Self-learning system for crypto trading. Logs trades with full context (indicators, market conditions), analyzes patterns of wins/losses, and auto-updates trading rules. Use to log trades, analyze performance, identify what works/fails, and continuously improve trading accuracy.
数据来源:ClawHub。 在 ClawSkills 查看
选择你使用的 Agent
方法一:命令行安装(推荐)
推荐(无需提前安装 clawhub)
npx clawhub@latest --dir ~/.claude/skills install crypto-self-learning或使用 clawhub CLI(需提前安装)
clawhub --dir ~/.claude/skills install crypto-self-learning⚠️ 需要 Node.js 18+,没有 Node?请使用下方方法二直接下载 ZIP。 安装 Node.js →
方法二:手动下载安装(无需 Node)
下载 ZIP,解压后将文件夹放到以下路径,重启 Agent 即可:
安装路径
~/.claude/skills/crypto-self-learning/💡解压后将文件夹放到上方路径,重启 Agent 即可生效
--- name: crypto-self-learning description: Self-learning system for crypto trading. Logs trades with full context (indicators, market conditions), analyzes patterns of wins/losses, and auto-updates trading rules. Use to log trades, analyze performance, identify what works/fails, and continuously improve trading accuracy. metadata: {"openclaw":{"emoji":"🧠","requires":{"bins":["jq","python3"]}}} ---
AI-powered self-improvement system for crypto trading. Learn from every trade to increase accuracy over time.
Every trade is a lesson. This skill:
After EVERY trade (win or loss), log it:
python3 {baseDir}/scripts/log_trade.py \
--symbol BTCUSDT \
--direction LONG \
--entry 78000 \
--exit 79500 \
--pnl_percent 1.92 \
--leverage 5 \
--reason "RSI oversold + support bounce" \
--indicators '{"rsi": 28, "macd": "bullish_cross", "ma_position": "above_50"}' \
--market_context '{"btc_trend": "up", "dxy": 104.5, "russell": "up", "day": "tuesday", "hour": 14}' \
--result WIN \
--notes "Clean setup, followed the plan"
| Field | Description | Example | |-------|-------------|---------| | --symbol | Trading pair | BTCUSDT | | --direction | LONG or SHORT | LONG | | --entry | Entry price | 78000 | | --exit | Exit price | 79500 | | --pnl_percent | Profit/Loss % | 1.92 or -2.5 | | --result | WIN or LOSS | WIN |
| Field | Description | |-------|-------------| | --leverage | Leverage used | | --reason | Why you entered | | --indicators | JSON with indicators at entry | | --market_context | JSON with macro conditions | | --notes | Post-trade observations |
Run analysis to discover patterns:
python3 {baseDir}/scripts/analyze.py
Outputs:
python3 {baseDir}/scripts/analyze.py --symbol BTCUSDT
python3 {baseDir}/scripts/analyze.py --direction LONG
python3 {baseDir}/scripts/analyze.py --min-trades 10
Extract actionable rules from your trade history:
python3 {baseDir}/scripts/generate_rules.py
This analyzes patterns and outputs rules like:
🚫 AVOID: LONG when RSI > 70 (win rate: 23%, n=13)
✅ PREFER: SHORT on Mondays (win rate: 78%, n=9)
⚠️ CAUTION: Trades with leverage > 10x (win rate: 35%, n=20)
Apply learned rules to agent memory:
python3 {baseDir}/scripts/update_memory.py --memory-path /path/to/MEMORY.md
This appends a "## 🧠 Learned Rules" section with data-driven insights.
python3 {baseDir}/scripts/update_memory.py --memory-path /path/to/MEMORY.md --dry-run
python3 {baseDir}/scripts/log_trade.py --list
python3 {baseDir}/scripts/log_trade.py --list --last 10
python3 {baseDir}/scripts/log_trade.py --stats
Run weekly to see progress:
python3 {baseDir}/scripts/weekly_review.py
Generates:
Trades are stored in {baseDir}/data/trades.json:
{
"trades": [
{
"id": "uuid",
"timestamp": "2026-02-02T13:00:00Z",
"symbol": "BTCUSDT",
"direction": "LONG",
"entry": 78000,
"exit": 79500,
"pnl_percent": 1.92,
"result": "WIN",
"indicators": {...},
"market_context": {...}
}
]
}
Add to tess-cripto's workflow:
--- Skill by Total Easy Software - Learn from every trade 🧠📈
安装 Crypto Self-Learning 后,可以对 AI 说这些话来触发它
Help me get started with Crypto Self-Learning
Explains what Crypto Self-Learning does, walks through the setup, and runs a quick demo based on your current project
Use Crypto Self-Learning to self-learning system for crypto trading
Invokes Crypto Self-Learning with the right parameters and returns the result directly in the conversation
What can I do with Crypto Self-Learning in my finance & investment workflow?
Lists the top use cases for Crypto Self-Learning, with example commands for each scenario
将技能文件夹放到 ~/.claude/skills/crypto-self-learning/ 目录(个人级,所有项目可用),或 .claude/skills/crypto-self-learning/(项目级)。重启 AI 客户端后,用 /crypto-self-learning 主动调用,或让 AI 根据上下文自动发现并使用。
Crypto Self-Learning 支持 Claude、Cursor、OpenClaw,可与这些 AI 平台无缝集成,扩展其能力。
Crypto Self-Learning 可免费安装使用。请查阅仓库了解许可证信息。
Self-learning system for crypto trading. Logs trades with full context (indicators, market conditions), analyzes patterns of wins/losses, and auto-updates trading rules. Use to log trades, analyze performance, identify what works/fails, and continuously improve trading accuracy.
Automate my finance & investment tasks using Crypto Self-Learning
Identifies repetitive steps in your workflow and sets up Crypto Self-Learning to handle them automatically
Crypto Self-Learning 属于「Finance & Investment」分类,该分类的技能帮助 AI 智能体在此领域执行专业任务。