Trade and track stocks, ETFs, commodities, bonds, and forex.

MITAuto-check passedBusiness, Finance & HR

Install Multi Asset

skills CLI
$ npx skills add Signal-Execution-Labs/forex-trading-ai-agent --skill multi-asset -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install Signal-Execution-Labs/forex-trading-ai-agent multi-asset --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/Signal-Execution-Labs/forex-trading-ai-agent.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/multi-asset .claude/skills/multi-asset && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
multi-asset
GitHub stars
162
Token cost
~2.5k tokens
SKILL.md length
153 words
Files
2 (incl. scripts)
Skills in repo
11
Repo updated
First seen
Licence
MIT

At a glance

Trade and track stocks, ETFs, commodities, bonds, and forex.

  • Works in 4 steps: Fixed schedule - Same day each week/month → Ignore prices - Invest regardless of… → Automate - Remove emotion → …
  • Tasks that involve Stock and market analysis
  • SKILL.md covers Overview, 🤖 AUTO-PILOT MODE, Supported Brokers and Commands, plus 1 more section
  • Runs Python scripts from its folder; calls python3

What it does

Multi Asset is an agent skill from Signal-Execution-Labs/forex-trading-ai-agent. Trade and track stocks, ETFs, commodities, bonds, and forex. Unified portfolio across all asset classes.

Its SKILL.md is about 2.5k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files, including scripts (for example `scripts/portfolio_overview.py`).

It sits in Business, Finance & HR, covering Stock and market analysis. The repository describes itself as: About AI quantitative trading platform for crypto, stocks, and forex with backtesting, live trading, market data, and multi-agent research.vibe-trading…. The licence is MIT.

When your agent uses it

  • Tasks that involve Stock and market analysis

Example prompts

  • “/multi-asset”

Requirements

  • Python 3

Workflow steps

4 steps, taken from the first numbered list in SKILL.md.

  1. Fixed schedule - Same day each week/month
  2. Ignore prices - Invest regardless of market
  3. Automate - Remove emotion
  4. Rebalance - Quarterly or threshold-based

What it can do on your machine

Read from SKILL.md and the folder at commit b8a6047. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 1 file in scripts/ (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • python3

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Multi Asset loads about 2.5k tokens when it runs. Until then it costs about 29 tokens; SKILL.md has 153 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~29
When it runs · the whole SKILL.md, loaded when a task matches
~2.5k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from Signal-Execution-Labs/forex-trading-ai-agent at commit b8a6047, republished under its MIT licence (© Signal-Execution-Labs). 153 words, ~2,490 tokens.

Download SKILL.mdSave it as .claude/skills/multi-asset/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
multi-asset
description
Trade and track stocks, ETFs, commodities, bonds, and forex. Unified portfolio across all asset classes.

Multi-Asset

Vollständige Abdeckung aller Asset-Klassen in einem System.

Overview

  • Stocks - US, EU, Emerging Markets
  • ETFs - Index, Sector, Thematic
  • Bonds - Government, Corporate
  • Commodities - Gold, Silver, Oil
  • Forex - Major pairs

🤖 AUTO-PILOT MODE

python
# ~/.kit/config/multi-asset.json
{
  "auto_pilot": {
    "enabled": true,
    "brokers": {
      "interactive_brokers": {"enabled": true, "account": "U1234567"},
      "trade_republic": {"enabled": true},
      "scalable": {"enabled": true}
    },
    "strategies": {
      "dca": {
        "enabled": true,
        "schedule": "weekly",
        "day": "monday",
        "investments": [
          {"symbol": "VTI", "amount_eur": 200},
          {"symbol": "VXUS", "amount_eur": 100},
          {"symbol": "BND", "amount_eur": 50}
        ]
      },
      "value_averaging": {
        "enabled": false,
        "target_growth_pct": 0.5
      },
      "rebalancing": {
        "enabled": true,
        "trigger": "quarterly"
      }
    },
    "alerts": {
      "price_target": true,
      "earnings": true,
      "dividend_ex_date": true,
      "52w_high_low": true
    },
    "require_approval": {
      "trades_above_eur": 1000,
      "new_positions": true
    }
  },
  "target_allocation": {
    "us_stocks": 35,
    "intl_stocks": 25,
    "bonds": 20,
    "commodities": 10,
    "crypto": 10
  }
}

Supported Brokers

BrokerRegionFeatures
Interactive BrokersGlobalFull API, all assets
Trade RepublicEUStocks, ETFs, Crypto
Scalable CapitalEUETFs, Stocks
DegiroEULow cost stocks
AlpacaUSCommission-free API

Commands

Full Portfolio Overview
bash
python3 -c "
import yfinance as yf

portfolio = {
    'stocks': [
        {'symbol': 'AAPL', 'shares': 50, 'cost': 150},
        {'symbol': 'MSFT', 'shares': 30, 'cost': 280},
        {'symbol': 'GOOGL', 'shares': 20, 'cost': 120},
    ],
    'etfs': [
        {'symbol': 'VTI', 'shares': 100, 'cost': 200},
        {'symbol': 'VXUS', 'shares': 80, 'cost': 55},
        {'symbol': 'BND', 'shares': 50, 'cost': 75},
    ],
    'commodities': [
        {'symbol': 'GLD', 'shares': 25, 'cost': 170},
    ]
}

print('🌍 MULTI-ASSET PORTFOLIO')
print('=' * 80)

total_value = 0
total_cost = 0
by_class = {}

for asset_class, positions in portfolio.items():
    class_value = 0
    print(f'\\n📁 {asset_class.upper()}')
    print('-' * 80)
    
    for pos in positions:
        try:
            stock = yf.Ticker(pos['symbol'])
            price = stock.info.get('currentPrice', stock.info.get('regularMarketPrice', 0))
            value = pos['shares'] * price
            cost = pos['shares'] * pos['cost']
            pnl = value - cost
            pnl_pct = (pnl / cost * 100) if cost > 0 else 0
            
            emoji = '🟢' if pnl >= 0 else '🔴'
            print(f\"{pos['symbol']:8} {pos['shares']:>6} @ \${price:>8.2f} = \${value:>10,.2f} {emoji} {pnl_pct:>+6.1f}%\")
            
            class_value += value
            total_cost += cost
        except Exception as e:
            print(f\"{pos['symbol']:8} Error: {e}\")
    
    by_class[asset_class] = class_value
    total_value += class_value

print()
print('=' * 80)
print('SUMMARY BY CLASS:')
for cls, val in by_class.items():
    pct = (val / total_value * 100) if total_value > 0 else 0
    print(f'  {cls:15} \${val:>12,.2f} ({pct:5.1f}%)')

print()
total_pnl = total_value - total_cost
total_pnl_pct = (total_pnl / total_cost * 100) if total_cost > 0 else 0
print(f'TOTAL VALUE: \${total_value:,.2f}')
print(f'TOTAL P&L:   \${total_pnl:+,.2f} ({total_pnl_pct:+.1f}%)')
"
Dollar-Cost Averaging (DCA) Execution
bash
python3 -c "
import yfinance as yf
from datetime import datetime

# Weekly DCA plan
dca_plan = [
    {'symbol': 'VTI', 'amount_eur': 200, 'name': 'US Total Market'},
    {'symbol': 'VXUS', 'amount_eur': 100, 'name': 'International'},
    {'symbol': 'BND', 'amount_eur': 50, 'name': 'Bonds'},
]

eur_usd = 1.08  # Exchange rate

print('💰 DCA EXECUTION')
print('=' * 60)
print(f'Date: {datetime.now().strftime(\"%Y-%m-%d\")}')
print(f'EUR/USD: {eur_usd}')
print()

total_invested = 0

for plan in dca_plan:
    try:
        stock = yf.Ticker(plan['symbol'])
        price = stock.info.get('currentPrice', 100)
        
        amount_usd = plan['amount_eur'] * eur_usd
        shares = amount_usd / price
        
        print(f\"{plan['symbol']:6} ({plan['name']})\")
        print(f\"  Budget: €{plan['amount_eur']} = \${amount_usd:.2f}\")
        print(f\"  Price:  \${price:.2f}\")
        print(f\"  Shares: {shares:.4f}\")
        print()
        
        total_invested += plan['amount_eur']
        
        # Execute order:
        # broker.buy(plan['symbol'], shares)
        
    except Exception as e:
        print(f\"{plan['symbol']}: Error - {e}\")

print(f'Total Invested: €{total_invested}')
print()
print('⚠️ DRY RUN - Enable auto_pilot to execute')
"
Sector Analysis
bash
python3 -c "
import yfinance as yf

# Sector ETFs
sectors = {
    'Technology': 'XLK',
    'Healthcare': 'XLV',
    'Financials': 'XLF',
    'Consumer Disc.': 'XLY',
    'Industrials': 'XLI',
    'Energy': 'XLE',
    'Utilities': 'XLU',
    'Materials': 'XLB',
    'Real Estate': 'XLRE',
    'Comm. Services': 'XLC',
    'Cons. Staples': 'XLP',
}

print('📊 SECTOR PERFORMANCE')
print('=' * 60)

performances = []

for name, symbol in sectors.items():
    try:
        etf = yf.Ticker(symbol)
        hist = etf.history(period='1mo')
        
        if len(hist) > 1:
            start = hist['Close'].iloc[0]
            end = hist['Close'].iloc[-1]
            change = ((end - start) / start) * 100
            performances.append((name, change))
    except:
        pass

# Sort by performance
performances.sort(key=lambda x: x[1], reverse=True)

for name, change in performances:
    emoji = '🟢' if change >= 0 else '🔴'
    bar = '█' * int(abs(change))
    print(f'{emoji} {name:18} {change:>+6.1f}% {bar}')
"
Bond Ladder Builder
bash
python3 -c "
# Bond ladder for stable income
ladder = [
    {'maturity': '1Y', 'etf': 'SHY', 'allocation': 20, 'yield': 4.8},
    {'maturity': '3Y', 'etf': 'IEI', 'allocation': 20, 'yield': 4.2},
    {'maturity': '7Y', 'etf': 'IEF', 'allocation': 20, 'yield': 4.0},
    {'maturity': '10Y', 'etf': 'TLH', 'allocation': 20, 'yield': 4.3},
    {'maturity': '20Y', 'etf': 'TLT', 'allocation': 20, 'yield': 4.5},
]

total_investment = 50000

print('🪜 BOND LADDER')
print('=' * 60)
print(f'Total Investment: \${total_investment:,}')
print()
print(f'{\"Maturity\":10} {\"ETF\":6} {\"Amount\":>12} {\"Yield\":>8} {\"Income\":>10}')
print('-' * 60)

total_income = 0

for rung in ladder:
    amount = total_investment * (rung['allocation'] / 100)
    income = amount * (rung['yield'] / 100)
    total_income += income
    
    print(f\"{rung['maturity']:10} {rung['etf']:6} \${amount:>11,.0f} {rung['yield']:>7.1f}% \${income:>9,.0f}\")

print('-' * 60)
avg_yield = (total_income / total_investment) * 100
print(f'{\"TOTAL\":10} {\"\":6} \${total_investment:>11,} {avg_yield:>7.1f}% \${total_income:>9,.0f}')
print()
print(f'Monthly Income: \${total_income/12:,.0f}')
"
Commodity Exposure
bash
python3 -c "
import yfinance as yf

commodities = {
    'Gold': 'GLD',
    'Silver': 'SLV',
    'Oil': 'USO',
    'Natural Gas': 'UNG',
    'Agriculture': 'DBA',
    'Copper': 'CPER',
}

print('🪙 COMMODITY PRICES')
print('=' * 50)

for name, symbol in commodities.items():
    try:
        etf = yf.Ticker(symbol)
        hist = etf.history(period='5d')
        
        if len(hist) > 0:
            price = hist['Close'].iloc[-1]
            prev = hist['Close'].iloc[0]
            change = ((price - prev) / prev) * 100
            emoji = '🟢' if change >= 0 else '🔴'
            print(f'{name:15} \${price:>8.2f} {emoji} {change:>+5.1f}%')
    except Exception as e:
        print(f'{name:15} Error')
"
Auto-Pilot: Full Automation
bash
python3 -c "
from datetime import datetime

print('🤖 MULTI-ASSET AUTO-PILOT')
print('=' * 50)
print(f'Running: {datetime.now().isoformat()}')
print()

# Check what day it is for DCA
day = datetime.now().strftime('%A')

tasks = [
    (f'📅 Check DCA schedule (Today: {day})', 'DCA due: Monday'),
    ('💰 Execute weekly DCA', 'Pending approval'),
    ('📊 Rebalance check', 'Within tolerance'),
    ('🔔 Earnings calendar', 'AAPL reports in 5 days'),
    ('💸 Dividend tracker', 'MSFT ex-date tomorrow'),
    ('📈 Performance update', 'Portfolio +2.3% MTD'),
]

for task, status in tasks:
    print(f'{task}')
    print(f'  → {status}')
    print()

# Pending actions requiring approval
print('📋 PENDING APPROVALS:')
print('  1. DCA: Buy €350 worth of VTI, VXUS, BND')
print('     Reply \"APPROVE DCA\" to execute')
print()
print('Next check: Tomorrow 09:00')
"

Workflow

Asset Class Roles
ClassRoleTarget %
US StocksGrowth35%
Intl StocksDiversification25%
BondsStability, Income20%
CommoditiesInflation Hedge10%
CryptoHigh Growth10%
DCA Best Practices
  1. Fixed schedule - Same day each week/month
  2. Ignore prices - Invest regardless of market
  3. Automate - Remove emotion
  4. Rebalance - Quarterly or threshold-based
Tax-Efficient Placement
Account TypeBest Assets
TaxableIndex ETFs (low turnover)
Tax-Deferred (401k)Bonds, REITs
Tax-Free (Roth)High growth stocks

© Signal-Execution-Labs, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 1 other file (scripts) in skills/multi-asset of Signal-Execution-Labs/forex-trading-ai-agent.

  • SKILL.md
  • scripts/portfolio_overview.py

Open the folder on GitHubat commit b8a6047

Compare with similar skills

Multi Asset next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Multi Asset compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Multi Asset this skillSignal-Execution-Labs/forex-trading-ai-agent162—~2.5kAutomated safety check: PassMIT
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Tushare Datazillionare/zillionare3212 repos~2.3kAutomated safety check: PassNone
Tradingview MCPatilaahmettaner/tradingview-mcp5k—~1.3kAutomated safety check: PassMIT
Digital Oraclekomako-workshop/digital-oracle875—~5.9kAutomated safety check: PassMIT
Longbridge Researchhelsome/folio2703 repos~2.1kAutomated safety check: PassMIT

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Questions about Multi Asset

What does Multi Asset do?

Trade and track stocks, ETFs, commodities, bonds, and forex. Multi Asset is an agent skill from Signal-Execution-Labs/forex-trading-ai-agent. Trade and track stocks, ETFs, commodities, bonds, and forex.

When should I use Multi Asset?

Multi Asset fits situations like: tasks that involve Stock and market analysis.

How do I install Multi Asset in Claude Code?

Run `npx skills add Signal-Execution-Labs/forex-trading-ai-agent --skill multi-asset -a claude-code`. Or copy the skill folder (skills/multi-asset in Signal-Execution-Labs/forex-trading-ai-agent) into .claude/skills/multi-asset in your project. Claude Code loads it when a task matches its description.

How do I install Multi Asset in Codex?

Run `npx skills add Signal-Execution-Labs/forex-trading-ai-agent --skill multi-asset -a codex`. Or copy the skill folder (skills/multi-asset in Signal-Execution-Labs/forex-trading-ai-agent) into .agents/skills/multi-asset in your project. Codex loads it when a task matches its description.

Can I use Multi Asset in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add Signal-Execution-Labs/forex-trading-ai-agent --skill multi-asset -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/multi-asset, .gemini/skills/multi-asset, .github/skills/multi-asset and .opencode/skills/multi-asset in your project.

What does Multi Asset need to run?

Going by SKILL.md and its folder, Multi Asset needs Python for the scripts in its folder and the command-line tools its instructions call (python3). Our summary lists: Python 3.

Does Multi Asset access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Multi Asset safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Multi Asset use?

Multi Asset is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Multi Asset use?

About 2.5k tokens (SKILL.md is roughly 10k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Multi Asset?

Skills that share tags, products or a category with Multi Asset: Stock API (zhangxiangliang/stock-api, 2k stars), Tushare Data (zillionare/zillionare, 321 stars), Tradingview MCP (atilaahmettaner/tradingview-mcp, 5k stars) and Digital Oracle (komako-workshop/digital-oracle, 875 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Multi Asset?

Signal-Execution-Labs (a GitHub organization) maintains it in Signal-Execution-Labs/forex-trading-ai-agent, which has 162 GitHub stars. The repository holds 11 skills in this directory. The repository was last updated on September 14, 2026.

Source: Signal-Execution-Labs/forex-trading-ai-agent on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.