← 返回 Skills 市场
Unbeatable Condor Strategy
作者
jinntrance
· GitHub ↗
· v1.0.0
· MIT-0
134
总下载
0
收藏
0
当前安装
1
版本数
在 OpenClaw 中安装
/install unbeatable-condor-strategy
功能描述
Check daily if given stocks hit the 4% volatility threshold condor signal. 无敌鹰式策略
安全使用建议
This skill appears coherent and contains only the expected operations (downloading market data, feature engineering, LightGBM training, and printing strikes). Before installing/running: (1) run it in an isolated Python environment (virtualenv) to avoid dependency conflicts; (2) be aware it fetches live market data from Yahoo via yfinance (requires network access); (3) LightGBM may need build tools or a compatible wheel on your OS; (4) this is a signal generator only — it prints recommended strikes but does not place orders; verify and backtest strategy logic yourself before risking capital; (5) if you need full assurance, review the script locally line-by-line (it is short and readable) or run it on non-production data first.
功能分析
Type: OpenClaw Skill
Name: unbeatable-condor-strategy
Version: 1.0.0
The skill bundle is a quantitative trading tool designed to generate Iron Condor option signals using machine learning. The script `condor_signals.py` fetches historical market data via the `yfinance` library and trains a LightGBM model to predict price volatility boundaries. All code logic and instructions in `SKILL.md` are consistent with the stated financial analysis purpose, with no evidence of data exfiltration, malicious execution, or prompt injection.
能力评估
Purpose & Capability
The name/description (condor/volatility-based signal) align with the provided script: it downloads historical price data, engineers features, trains LightGBM quantile regressors, and emits a 4% width signal. Required resources (pandas, numpy, lightgbm, yfinance) are appropriate for the stated task.
Instruction Scope
SKILL.md instructs the agent to install the listed Python packages and run condor_signals.py with tickers. The script only accesses market data via yfinance, computes indicators, trains models, and prints signals. It does not read unrelated local files, environment variables, or transmit data to custom endpoints.
Install Mechanism
No install spec is provided (instruction-only). The README recommends pip-installing common Python libraries. This is a low-risk, expected install pattern. Note: LightGBM can require build tooling on some systems (compilation or a wheel).
Credentials
The skill requests no environment variables, no credentials, and no config paths. Network access to fetch market data (yfinance/Yahoo) is necessary and proportional to the purpose.
Persistence & Privilege
always is false and the skill makes no persistent modifications to the agent or system. It does not store tokens or alter other skills' configuration.
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 unbeatable-condor-strategy - 安装完成后，直接呼叫该 Skill 的名称或使用
/unbeatable-condor-strategy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
Initial release of the unbeatable-condor-strategy skill.
- Detects daily if specific stocks meet a 4% volatility threshold for triggering the Condor signal.
- Uses LightGBM quantile regression on historic price data to predict safe and profitable short iron condor or strangle opportunities.
- Provides recommended strike prices for selling options if a signal is triggered.
- Advises risk management steps and allocation limits when a signal occurs.
- Clearly informs users if the volatility threshold isn't met, suggesting no trade.
元数据
常见问题
Unbeatable Condor Strategy 是什么？
Check daily if given stocks hit the 4% volatility threshold condor signal. 无敌鹰式策略. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 134 次。
如何安装 Unbeatable Condor Strategy？
在 OpenClaw 或 Claude Code 对话框中运行命令「/install unbeatable-condor-strategy」即可一键安装，无需额外配置。
Unbeatable Condor Strategy 是免费的吗？
是的，Unbeatable Condor Strategy 完全免费，采用 MIT-0 许可证，可自由下载、安装和使用。
Unbeatable Condor Strategy 支持哪些平台？
Unbeatable Condor Strategy 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 Unbeatable Condor Strategy？
由 jinntrance（@jinntrance）开发并维护，当前版本 v1.0.0。
推荐 Skills