fin-guru-strategize
GitHub将量化分析转化为可执行的投资组合策略,涵盖资产配置、入场时机、仓位管理及实施计划。用于回答买卖、调仓及收入部署问题,需包含风险指标并调用CLI工具验证。
Trigger Scenarios
Install
npx skills add AojdevStudio/Finance-Guru --skill fin-guru-strategize -g -y
SKILL.md
Frontmatter
{
"name": "fin-guru-strategize",
"description": "Turn research and quantitative results into a portfolio strategy with allocation changes, entry timing, position sizing, margin and dividend tactics, and an implementation plan with triggers. Use when the owner asks what to buy, sell, trim, or rotate, how much to put into a position, or how to deploy monthly income across portfolio layers. Not for raw risk numbers (use fin-guru-quant-analysis) or a margin dashboard update (use margin-management)."
}
Strategy Integration Skill
Convert quantitative analysis into actionable strategic recommendations.
Capability probe
Before adding current external assumptions, follow the shared paid MCP capability probe. This workflow wants exa for broad current-market discovery and financial-datasets for normalized company fundamentals. Announce any primary-source WebSearch fallback and its quality limits; stop if the requested strategy depends on data the fallback cannot verify.
Workflow Steps
- Review Analysis — Ingest quantitative outputs (risk metrics, momentum, correlations)
- Objective Alignment — Confirm client goals, risk tolerance, and policy constraints
- Strategy Development — Map analytical insights to actionable recommendations
- Risk Validation — Validate proposed positions using
risk_metrics_cli.pyandmomentum_cli.py - Implementation Plan — Create detailed execution roadmap with timing and triggers
- Monitoring Framework — Establish performance tracking and alert systems
Integration Points
- Load
{project-root}/fin-guru/checklists/margin-strategy.mdfor margin tactics - Load
{project-root}/fin-guru/checklists/dividend-framework.mdfor income strategies - Load
{project-root}/fin-guru/checklists/cashflow-policy.mdfor cash flow optimization - Load
{project-root}/fin-guru/data/modern-income-vehicles.mdfor Layer 2 evaluation criteria
Risk Validation Tools
# Pre-trade risk validation
uv run python -m src.analysis.risk_metrics_cli TICKER --days 252 --benchmark SPY --output json
# Entry timing analysis
uv run python -m src.utils.momentum_cli TICKER --days 90 --output json
# Volatility-based position sizing
uv run python -m src.utils.volatility_cli TICKER --days 90 --output json
# Portfolio optimization
uv run python -m src.strategies.optimizer_cli TICKERS --method max_sharpe --output json
Output
Return the fin-guru-output-contract skill. The Numbers table carries Sharpe, Sortino, and max drawdown for every position the strategy adds or changes. A recommendation without those three numbers is incomplete. Add an implementation plan after the Numbers table, with the amount, the entry trigger, and the exit trigger for each change.
Requirements
- ALL strategic recommendations MUST include risk-adjusted metrics (Sharpe, Sortino, Max Drawdown)
- Distribution variance of ±5-15% monthly is NORMAL for options-based funds — do not flag
- Evaluate Layer 2 holdings on trailing 12-month yield, not monthly distribution changes
- Only recommend selling on RED FLAGS (>30% sustained decline, NAV erosion, strategy changes)
- Verify all market assumptions are based on current date conditions
Version History
-
d6ceaea
Current 2026-10-19 22:18
修复数据框架路径悬空问题,将边际、股息和现金流加载指向正确的checklists目录,并增加对缺失文件的测试失败检查。
-
ac43b09
2026-09-23 02:03
新增 paid MCP capability probe 用于验证 exa 和 financial-datasets 等外部数据源可用性;将 CLI 调用统一改为模块形式 (python -m src...);更新文档以指向新的实例目录布局。
- d13f5ab 2026-08-20 11:51


