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Optimize portfolio allocation using npx neural-trader mean-variance engine with risk constraints and rebalancing plan
Optimize portfolio allocation using neural-trader's portfolio engine.
Steps:
npm ls neural-trader 2>/dev/null || npm install neural-tradermcp__claude-flow__memory_search({ query: "current portfolio holdings", namespace: "trading-portfolio" })npx neural-trader --portfolio optimize
With risk target:
npx neural-trader --portfolio optimize --risk-target <number>
npx neural-trader --risk assess --portfolio current
npx neural-trader --var --portfolio current
npx neural-trader --correlation --portfolio current --flag-threshold 0.8
mcp__claude-flow__neural_predict({ input: "expected returns for [HOLDINGS] given current regime" })npx neural-trader --portfolio rebalance
Output: trades needed, current vs target weights, estimated costsnpx skills add ruvnet/ruflo --skill trader-portfolioHow clear and easy to understand the SKILL.md instructions are, rated from 1 to 5.
Clear and well structured, with only minor parts that might need a second read.
How directly an agent can act on the SKILL.md instructions, rated from 1 to 5.
Mostly actionable with clear steps; only a few small gaps remain.