Finance agent skills
Find skills for market data, stock research, SEC filings, portfolio analysis, backtesting, risk, crypto, and quant workflows.
Built for finance builders searching for agent skills that can support market research, quant analysis, and financial workflows.
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These pages are built for high-intent search and for agents that need a structured shortlist before installing third-party code.
01
Summarize SEC filings and earnings materials
02
Analyze stocks, portfolios, factors, and risk
03
Backtest quant ideas with reproducible steps
04
Build dashboards over financial and market data
Ranked shortlist
#01
Algorithmic trading and quantitative trading open source platform to develop trading robots (stock markets, forex, crypto, bitcoins, and options).
100
Quality
100
Trust
71
Fit
$ npx skills add StockSharp/StockSharp#02
The backtesting engine that gives you an unfair advantage. Run thousands of trading ideas before others finish one.
100
Quality
100
Trust
69
Fit
$ npx skills add polakowo/vectorbt#03
Track stocks, crypto, and derivatives prices and positions in real time from your terminal
100
Quality
100
Trust
68
Fit
$ npx skills add achannarasappa/tickerFinancial portfolio optimisation in python, including classical efficient frontier, Black-Litterman, Hierarchical Risk Parity
100
Quality
100
Trust
68
Fit
$ npx skills add PyPortfolio/PyPortfolioOpt#05
Financial data platform for analysts, quants and AI agents.
100
Quality
100
Trust
77
Fit
$ npx skills add OpenBB-finance/OpenBBFinceptTerminal is a modern finance application offering advanced market analytics, investment research, and economic data tools, designed for interactive exploration and data-driven decision-making in a user-friendly environment.
100
Quality
100
Trust
74
Fit
$ npx skills add Fincept-Corporation/FinceptTerminalEvaluation
Source attribution for financial claims
Reproducible data loading and analysis steps
Fresh repository activity and clear limitations
Separation between analysis support and financial advice
Questions
They should be treated as research and analysis tools, not regulated financial advice. Always review sources, assumptions, and outputs before acting.
Strong candidates cite sources, handle data reproducibly, document limitations, and are maintained enough to be useful in current market workflows.