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Install in OpenClaw
/install yang-selection
Description
杨永兴尾盘选股法 - 腾讯财经实时筛选，智能市值缓存
Usage Guidance
This skill appears internally consistent for stock screening: it calls Tencent's public realtime API and uses the baostock library for historical data, reads a stock list file produced by another skill, and writes a local cache file. Before installing: (1) confirm the main_board_stocks.json you will supply comes from a trusted source, (2) be aware the script will make outbound HTTP requests to qt.gtimg.cn and to Baostock services, (3) adjust or verify the absolute path (/home/admin/...) if your environment differs, and (4) review/verify installed third-party packages (baostock) from PyPI if you have strict supply-chain policies. No secrets are requested by this skill.
Capability Analysis
Type: OpenClaw Skill
Name: yang-selection
Version: 1.0.0
The skill is a legitimate stock screening tool implementing the Yang Yongxing strategy. It fetches real-time data from the Tencent Finance API and historical data via the Baostock library. The code in yang_selection.py is well-structured, includes a local caching mechanism (market_cap_cache.json), and lacks any indicators of malicious behavior such as data exfiltration, unauthorized command execution, or prompt injection.
Capability Assessment
Purpose & Capability
Name/description (尾盘选股 using Tencent + Baostock) align with the included code and instructions. Required binary is only python3 and declared dependencies (baostock, pandas, numpy, requests) are expected for the stated functionality.
Instruction Scope
SKILL.md and README instruct fetching a stock list from the separate query-main-board-stocks skill, calling the Tencent realtime endpoint and Baostock for history, and writing a local market_cap_cache.json — all within expected scope. Note: the code references an absolute path (/home/admin/...) and relative paths to the other skill's output; you should ensure the required main_board_stocks.json comes from a trusted source.
Install Mechanism
There is no automated install script (instruction-only). Dependencies are normal Python packages installed via pip per README. No remote arbitrary downloads or archive extraction are present.
Credentials
The skill requests no environment variables or credentials. External network calls are limited to Tencent's public qt.gtimg.cn endpoint and Baostock (library) — both are consistent with the described data sources.
Persistence & Privilege
Skill does not request always:true, does not modify other skills, and only writes a local market_cap_cache.json file in its directory. It does reference/require the output of another skill but does not request elevated agent privileges.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install yang-selection - After installation, invoke the skill by name or use
/yang-selection - Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Initial release of yang-selection.
- Implements Yang Yongxing’s end-of-day stock picking method.
- Real-time stock screening via Tencent Finance API—no Baostock login required.
- Intelligent market cap caching to prevent duplicate queries within 30 days.
- Two-step filtering: basic (price gain, turnover, market cap) and deep (volume ratio, moving averages, new highs).
- Query rate limited to 10 stocks per second.
- Outputs results to terminal and uses a local cache file.
Metadata
Frequently Asked Questions
What is 杨永兴尾盘选股?
杨永兴尾盘选股法 - 腾讯财经实时筛选，智能市值缓存. It is an AI Agent Skill for Claude Code / OpenClaw, with 111 downloads so far.
How do I install 杨永兴尾盘选股?
Run "/install yang-selection" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is 杨永兴尾盘选股 free?
Yes, 杨永兴尾盘选股 is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does 杨永兴尾盘选股 support?
杨永兴尾盘选股 is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created 杨永兴尾盘选股?
It is built and maintained by dxyu94 (@dxyu94); the current version is v1.0.0.
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