Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add nicepkg/ai-workflow --skill portfolio-managergit clone --depth 1 https://github.com/nicepkg/ai-workflowWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/nicepkg/ai-workflow/portfolio-manager)<a href="https://agentmods.dev/skills/nicepkg/ai-workflow/portfolio-manager"><img src="https://agentmods.dev/badge/skills/nicepkg/ai-workflow/portfolio-manager/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/nicepkg/ai-workflow/portfolio-manager"><img src="https://agentmods.dev/badge/skills/nicepkg/ai-workflow/portfolio-manager.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00066 | $0.05045 |
| Opus 5.5 | $0.00026 | $0.02018 |
| Sonnet 5.5 | $0.00013 | $0.01009 |
| Haiku 4.5 | $0.00007 | $0.00505 |
Grade A, and why
portfolio-manager scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 751 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Portfolio Manager
Overview
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.
When to Use
Invoke this skill when the user requests:
- "Analyze my portfolio"
- "Review my current positions"
- "What's my asset allocation?"
- "Check my portfolio risk"
- "Should I rebalance my portfolio?"
- "Evaluate my holdings"
- "Portfolio performance review"
- "What stocks should I buy or sell?"
- Any request involving portfolio-level analysis or management
Prerequisites
Alpaca MCP Server Setup
This skill requires Alpaca MCP Server to be configured and connected. The MCP server provides access to:
- Current portfolio positions
- Account equity and buying power
- Historical positions and transactions
- Market data for held securities
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 data- Market data tools for price quotes and fundamentals
If Alpaca MCP Server is not connected, inform the user and provide setup instructions from references/alpaca_mcp_setup.md.
Workflow
Step 1: Fetch Portfolio Data via Alpaca MCP
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
What ships with it
10 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- README.md 11 KB
- references/alpaca-mcp-setup.md 9.7 KB
- references/asset-allocation.md 17 KB
- references/diversification-principles.md 18 KB
- references/portfolio-risk-metrics.md 17 KB
- references/position-evaluation.md 16 KB
- references/rebalancing-strategies.md 19 KB
- references/risk-profile-questionnaire.md 19 KB
- references/target-allocations.md 19 KB
- scripts/test_alpaca_connection.py 10 KB runs code
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 751 lines · 66 tokens per session scan A 863c837a38bd
portfolio-manager is a skill published in the GitHub repository nicepkg/ai-workflow (288 stars, last pushed 9mo ago), licensed MIT. It adds 66 tokens to every session and 5,045 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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