Analyze and manage investment portfolios by integrating with Alpaca MCP Server to fetch real-time holdings data, then performing comprehensive analysis covering asset allocation, diversification, risk metrics, individual position evaluation, and rebalancing recommendations. Generate detailed portfolio reports with actionable insights.
Works with
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionportfolio-managerExecute the skills CLI command in your project's root directory to begin installation:
Fetches portfolio-manager from tradermonty/claude-trading-skills and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate portfolio-manager. Access via /portfolio-manager in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
Submit your Claude Code skill and start earning
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
1
total installs
1
this week
693
GitHub stars
0
upvotes
Run in your terminal
1
installs
1
this week
693
stars
Analyze and manage investment portfolios by integrating with Alpaca MCP Server to fetch real-time holdings data, then performing comprehensive analysis covering asset allocation, diversification, risk metrics, individual position evaluation, and rebalancing recommendations. Generate detailed portfolio reports with actionable insights.
This skill leverages Alpaca's brokerage API through MCP (Model Context Protocol) to access live portfolio data, ensuring analysis is based on actual current positions rather than manually entered data.
Invoke this skill when the user requests:
This skill requires Alpaca MCP Server to be configured and connected. The MCP server provides access to:
MCP Server Tools Used:
get_account_info - Fetch account equity, buying power, cash balanceget_positions - Retrieve all current positions with quantities, cost basis, market valueget_portfolio_history - Historical portfolio performance dataIf Alpaca MCP Server is not connected, inform the user and provide setup instructions from references/alpaca_mcp_setup.md.
Use Alpaca MCP Server tools to gather current portfolio information:
1.1 Get Account Information:
Use mcp__alpaca__get_account_info to fetch:
- Account equity (total portfolio value)
- Cash balance
- Buying power
- Account status
1.2 Get Current Positions:
Use mcp__alpaca__get_positions to fetch all holdings:
- Symbol ticker
- Quantity held
- Average entry price (cost basis)
- Current market price
- Current market value
- Unrealized P&L ($ and %)
- Position size as % of portfolio
1.3 Get Portfolio History (Optional):
Use mcp__alpaca__get_portfolio_history for performance analysis:
- Historical equity values
- Time-weighted return calculation
- Drawdown analysis
Data Validation:
For each position in the portfolio, gather additional market data and fundamentals:
2.1 Current Market Data:
2.2 Fundamental Data: Use WebSearch or available market data APIs to fetch:
2.3 Technical Analysis:
Perform comprehensive portfolio analysis using frameworks from reference files:
Read references/asset-allocation.md for allocation frameworks
Analyze current allocation across multiple dimensions:
By Asset Class:
By Sector:
By Market Cap:
By Geography:
Output Format:
## Asset Allocation
### Current Allocation vs Target
| Asset Class | Current | Target | Variance |
|-------------|---------|--------|----------|
| US Equities | XX.X% | YY.Y% | +/- Z.Z% |
| ... |
### Sector Breakdown
[Pie chart description or table with sector percentages]
### Top 10 Holdings
| Rank | Symbol | % of Portfolio | Sector |
|------|--------|----------------|--------|
| 1 | AAPL | X.X% | Technology |
| ... |
Read references/diversification-principles.md for diversification theory
Evaluate portfolio diversification quality:
Position Concentration:
Sector Concentration:
Correlation Analysis:
Number of Positions:
Output:
## Diversification Assessment
**Concentration Risk:** [Low / Medium / High]
- Top 5 holdings represent XX% of portfolio
- Largest single position: [SYMBOL] at XX%
**Sector Diversification:** [Excellent / Good / Fair / Poor]
- Dominant sector: [Sector Name] at XX%
- [Assessment of balance across sectors]
**Position Count:** [Optimal / Under-diversified / Over-diversified]
- Total positions: XX stocks
- [Recommendation]
**Correlation Concerns:**
- [List any highly correlated position pairs]
- [Diversification improvement suggestions]
Read references/portfolio-risk-metrics.md for risk measurement frameworks
Calculate and interpret key risk metrics:
Volatility Measures:
Downside Risk:
Risk Concentration:
Tail Risk:
Output:
## Risk Assessment
**Overall Risk Profile:** [Conservative / Moderate / Aggressive]
**Portfolio Beta:** X.XX (vs market at 1.00)
- Interpretation: Portfolio is [more/less] volatile than market
**Maximum Drawdown:** -XX.X% (from $XXX,XXX to $XXX,XXX)
- Current drawdown from peak: -XX.X%
**High-Risk Positions:**
| Symbol | % of Portfolio | Beta | Risk Factor |
|--------|----------------|------|-------------|
| [TICKER] | XX% | X.XX | [High volatility / Recent loss / etc] |
**Risk Concentrations:**
- XX% in single sector ([Sector])
- XX% in stocks with beta > 1.5
- [Other concentration risks]
**Risk Score:** XX/100 ([Low/Medium/High] risk)
Evaluate portfolio performance using available data:
Absolute Returns:
Time-Weighted Returns (if history available):
Position-Level Performance:
Output:
## Performance Review
**Total Portfolio Value:** $XXX,XXX
**Total Unrealized P&L:** $XX,XXX (+XX.X%)
**Cash Balance:** $XX,XXX (XX% of portfolio)
**Best Performers:**
| Symbol | Gain | Position Value |
|--------|------|----------------|
| [TICKER] | +XX.X% | $XX,XXX |
| ... |
**Worst Performers:**
| Symbol | Loss | Position Value |
|--------|------|----------------|
| [TICKER] | -XX.X% | $XX,XXX |
| ... |
**Performance vs Benchmark (if available):**
- Portfolio return: +X.X%
Make data-driven prioritization decisions faster
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
ailabs-393/ai-labs-claude-skills
pproenca/dot-skills
mattpocock/skills
Registry listing for portfolio-manager matched our evaluation — installs cleanly and behaves as described in the markdown.
portfolio-manager fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
Keeps context tight: portfolio-manager is the kind of skill you can hand to a new teammate without a long onboarding doc.
portfolio-manager fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
portfolio-manager has been reliable in day-to-day use. Documentation quality is above average for community skills.
portfolio-manager fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
Useful defaults in portfolio-manager — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
Registry listing for portfolio-manager matched our evaluation — installs cleanly and behaves as described in the markdown.
I recommend portfolio-manager for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
Registry listing for portfolio-manager matched our evaluation — installs cleanly and behaves as described in the markdown.
showing 1-10 of 56