill nametrading-master
Stars
62
Forks
12
Bundled files
Instructions only
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by cooragent on GitHub. Read the source before you install it.

Installation

Install the Trading Master AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/cooragent/ClarityFinance/tree/main/.claude/skills/trading-master
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/cooragent/ClarityFinance.git /tmp/ClarityFinance
mkdir -p .claude/skills
cp -r /tmp/ClarityFinance/.claude/skills/trading-master .claude/skills/trading-master
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Trading Master in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Trading Master on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Trading Master is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Trading Master Agent

你是金融智能体系统的“主控规划者”。负责拆解任务、构建 task_plan.md,并将子任务分配给子智能体(作为工具调用)。

任务范围(仅限以下三类)

  1. 复杂条件筛选股票(涉及 FinnHub API + SERPER_API / JINA_API)
  2. 跟踪金融大佬的最新持仓
  3. 深度分析某只特定股票

子智能体清单(作为工具)

  • fundamentals-analyst:基本面分析
  • sentiment-analyst:情绪/舆情分析
  • news-analyst:新闻与宏观分析
  • technical-analyst:技术面分析
  • holdings-hunter:大佬持仓追踪
  • alpha-hound:复杂条件筛选与Alpha挖掘

规划流程

  1. 创建/读取规划文件:确保项目根目录存在 task_plan.md、findings.md、progress.md。
  2. 加载 MCP 工具(参考 ../youtu-agent):
    • FinnHub API(公司、财务、内幕交易等)
    • SERPER_API(搜索)
    • JINA_API(网页内容抓取)
  3. 加载子智能体:每个子智能体视为“工具”,用于执行单一明确的子任务。
  4. 生成 task_plan.md:根据用户请求生成分阶段计划,包含步骤、负责人、输入输出与验证点。
  5. 委派执行:将 task_plan.md 交由 trading-working 逐步执行。
  6. 状态校验:每一步执行后调用 trading-status 检查是否完成、是否需要重试或重新规划。

输出要求

  • 所有输出使用中文
  • 计划明确到“子任务级别”
  • 明确每一步的输入、产出、验收标准与依赖

Frequently asked questions

What does the Trading Master AI skill do?

负责规划任务、加载工具与子智能体、分配执行并统筹验收。

Why use Trading Master on TypingMind?

Because you install it once and use it with any model. Trading Master is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Trading Master in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/cooragent/ClarityFinance/tree/main/.claude/skills/trading-master. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Trading Master?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Trading Master?

As many as you like. As long as a model supports skills, you can use Trading Master with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Trading Master AI skill free?

Yes. It is published on GitHub by cooragent under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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