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在 OpenClaw 中安装
/install crypto-self-learning
功能描述
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.
安全使用建议
Safe to install if you want a local trade journal and analysis helper. Review generated rules before applying them to MEMORY.md, use --dry-run first, keep backups of memory files, and do not treat learned rules as financial advice or allow them to trade automatically without human review.
功能分析
Type: OpenClaw Skill
Name: crypto-self-learning
Version: 1.0.0
The OpenClaw skill 'crypto-self-learning' is designed for local crypto trade analysis and rule generation. All scripts (`analyze.py`, `generate_rules.py`, `log_trade.py`, `update_memory.py`) operate on local JSON files within the skill's `data` directory. The `SKILL.md` instructions and the `update_memory.py` script's modification of `MEMORY.md` are directly aligned with the stated purpose of updating the agent's learned rules, without any evidence of prompt injection, data exfiltration, remote execution, or other malicious behaviors. Required binaries (`jq`, `python3`) are standard and appropriate for the task.
能力评估
Purpose & Capability
The scripts match the stated purpose of logging trades, analyzing patterns, generating local rules, and optionally adding those rules to agent memory; outputs may influence financial decisions and should be treated as advisory.
Instruction Scope
The SKILL.md command examples are explicit, and the memory update command requires a user-supplied MEMORY.md path with a documented dry-run option, though the default update command writes to that file.
Install Mechanism
There is no installer or obfuscated setup; the package contains visible Python scripts and a data file. SKILL.md references weekly_review.py, but that helper is not included, so that command should not be run from an unreviewed source.
Credentials
The artifact uses local Python and JSON files, with no network calls, exchange credentials, API keys, remote execution, or account actions observed.
Persistence & Privilege
Persistence is expected for this purpose: trades are stored under the skill data directory, generated rules are saved locally, and update_memory.py can rewrite the user-selected memory file.
如何使用
- 确保已安装 OpenClaw（本地或 Docker 部署）
- 在对话框中输入安装命令：
/install crypto-self-learning - 安装完成后，直接呼叫该 Skill 的名称或使用
/crypto-self-learning触发 - 根据 Skill 的参数说明提供必要输入，即可获得结构化输出
版本历史
v1.0.0
Self-learning system for crypto trading. Logs trades, analyzes patterns, generates rules, and auto-updates agent memory for continuous improvement.
元数据
常见问题
Crypto Self-Learning 是什么？
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. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 5969 次。
如何安装 Crypto Self-Learning？
在 OpenClaw 或 Claude Code 对话框中运行命令「/install crypto-self-learning」即可一键安装，无需额外配置。
Crypto Self-Learning 是免费的吗？
是的，Crypto Self-Learning 完全免费（开源免费），可自由下载、安装和使用。
Crypto Self-Learning 支持哪些平台？
Crypto Self-Learning 跨平台运行，可在任意部署了 OpenClaw / Claude Code 的环境中使用（cross-platform）。
谁开发了 Crypto Self-Learning？
由 totaleasy（@totaleasy）开发并维护，当前版本 v1.0.0。
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