Stock API
zhangxiangliang/stock-api
Fetch real-time stock quotes, K-line (candlestick) history, and search symbols for China A-shares, Hong Kong, and US markets.
Trade and track stocks, ETFs, commodities, bonds, and forex.
$ npx skills add Signal-Execution-Labs/forex-trading-ai-agent --skill multi-asset -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install Signal-Execution-Labs/forex-trading-ai-agent multi-asset --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ 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-srcUse ~/.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/
Install the "multi-asset" agent skill from https://github.com/Signal-Execution-Labs/forex-trading-ai-agent/tree/main/skills/multi-asset into .claude/skills/multi-asset/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "multi-asset", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/Signal-Execution-Labs/forex-trading-ai-agent/tree/main/skills/multi-assetType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add Signal-Execution-Labs/forex-trading-ai-agent --skill multi-asset -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install Signal-Execution-Labs/forex-trading-ai-agent multi-asset --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Signal-Execution-Labs/forex-trading-ai-agent.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/multi-asset .agents/skills/multi-asset && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "multi-asset" agent skill from https://github.com/Signal-Execution-Labs/forex-trading-ai-agent/tree/main/skills/multi-asset into .agents/skills/multi-asset/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "multi-asset", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add Signal-Execution-Labs/forex-trading-ai-agent --skill multi-asset -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install Signal-Execution-Labs/forex-trading-ai-agent multi-asset --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Signal-Execution-Labs/forex-trading-ai-agent.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/multi-asset .cursor/skills/multi-asset && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "multi-asset" agent skill from https://github.com/Signal-Execution-Labs/forex-trading-ai-agent/tree/main/skills/multi-asset into .cursor/skills/multi-asset/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "multi-asset", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/Signal-Execution-Labs/forex-trading-ai-agent.git --path skills/multi-asset--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add Signal-Execution-Labs/forex-trading-ai-agent --skill multi-asset -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install Signal-Execution-Labs/forex-trading-ai-agent multi-asset --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Signal-Execution-Labs/forex-trading-ai-agent.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/multi-asset .gemini/skills/multi-asset && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "multi-asset" agent skill from https://github.com/Signal-Execution-Labs/forex-trading-ai-agent/tree/main/skills/multi-asset into .gemini/skills/multi-asset/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "multi-asset", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install Signal-Execution-Labs/forex-trading-ai-agent multi-assetInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add Signal-Execution-Labs/forex-trading-ai-agent --skill multi-asset -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/Signal-Execution-Labs/forex-trading-ai-agent.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/multi-asset .github/skills/multi-asset && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "multi-asset" agent skill from https://github.com/Signal-Execution-Labs/forex-trading-ai-agent/tree/main/skills/multi-asset into .github/skills/multi-asset/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "multi-asset", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add Signal-Execution-Labs/forex-trading-ai-agent --skill multi-asset -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install Signal-Execution-Labs/forex-trading-ai-agent multi-asset --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Signal-Execution-Labs/forex-trading-ai-agent.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/multi-asset .opencode/skills/multi-asset && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "multi-asset" agent skill from https://github.com/Signal-Execution-Labs/forex-trading-ai-agent/tree/main/skills/multi-asset into .opencode/skills/multi-asset/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "multi-asset", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
multi-assetTrade 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. 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.
4 steps, taken from the first numbered list in SKILL.md.
Read from SKILL.md and the folder at commit b8a6047. It shows what the files ask for, not the result of running them.
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.
Ships 1 file in scripts/ (Python), which the agent can run.
Shell commands in SKILL.md call:
python3From the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
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.
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.
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.
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.
.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.Vollständige Abdeckung aller Asset-Klassen in einem System.
# ~/.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
}
}| Broker | Region | Features |
|---|---|---|
| Interactive Brokers | Global | Full API, all assets |
| Trade Republic | EU | Stocks, ETFs, Crypto |
| Scalable Capital | EU | ETFs, Stocks |
| Degiro | EU | Low cost stocks |
| Alpaca | US | Commission-free API |
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}%)')
"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')
"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}')
"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}')
"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')
"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')
"| Class | Role | Target % |
|---|---|---|
| US Stocks | Growth | 35% |
| Intl Stocks | Diversification | 25% |
| Bonds | Stability, Income | 20% |
| Commodities | Inflation Hedge | 10% |
| Crypto | High Growth | 10% |
| Account Type | Best Assets |
|---|---|
| Taxable | Index 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
SKILL.md and 1 other file (scripts) in skills/multi-asset of Signal-Execution-Labs/forex-trading-ai-agent.
Open the folder on GitHubat commit b8a6047
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.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Multi Asset this skillSignal-Execution-Labs/forex-trading-ai-agent | 162 | — | ~2.5k | Automated safety check: Pass | MIT | |
| Stock APIzhangxiangliang/stock-api | 2k | — | ~507 | Automated safety check: Pass | MIT | |
| Tushare Datazillionare/zillionare | 321 | 2 repos | ~2.3k | Automated safety check: Pass | None | |
| Tradingview MCPatilaahmettaner/tradingview-mcp | 5k | — | ~1.3k | Automated safety check: Pass | MIT | |
| Digital Oraclekomako-workshop/digital-oracle | 875 | — | ~5.9k | Automated safety check: Pass | MIT | |
| Longbridge Researchhelsome/folio | 270 | 3 repos | ~2.1k | Automated safety check: Pass | MIT |
zhangxiangliang/stock-api
Fetch real-time stock quotes, K-line (candlestick) history, and search symbols for China A-shares, Hong Kong, and US markets.
zillionare/zillionare
面向中文自然语言的 Tushare 数据研究技能。用于把“看看这只股票最近怎么样”“帮我查财报趋势”“最近哪个板块最强”“北向资金在买什么”“给我导出一份行情数据”这类请求,转成可执行的数据获取、清洗、对比、筛选、导出与简要分析流程。适用于 A 股、指数、ETF/基金、财务、估值、资金流、公告新闻、板块概念与宏观数据等研究场景。
atilaahmettaner/tradingview-mcp
AI Trading Intelligence — live prices, 30+ technical indicators, backtesting (6 strategies), walk-forward overfitting detection, trade logs, equity curves, licensed news sentiment (Marketaux), and…
komako-workshop/digital-oracle
Answer prediction questions using market trading data, not opinions.
helsome/folio
Institution ratings, consensus price targets, EPS/revenue forecasts, finance calendar, shareholder data, fund holders, insider trades (SEC Form 4), short interest, industry rankings, peer group…
helsome/folio
Earnings analysis — pre- and post-earnings. An agent skill from helsome/folio.
Signal-Execution-Labs/forex-trading-ai-agent
Automatic portfolio rebalancing to maintain target allocations.
Signal-Execution-Labs/forex-trading-ai-agent
Set price alerts, volume alerts, indicator alerts (RSI/MACD), and news alerts for crypto trading.
Signal-Execution-Labs/forex-trading-ai-agent
Automated trading with strategy execution, risk management, position sizing, and stop-loss/take-profit.
Signal-Execution-Labs/forex-trading-ai-agent
Backtest trading strategies with historical data. An agent skill from Signal-Execution-Labs/forex-trading-ai-agent.
Signal-Execution-Labs/forex-trading-ai-agent
Connect to DeFi protocols for staking, lending, yield farming, and liquidity provision.
Signal-Execution-Labs/forex-trading-ai-agent
Track dividends, manage DRIP (reinvestment), forecast income, and optimize dividend portfolio.
Categories
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.
Multi Asset fits situations like: tasks that involve Stock and market analysis.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.