用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
直接命令不会经过审查 Prompt;运行前请先检查来源。
npx skills add https://github.com/javimosch/open-claw-skills --skill plusefin-analysis命令会保持在同一行。复制前请横向滚动并检查完整内容。
想先保存到本地?可下载 SkillsMP 当前能够提供的文件。
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基于 SOC 职业分类
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| name | plusefin-analysis |
| description | AI-ready stock analysis with financial data, options, sentiment, and structured research framework |
| metadata | {"clawdbot":{"emoji":"📈","homepage":"https://github.com/plusefin/plusefin-skill","requires":{"env":"[Truncated]"},"primaryEnv":"PLUSEFIN_API_KEY"}} |
AI-ready financial data research skill with structured research methodology.
export PLUSEFIN_API_KEY=your_api_key
ticker - overview, valuation, ratingssentiment / sentiment-historyoptions / options-analyze (IV, Greeks, OI)holders - major holders changesstatements (income/balance/cash)earnings / insidersprice-historyBased on data, formulate hypotheses:
Structured output:
Each key conclusion must include source citations.
# Set API key
export PLUSEFIN_API_KEY=your_api_key
# Run commands
python plusefin.py <command> [args]
| Command | Usage | Description |
|---|---|---|
ticker | python plusefin.py ticker <symbol> | Company overview, valuation, ratings |
price-history | python plusefin.py price-history <ticker> [period] | Historical prices (6mo/1y/2y) |
sentiment | python plusefin.py sentiment | Market sentiment (Fear & Greed) |
sentiment-history | python plusefin.py sentiment-history [days] | Historical sentiment |
options | python plusefin.py options <symbol> [num] | Options chain |
options-analyze | python plusefin.py options-analyze <symbol> | Options analysis |
holders | python plusefin.py holders <symbol> | Institutional holdings |
statements | python plusefin.py statements <symbol> [type] | Financial statements (income/balance/cash) |
earnings | python plusefin.py earnings <symbol> | Earnings history |
insiders | python plusefin.py insiders <symbol> | Insider trading |
news | python plusefin.py news <symbol> | Stock news |
fred | python plusefin.py fred <series_id> | Macroeconomic data |