Portfolio optimization using PyPortfolioOpt for mean-variance optimization, efficient frontier analysis, risk modeling, and discrete allocation. Use when building investment portfolios, calculating optimal weights, analyzing risk-return tradeoffs, maximizing Sharpe ratio, minimizing volatility, or converting weights to share allocations. Supports HRP, CVaR, semivariance, and custom objectives.
This skill should be used when the user asks to "analyze crypto", "分析行情", "analyze btc", "look at eth", "check sol", or mentions cryptocurrency technical analysis. It provides market maker perspective analysis using Binance API data.
Run the mortgage underwriter CLI to analyze loan documents. Use when testing document analysis, debugging underwriter output, or processing loan files. Covers setup, execution, and result interpretation.
Expert in compliance frameworks (SOC2, ISO 27001), automated auditing, and risk management.
View automated portfolio, check cash account, monitor tax-loss harvesting, and track goals on Wealthfront
"How do I deliver maximum value with minimum cost?" - The capability of finding optimal paths to insight. Not restriction, but excellence at efficiency. Use when (1) spawning as opus-distillatus agent for focused synthesis, (2) token budget matters and quality cannot suffer, (3) working on tasks where the process itself is valuable and will be examined, (4) combining multiple sources into crystallized insight. This is an IDENTITY skill - it describes what you're excellent at, not what you can't do. Trust your judgment to find where tokens create value.
Trading session timing for MES/MGC futures with timezone handling. Use when implementing session-based entry/exit logic, ORB time windows, RTH detection, or handling global market overlaps.
Develop competitive research funding proposals for major agencies including NSF, NIH, DOE, and foundations. Guides persuasive proposal writing that demonstrates scientific rigor, innovation, and impact.
Twelve Data financial API for stocks, forex, crypto, ETFs, and 100+ technical indicators. Use when fetching time series data, technical analysis, fundamentals, or real-time streaming quotes.
Reserve allocation and follow-on optimization for the Phoenix fund model. Use when working on deterministic reserve engine logic and optimal reserves ranking.
Provides expert guidance for NautilusTrader algorithmic trading platform. Covers backtesting strategies, live trading deployment, event-driven architecture, and building trading systems.
Build a weighted decision matrix to compare options. Use when user needs to compare stacks, technologies, or any set of alternatives with multiple criteria.
Market regime detection and regime-specific trading strategies. Use when analyzing market conditions to select appropriate strategy.
Analyzes venture capital, investment trends, funding rounds, investor strategies, M&A activity, and funding patterns in specific markets or industries. Use when the user requests funding analysis, VC landscape research, investment trend analysis, or wants to understand investor activity and funding dynamics.
Generate, refactor, and maintain Python live trading bots for NQ futures prop firm trading (Apex Trader Funding). Supports Databento API for market data, TradersPost for execution, eval/PA modes, custom strategies, and comprehensive production features. Triggers: "live trading bot", "Python bot", "NQ bot", "futures bot", "create bot", "refactor bot", "/bot:new", "/bot:refactor", "/bot:custom".
Look up Target Allocation Percentages (TAPs) based on revenue level. Returns recommended Profit First percentages for Profit, Owner's Pay, Tax, and OpEx.
View investment accounts, check thinkorswim data, and access TD Ameritrade research (now Schwab)
FinnHub financial data API integration for stocks, forex, crypto, news, and fundamentals. Use when fetching real-time quotes, company profiles, financial statements, insider trading, earnings calendars, or market news.
FINER基準（Feasible, Interesting, Novel, Ethical, Relevant）で研究案を評価し、 Go/No-Go判定と改善提案を行う。RWD特有のバイアス・限界も評価項目に含む。
Trading performance evaluation via backtesting and metrics
Bitcoin trading simulation with technical analysis (EMA/RSI/Bollinger), Monte Carlo projections, and Telegram alerts. Cambodian market focus (USD/KHR 4050). TRIGGERS: BTC backtesting, indicator calculations, Fear & Greed integration, crypto strategy development, CoinGecko/Alternative.me APIs, portfolio simulation, trailing stop optimization, Sharpe/drawdown metrics. ENTRY POINTS: btc_trader.py (365d backtest), btc_simulation.py (60d Monte Carlo), backtest_runner.py (advanced metrics).
Risk management specialist who assesses, analyzes, and mitigates financial and operational risks with expertise in quantitative risk modeling, compliance frameworks, and enterprise risk assessment
太陽スタイル分析・スコアリングエンジン - 176パターンに基づくコンテンツ品質分析と改善提案
