Review portfolio holdings and prepare a proposed rebalancing plan from target weights. Explains that neural-trader 2.8.11 only returns equal weights, directs actual optimization to a separate skill, and does not place trades.
Optimize portfolio allocation using npx neural-trader mean-variance engine with risk constraints and rebalancing plan
Reads portfolio holdings to help review asset allocation and prepare a rebalancing proposal. Rebalancing means adjusting holdings to match target proportions. The proposal brings together current and target weights, required trades, and estimated costs, and saves allocation information. The workflow also includes searching past allocations and calling SONA to predict expected returns.
Use it to organize your current holdings or prepare adjustments toward target weights calculated separately. It also helps you distinguish what the commands actually return from the parts that require additional calculations.
/trader-portfolio-cg and my holdings to summarize proposed trades and costs.”Uses neural-trader and MCP tools from ruflo-core. In version 2.8.11, the allocation command is an equal-weight demo: it performs neither actual optimization nor rebalancing calculations. Mean-variance optimization is handled by /trader-portfolio-cg. Risk assessment requires a return series calculated from real data. Trades are proposals only; no orders are placed.
This overview was written by AI (OpenAI Codex) from the public SKILL.md. Check the original below for the exact behavior.
AI rated this skill on four points using only the contents of its SKILL.md. Stars and popularity are not taken into account.
The total counts each point as A = 25, B = 15, C = 5. Rated by AI (OpenAI Codex) as of Oct 21, 2026. Treat it as a guide and read the original before installing.
Review the instructions the agent will receive before you install.
Optimize portfolio allocation using neural-trader's portfolio engine.
Steps:
npm ls neural-trader 2>/dev/null || npm install --ignore-scripts neural-tradermcp__plugin_ruflo-core_ruflo__memory_search({ query: "current portfolio holdings", namespace: "trading-portfolio" })npx neural-trader --portfolio optimize --symbols AAPL,MSFT,GOOGL --target-return 0.10
--risk-target is accepted as an alias of --target-return.) In 2.8.11 this returns EQUAL weights and a risk figure for them, with a note saying the returns matrix is not wired; it does not optimise anything. For real mean-variance weights use /trader-portfolio-cg. --portfolio current and --portfolio rebalance run the same equal-weight demo and ignore the word after --portfolio.--var and --correlation are not CLI flags. Use --risk assess --returns <series> (see /trader-risk) with returns you derived from real data.mcp__plugin_ruflo-core_ruflo__neural_predict({ input: "expected returns for [HOLDINGS] given current regime" })/trader-portfolio-cg returns and the user's stated holdings: trades needed, current vs target weights, estimated costs. Present it as a proposal for the user to act on; this plugin places no orders.mcp__plugin_ruflo-core_ruflo__agentdb_pattern-search({ query: "optimized portfolio Sharpe > 1", namespace: "trading-portfolio" })mcp__plugin_ruflo-core_ruflo__memory_store({ key: "portfolio-optimal-TIMESTAMP", value: "ALLOCATION_JSON", namespace: "trading-portfolio" })No reviews yet. Tell others what you thought.
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