Tushare Data
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。
Set price alerts, volume alerts, indicator alerts (RSI/MACD), and news alerts for crypto trading.
$ npx skills add Signal-Execution-Labs/forex-trading-ai-agent --skill alert-system -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install Signal-Execution-Labs/forex-trading-ai-agent alert-system --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/alert-system .claude/skills/alert-system && 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 "alert-system" agent skill from https://github.com/Signal-Execution-Labs/forex-trading-ai-agent/tree/main/skills/alert-system into .claude/skills/alert-system/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "alert-system", 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/alert-systemType 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 alert-system -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install Signal-Execution-Labs/forex-trading-ai-agent alert-system --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/alert-system .agents/skills/alert-system && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "alert-system" agent skill from https://github.com/Signal-Execution-Labs/forex-trading-ai-agent/tree/main/skills/alert-system into .agents/skills/alert-system/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "alert-system", 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 alert-system -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install Signal-Execution-Labs/forex-trading-ai-agent alert-system --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/alert-system .cursor/skills/alert-system && 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 "alert-system" agent skill from https://github.com/Signal-Execution-Labs/forex-trading-ai-agent/tree/main/skills/alert-system into .cursor/skills/alert-system/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "alert-system", 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/alert-system--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 alert-system -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install Signal-Execution-Labs/forex-trading-ai-agent alert-system --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/alert-system .gemini/skills/alert-system && 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 "alert-system" agent skill from https://github.com/Signal-Execution-Labs/forex-trading-ai-agent/tree/main/skills/alert-system into .gemini/skills/alert-system/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "alert-system", 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 alert-systemInstalls 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 alert-system -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/alert-system .github/skills/alert-system && 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 "alert-system" agent skill from https://github.com/Signal-Execution-Labs/forex-trading-ai-agent/tree/main/skills/alert-system into .github/skills/alert-system/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "alert-system", 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 alert-system -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 alert-system --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/alert-system .opencode/skills/alert-system && 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 "alert-system" agent skill from https://github.com/Signal-Execution-Labs/forex-trading-ai-agent/tree/main/skills/alert-system into .opencode/skills/alert-system/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "alert-system", 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.
alert-systemSet price alerts, volume alerts, indicator alerts (RSI/MACD), and news alerts for crypto trading.
Alert System is an agent skill from Signal-Execution-Labs/forex-trading-ai-agent. Set price alerts, volume alerts, indicator alerts (RSI/MACD), and news alerts for crypto trading.
Its SKILL.md is about 1.6k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files, including scripts (for example `scripts/alert_monitor.py`).
It sits in Business, Finance & HR, covering Trading and backtesting. 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.
Alert System loads about 1.6k tokens when it runs. Until then it costs about 28 tokens; SKILL.md has 184 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). 184 words, ~1,579 tokens.
.claude/skills/alert-system/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.Real-time alerts for price movements, technical indicators, and market events.
Alerts stored in ~/.kit/alerts.json:
{
"alerts": [
{
"id": "alert_001",
"type": "price",
"symbol": "BTC/USDT",
"condition": "above",
"value": 50000,
"active": true,
"notify": ["telegram", "sound"]
}
]
}python3 -c "
import ccxt
import time
symbol = 'BTC/USDT'
target = 50000
exchange = ccxt.binance()
print(f'⏳ Watching {symbol} for price above \${target:,}...')
while True:
ticker = exchange.fetch_ticker(symbol)
price = ticker['last']
if price >= target:
print(f'🚨 ALERT: {symbol} is now \${price:,.2f} (above \${target:,})')
break
print(f'Current: \${price:,.2f}', end='\\r')
time.sleep(10)
"python3 -c "
import ccxt
import time
symbol = 'BTC/USDT'
target = 45000
exchange = ccxt.binance()
print(f'⏳ Watching {symbol} for price below \${target:,}...')
while True:
ticker = exchange.fetch_ticker(symbol)
price = ticker['last']
if price <= target:
print(f'🚨 ALERT: {symbol} dropped to \${price:,.2f} (below \${target:,})')
break
time.sleep(10)
"python3 -c "
import ccxt
import time
symbol = 'BTC/USDT'
threshold_pct = 5 # 5% move
exchange = ccxt.binance()
ticker = exchange.fetch_ticker(symbol)
start_price = ticker['last']
print(f'⏳ Watching {symbol} for {threshold_pct}% move from \${start_price:,.2f}...')
while True:
ticker = exchange.fetch_ticker(symbol)
price = ticker['last']
change_pct = ((price - start_price) / start_price) * 100
if abs(change_pct) >= threshold_pct:
direction = '📈' if change_pct > 0 else '📉'
print(f'🚨 {direction} {symbol} moved {change_pct:+.2f}% to \${price:,.2f}')
break
time.sleep(30)
"python3 -c "
import ccxt
import time
symbol = 'BTC/USDT'
volume_multiplier = 2 # 2x average volume
exchange = ccxt.binance()
# Get average volume (last 24 bars)
ohlcv = exchange.fetch_ohlcv(symbol, '1h', limit=24)
avg_volume = sum(c[5] for c in ohlcv) / len(ohlcv)
print(f'⏳ Watching {symbol} for volume spike (>{volume_multiplier}x avg)...')
print(f'Average hourly volume: {avg_volume:,.0f}')
while True:
ticker = exchange.fetch_ticker(symbol)
current_volume = ticker['quoteVolume'] / 24 # Rough hourly
if current_volume > avg_volume * volume_multiplier:
print(f'🚨 VOLUME SPIKE: {symbol} volume {current_volume:,.0f} ({current_volume/avg_volume:.1f}x average)')
break
time.sleep(60)
"python3 -c "
import ccxt
import ta
import pandas as pd
symbol = 'BTC/USDT'
exchange = ccxt.binance()
# Fetch OHLCV data
ohlcv = exchange.fetch_ohlcv(symbol, '1h', limit=100)
df = pd.DataFrame(ohlcv, columns=['timestamp', 'open', 'high', 'low', 'close', 'volume'])
# Calculate RSI
df['rsi'] = ta.momentum.RSIIndicator(df['close'], window=14).rsi()
current_rsi = df['rsi'].iloc[-1]
print(f'{symbol} RSI(14): {current_rsi:.1f}')
if current_rsi >= 70:
print('🔴 OVERBOUGHT - Consider taking profits')
elif current_rsi <= 30:
print('🟢 OVERSOLD - Potential buying opportunity')
else:
print('⚪ Neutral')
"python3 -c "
import ccxt
import ta
import pandas as pd
symbol = 'BTC/USDT'
exchange = ccxt.binance()
ohlcv = exchange.fetch_ohlcv(symbol, '4h', limit=100)
df = pd.DataFrame(ohlcv, columns=['timestamp', 'open', 'high', 'low', 'close', 'volume'])
macd = ta.trend.MACD(df['close'])
df['macd'] = macd.macd()
df['signal'] = macd.macd_signal()
df['histogram'] = macd.macd_diff()
current_hist = df['histogram'].iloc[-1]
prev_hist = df['histogram'].iloc[-2]
print(f'{symbol} MACD Histogram: {current_hist:.4f}')
if prev_hist < 0 and current_hist > 0:
print('🟢 BULLISH CROSSOVER - MACD crossed above signal')
elif prev_hist > 0 and current_hist < 0:
print('🔴 BEARISH CROSSOVER - MACD crossed below signal')
else:
direction = 'Bullish' if current_hist > 0 else 'Bearish'
print(f'⚪ No crossover - Currently {direction}')
"python3 -c "
import ccxt
import time
watchlist = ['BTC/USDT', 'ETH/USDT', 'SOL/USDT', 'XRP/USDT']
exchange = ccxt.binance()
print('📊 Crypto Price Monitor')
print('=' * 50)
while True:
for symbol in watchlist:
ticker = exchange.fetch_ticker(symbol)
price = ticker['last']
change = ticker['percentage']
emoji = '🟢' if change >= 0 else '🔴'
print(f'{emoji} {symbol:12} \${price:>10,.2f} {change:+6.2f}%')
print('-' * 50)
time.sleep(60)
"~/.kit/alerts.json| Type | Trigger | Use Case |
|---|---|---|
price_above | Price >= target | Take profit |
price_below | Price <= target | Stop loss, buy dip |
pct_change | X% move in Y time | Volatility |
volume_spike | Volume > X * average | Breakout |
rsi_high | RSI >= 70 | Overbought |
rsi_low | RSI <= 30 | Oversold |
macd_cross | MACD/Signal cross | Trend change |
© 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/alert-system of Signal-Execution-Labs/forex-trading-ai-agent.
Open the folder on GitHubat commit b8a6047
Alert System 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 |
|---|---|---|---|---|---|---|
| Alert System this skillSignal-Execution-Labs/forex-trading-ai-agent | 162 | — | ~1.6k | 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 | |
| Polyclawchainstacklabs/polyclaw | 359 | 1 repos | ~2k | Automated safety check: Pass | Apache-2.0 | |
| Markdownfacioquo/stock-indicators-dotnet | 1.2k | — | ~812 | Automated safety check: Pass | Apache-2.0 |
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.
chainstacklabs/polyclaw
Trade on Polymarket via split + CLOB execution. An agent skill from chainstacklabs/polyclaw.
facioquo/stock-indicators-dotnet
Format and lint Markdown in this repository against GitHub Flavored Markdown and its markdownlint-cli2 configuration — headers, lists, code fences, callouts (VitePress containers on docs-site pages…
MobiusQuant/OpenMobius-skill
Provides multi-school trading Q&A, chart/OHLCV analysis, annotation, and fresh-market workflows covering ICT/SMC, ChanLun, Wyckoff, Price Action, Order Flow, VSA, and Elliott Wave.
Signal-Execution-Labs/forex-trading-ai-agent
Automatic portfolio rebalancing to maintain target allocations.
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.
Signal-Execution-Labs/forex-trading-ai-agent
Connect to crypto exchanges (Binance, Kraken, Coinbase, etc.).
Categories
Set price alerts, volume alerts, indicator alerts (RSI/MACD), and news alerts for crypto trading. Alert System is an agent skill from Signal-Execution-Labs/forex-trading-ai-agent. Set price alerts, volume alerts, indicator alerts (RSI/MACD), and news alerts for crypto trading.
Alert System fits situations like: tasks that involve Trading and backtesting.
Run `npx skills add Signal-Execution-Labs/forex-trading-ai-agent --skill alert-system -a claude-code`. Or copy the skill folder (skills/alert-system in Signal-Execution-Labs/forex-trading-ai-agent) into .claude/skills/alert-system 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 alert-system -a codex`. Or copy the skill folder (skills/alert-system in Signal-Execution-Labs/forex-trading-ai-agent) into .agents/skills/alert-system 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 alert-system -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/alert-system, .gemini/skills/alert-system, .github/skills/alert-system and .opencode/skills/alert-system in your project.
Going by SKILL.md and its folder, Alert System 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.
Alert System is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 1.6k tokens (SKILL.md is roughly 6.3k 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 Alert System: Tushare Data (zillionare/zillionare, 321 stars), Tradingview MCP (atilaahmettaner/tradingview-mcp, 5k stars), Digital Oracle (komako-workshop/digital-oracle, 875 stars) and Polyclaw (chainstacklabs/polyclaw, 359 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.