findata-toolkit-cn
自包含的数据工具包，提供A股市场实时金融数据和定量计算。所有数据源免费，无需API密钥。
Works with
Installation Guide
How to use findata-toolkit-cn on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your machine
- ›Node.js 16+ with npm — verify with
node --version - ›Active project directory where you want to add
findata-toolkit-cn
Run the install command
Execute the skills CLI command in your project's root directory to begin installation:
Fetches findata-toolkit-cn from geeksfino/finskills and configures it for Cursor.
Select Cursor when prompted
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate findata-toolkit-cn. Access via /findata-toolkit-cn in your agent's command palette.
Security Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
Documentation
金融数据工具包 — A股市场
自包含的数据工具包，提供A股市场实时金融数据和定量计算。所有数据源免费，无需API密钥。
安装
安装依赖（一次性）：
pip install -r requirements.txt
可用工具
所有脚本位于 scripts/ 目录。从技能根目录运行。
1. A股数据 (scripts/stock_data.py)
通过 AKShare 获取A股基本面、行情、财务指标。
| 命令 | 用途 |
|---|---|
python scripts/stock_data.py 600519 |
基本信息（贵州茅台） |
python scripts/stock_data.py 600519 --metrics |
完整财务指标（估值、盈利、杠杆、增长） |
python scripts/stock_data.py 600519 --history |
历史OHLCV行情 |
python scripts/stock_data.py 600519 --financials |
利润表、资产负债表、现金流量表 |
python scripts/stock_data.py 600519 --insider |
董监高增减持数据 |
python scripts/stock_data.py --northbound |
北向资金流向（沪股通/深股通） |
python scripts/stock_data.py 600519 000858 --screen |
批量筛选 |
2. 宏观数据 (scripts/macro_data.py)
通过 AKShare 获取中国宏观经济指标。
| 命令 | 用途 |
|---|---|
python scripts/macro_data.py --dashboard |
完整宏观仪表盘 |
python scripts/macro_data.py --rates |
利率数据（LPR、Shibor） |
python scripts/macro_data.py --inflation |
CPI/PPI数据 |
python scripts/macro_data.py --pmi |
PMI数据（制造业/非制造业） |
python scripts/macro_data.py --social-financing |
社会融资规模 + M2 |
python scripts/macro_data.py --cycle |
经济周期阶段判断 |
数据来源
| 来源 | 数据内容 | API密钥 |
|---|---|---|
| AKShare | A股行情、财务数据、董监高交易、北向资金、宏观指标 | 无需 |
输出格式
所有脚本以 JSON 输出到标准输出，便于解析。错误信息输出到标准错误。
配置
可选：编辑 config/data_sources.yaml 自定义速率限制或添加付费数据源API密钥。
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Use Cases
User Story & Requirements Generation
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Competitive Analysis
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Roadmap Prioritization
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale