/portfolio-optimizer
Modern portfolio theory optimization including Markowitz mean-variance, Black-Litterman, risk parity, and efficient frontier construction with constraints.
$ npx -y skills add CoWork-OS/CoWork-OS --skill portfolio-optimizer --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
- Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
- You can call itInvoke it directly when you want it.
- Slash command
/portfolio-optimizer
Context preview
The summary Claude sees to decide when to auto-load this skill.
Modern portfolio theory optimization including Markowitz mean-variance, Black-Litterman, risk parity, and efficient frontier construction with constraints.
SKILL.md
portfolio-optimizer.SKILL.mdname: portfolio-optimizer
description: "Modern portfolio theory optimization including Markowitz mean-variance, Black-Litterman, risk parity, and efficient frontier construction with constraints."
Portfolio Optimizer
Purpose
Modern portfolio theory optimization including Markowitz mean-variance, Black-Litterman, risk parity, and efficient frontier construction with constraints.
Routing
- Use when: Use when the user asks about portfolio optimization, asset allocation, efficient frontier, Markowitz optimization, Black-Litterman, risk parity, diversification, rebalancing, or optimal portfolio construction.
- Do not use when: Do not use when the request is about individual stock analysis, financial modeling, risk metrics only (use Risk Analyzer), or tax planning.
- Outputs: Outcome from Portfolio Optimizer: optimized asset allocation with weights, expected return, risk metrics, efficient frontier positioning, and rebalancing recommendations.
- Success criteria: Returns specific allocation weights, portfolio expected return and risk, Sharpe ratio, comparison to current allocation, and actionable rebalancing steps.
Trigger Examples
Positive
- Use the portfolio-optimizer skill for this request.
- Help me with portfolio optimizer.
- Use when the user asks about portfolio optimization, asset allocation, efficient frontier, Markowitz optimization, Black-Litterman, risk parity, diversification, rebalancing, or optimal portfolio construction.
- Portfolio Optimizer: provide an actionable result.
Negative
- Do not use when the request is about individual stock analysis, financial modeling, risk metrics only (use Risk Analyzer), or tax planning.
- Do not use portfolio-optimizer for unrelated requests.
- This request is outside portfolio optimizer scope.
- This is conceptual discussion only; no tool workflow is needed.
Parameters
| Name | Type | Required | Description | |---|---|---|---| | holdings | string | Yes | Current portfolio holdings and weights (e.g., SPY 40%, AGG 30%, GLD 10%, VWO 20%) | | objective | select | Yes | Optimization objective | | question | string | Yes | Your specific optimization question | | constraints | string | No | Portfolio constraints (e.g., long-only, max 25% per position, no emerging markets) | | targetReturn | string | No | Target annual return for optimization (e.g., 8%) |
Runtime Prompt
- Current runtime prompt length: 1094 characters.
- Runtime prompt is defined directly in `../portfolio-optimizer.json`.
Read more
name: portfolio-optimizer description: "Modern portfolio theory optimization including Markowitz mean-variance, Black-Litterman, risk parity, and efficient frontier construction with constraints."
Portfolio Optimizer
Purpose
Modern portfolio theory optimization including Markowitz mean-variance, Black-Litterman, risk parity, and efficient frontier construction with constraints.
Routing
- Use when: Use when the user asks about portfolio optimization, asset allocation, efficient frontier, Markowitz optimization, Black-Litterman, risk parity, diversification, rebalancing, or optimal portfolio construction.
- Do not use when: Do not use when the request is about individual stock analysis, financial modeling, risk metrics only (use Risk Analyzer), or tax planning.
- Outputs: Outcome from Portfolio Optimizer: optimized asset allocation with weights, expected return, risk metrics, efficient frontier positioning, and rebalancing recommendations.
- Success criteria: Returns specific allocation weights, portfolio expected return and risk, Sharpe ratio, comparison to current allocation, and actionable rebalancing steps.
Trigger Examples
Positive
- Use the portfolio-optimizer skill for this request.
- Help me with portfolio optimizer.
- Use when the user asks about portfolio optimization, asset allocation, efficient frontier, Markowitz optimization, Black-Litterman, risk parity, diversification, rebalancing, or optimal portfolio construction.
- Portfolio Optimizer: provide an actionable result.
Negative
- Do not use when the request is about individual stock analysis, financial modeling, risk metrics only (use Risk Analyzer), or tax planning.
- Do not use portfolio-optimizer for unrelated requests.
- This request is outside portfolio optimizer scope.
- This is conceptual discussion only; no tool workflow is needed.
Parameters
| Name | Type | Required | Description | |---|---|---|---| | holdings | string | Yes | Current portfolio holdings and weights (e.g., SPY 40%, AGG 30%, GLD 10%, VWO 20%) | | objective | select | Yes | Optimization objective | | question | string | Yes | Your specific optimization question | | constraints | string | No | Portfolio constraints (e.g., long-only, max 25% per position, no emerging markets) | | targetReturn | string | No | Target annual return for optimization (e.g., 8%) |
Runtime Prompt
- Current runtime prompt length: 1094 characters.
- Runtime prompt is defined directly in `../portfolio-optimizer.json`.
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Repo: CoWork-OS/CoWork-OS
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