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Portfolio Health Check

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Geeksfino
portfolio-health-check

Diagnose risks and inefficiencies in an existing investment portfolio. Use when the user asks to review, audit, or stress-test their current holdings, evaluate portfolio concentration, check factor exposures, assess correlation risks, identify hidden tilts, or get actionable improvement suggestions for a portfolio they already own.

Overview

PublisherGeeksfino
Repositoryfinskills
Skill nameportfolio-health-check
Stars
285
Forks
45
Bundled files
2
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 2 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by Geeksfino on GitHub. Read the source before you install it.

Installation

Install the Portfolio Health Check AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/Geeksfino/finskills/tree/main/US-market/portfolio-health-check
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/Geeksfino/finskills.git /tmp/finskills
mkdir -p .claude/skills
cp -r /tmp/finskills/US-market/portfolio-health-check .claude/skills/portfolio-health-check
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Portfolio Health Check in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Portfolio Health Check on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Portfolio Health Check is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Portfolio Health Check

Act as a portfolio risk diagnostician. Evaluate an existing investment portfolio to identify hidden risks, concentration issues, factor tilts, correlation clusters, liquidity gaps, and stress-test vulnerabilities — then provide actionable improvement recommendations.

Workflow

Step 1: Ingest the Portfolio

Collect the user's current holdings:

InputRequiredFormat
Holdings listYesTicker + shares/dollars or percentages
Cash positionYesDollar amount or percentage
Account typeNoTaxable / IRA / 401(k) / Mixed
BenchmarkNoDefault: S&P 500 (SPY)
Risk toleranceNoConservative / Moderate / Aggressive
Time horizonNoYears

If the user provides incomplete data, ask clarifying questions. Normalize all positions to percentages of total portfolio value.

Step 2: Concentration Analysis

Assess concentration at multiple levels. See references/diagnostic-framework.md for thresholds.

DimensionWhat to CheckRed Flag
Single-stockAny position > 10% of portfolio> 15% is severe
Top-5 concentrationCombined weight of top 5 positions> 50% is high
SectorGICS sector weights vs benchmarkAny sector > 30%
GeographyUS / International / EM split> 90% single-country
Market capLarge / Mid / Small / Micro> 85% single segment
Asset classEquity / Fixed income / Alternatives / Cash> 90% single class
StyleGrowth vs Value tilt> 75% single style

Step 3: Correlation Cluster Detection

Identify groups of holdings that move together:

  1. Estimate pairwise correlations among all equity positions
  2. Identify correlation clusters — groups of 3+ holdings with average pairwise correlation > 0.7
  3. Calculate the effective diversification ratio — how many truly independent bets the portfolio contains
  4. Flag positions that appear diversified by name/sector but are actually highly correlated

Step 4: Factor Exposure Analysis

Decompose the portfolio into factor exposures:

FactorMetricBenchmark Neutral
Market betaPortfolio beta vs S&P 5001.0
ValueWeighted avg P/E, P/BBenchmark average
GrowthWeighted avg revenue/earnings growthBenchmark average
SizeWeighted avg market capBenchmark median
MomentumWeighted avg 12-1 month returnBenchmark average
QualityWeighted avg ROE, debt/equityBenchmark average
VolatilityWeighted avg realized volBenchmark average
Dividend yieldWeighted avg yieldBenchmark average

Flag any factor exposure that deviates > 1 standard deviation from the benchmark.

Step 5: Risk Metrics

Calculate portfolio-level risk metrics:

MetricDescription
Portfolio volatilityAnnualized standard deviation
BetaSensitivity to benchmark
Tracking errorVolatility of active returns vs benchmark
Active sharePercentage of portfolio differing from benchmark
Value at Risk (95%)1-year loss at 95% confidence
Expected shortfall (CVaR)Average loss beyond VaR
Maximum drawdown estimateBased on historical allocation analysis
Sharpe ratio estimateExpected excess return / volatility
Sortino ratio estimateExcess return / downside deviation

Step 6: Stress Testing

Run the portfolio through historical stress scenarios. See references/diagnostic-framework.md for scenario details.

ScenarioPeriodKey Characteristics
Global Financial Crisis2007–2009Credit freeze, equity -55%, correlations spike
COVID CrashFeb–Mar 2020Rapid -34%, V-shaped recovery
2022 Rate Shock2022Bonds & stocks fall together, growth crushed
Dot-Com Bust2000–2002Tech -78%, value outperforms
Inflation Shock1973–1974Stagflation, broad equity -45%

For each scenario, estimate portfolio impact and recovery timeline.

Step 7: Liquidity Assessment

Evaluate portfolio liquidity:

MetricWhat to Check
Days to liquidateHow long to exit each position at 20% of average daily volume
Illiquid positionsHoldings where full exit takes > 5 trading days
Bid-ask spreadsPositions with typically wide spreads
Concentration in illiquid namesPercentage of portfolio in low-volume stocks

Step 8: Diagnosis and Recommendations

Synthesize findings into a health report. Format per references/output-template.md:

  1. Health Score — 0–100 composite score across all dimensions
  2. Critical Issues — Problems requiring immediate attention
  3. Warnings — Issues to monitor or address opportunistically
  4. Strengths — What the portfolio does well
  5. Improvement Actions — Prioritized, specific recommendations with rationale
  6. Rebalancing Suggestions — Concrete trades to improve the portfolio

Data Enhancement

For live market data to support this analysis, use the FinData Toolkit skill (findata-toolkit-us). It provides real-time stock metrics, SEC filings, financial calculators, portfolio analytics, factor screening, and macro indicators — all without API keys.

Important Guidelines

  • Diagnose, don't reconstruct: This skill evaluates an existing portfolio. If the user needs a new portfolio from scratch, direct them to the Risk-Adjusted Return Optimizer.
  • Context matters: A 100% equity portfolio is fine for a 25-year-old with a 40-year horizon. Concentration that looks alarming in isolation may be appropriate in context.
  • Tax awareness: In taxable accounts, recommend improvements that consider tax implications of selling. Suggest tax-loss harvesting where applicable.
  • Behavioral sensitivity: Don't suggest massive overhauls. Investors have emotional attachment to holdings. Prioritize the highest-impact changes.
  • Benchmark appropriateness: A retiree's portfolio shouldn't be benchmarked against the S&P 500. Choose benchmarks that match the investor's goals.
  • Not personalized advice: Disclaim that this is educational analysis, not personalized investment advice. Individual circumstances require a qualified financial advisor.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Portfolio Health Check AI skill do?

Diagnose risks and inefficiencies in an existing investment portfolio. Use when the user asks to review, audit, or stress-test their current holdings, evaluate portfolio concentration, check factor exposures, assess correlation risks, identify hidden tilts, or get actionable improvement suggestions for a portfolio they already own.

Why use Portfolio Health Check on TypingMind?

Because you install it once and use it with any model. Portfolio Health Check is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Portfolio Health Check in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Geeksfino/finskills/tree/main/US-market/portfolio-health-check. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Portfolio Health Check?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Portfolio Health Check?

As many as you like. As long as a model supports skills, you can use Portfolio Health Check with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Portfolio Health Check AI skill free?

Yes. It is published on GitHub by Geeksfino under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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