用财务指标快速排除垃圾股，找到有基本面支撑的标的。用于A股基本面选股。
| Publisher | lxyeternal |
| Repository | MalSkillBench |
| Skill name | fundamental-screening |
| Stars | 64 |
| Forks | 14 |
| Bundled files | 1 |
| Links |
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Published by lxyeternal on GitHub. Read the source before you install it.
Install the Fundamental Screening AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.
TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.
https://github.com/lxyeternal/MalSkillBench/tree/main/Dataset/Skills/benign/a-stock-fundamental-screeningAny agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.
git clone --depth 1 https://github.com/lxyeternal/MalSkillBench.git /tmp/MalSkillBench
mkdir -p .claude/skills
cp -r /tmp/MalSkillBench/Dataset/Skills/benign/a-stock-fundamental-screening .claude/skills/fundamental-screeningEnable Fundamental Screening 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.
AI skills are plain Markdown instructions rather than provider-specific code, so Fundamental Screening 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.
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.
This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.
用财务指标快速排除垃圾股，找到有基本面支撑的标的。
即使是短线题材股，也要检查：
避免踩中"黑天鹅"。
调用 akshare-stock 获取：
The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.
用财务指标快速排除垃圾股，找到有基本面支撑的标的。用于A股基本面选股。
Because you install it once and use it with any model. Fundamental Screening 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.
Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/lxyeternal/MalSkillBench/tree/main/Dataset/Skills/benign/a-stock-fundamental-screening. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.
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.
As many as you like. As long as a model supports skills, you can use Fundamental Screening with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.
It is published on GitHub by lxyeternal. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.
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.
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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