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quant-trading-backtrader
作者
gmsx000-cloud
· GitHub ↗
· v1.0.0
985
总下载
1
收藏
7
当前安装
1
版本数
在 OpenClaw 中安装
/install quant-trading-backtrader
功能描述
Build, backtest, and optimize quantitative trading strategies in Python using Backtrader with support for indicators, risk management, and reporting.
安全使用建议
This package behaves like a simple Backtrader example and contains no obvious exfiltration or secret access, but proceed cautiously because the source is unknown and the bundle contains a suspicious npm-style package.json that lists Python packages (likely a packaging mistake). Before running: 1) Verify the publisher or obtain the SKILL from a trusted source. 2) Inspect code yourself (you already have examples/sma_crossover.py) and search for any network calls or subprocess execution. 3) Run in an isolated environment (virtualenv or VM) and avoid running pip install globally — malicious or typo-squatted PyPI packages are a general risk. 4) If you plan to install dependencies, pin known-good package versions from trusted indexes, and consider auditing the actual PyPI packages (or use a vetted wheel). If you need higher assurance, request the upstream source/repository or a maintained release rather than this anonymous bundle.
功能分析
Type: OpenClaw Skill
Name: quant-trading-backtrader
Version: 1.0.0
The skill bundle is benign. It provides a quantitative trading backtesting tool using the Backtrader framework. The `SKILL.md` file contains standard instructions and usage examples without any prompt injection attempts. The `examples/sma_crossover.py` script uses the `os` module solely for creating and then cleaning up a temporary CSV file (`temp_data.csv`) that it generates for backtesting purposes, which is a legitimate and contained file system operation. There is no evidence of data exfiltration, malicious execution, persistence mechanisms, or other harmful behaviors.
能力评估
Purpose & Capability
Name, description, SKILL.md, and the included example (sma_crossover.py) all align: they implement/backtest a simple SMA crossover using Backtrader, demonstrate stop-loss handling, generate synthetic CSV data, run a backtest, and delete the temp file. There are no requested env vars, binaries, or config paths that conflict with the trading/backtesting purpose.
Instruction Scope
Runtime instructions are narrowly scoped to installing Backtrader/matplotlib and using the provided templates/examples. The SKILL.md and example script only read/write a local temporary CSV, run backtests, and print logs. There are no instructions to read unrelated system files, access network endpoints, or exfiltrate data.
Install Mechanism
The skill is instruction-only (no install spec), which is low risk, but there's a package.json in the bundle listing Python packages (backtrader, matplotlib) as npm dependencies — an incoherence. This manifest is out of place (npm manifests normally list JS packages) and could indicate sloppy packaging or automated conversion; it does not itself install anything, but it is unexpected and should be verified.
Credentials
The skill requests no credentials or environment variables. The example script writes a temporary CSV (temp_data.csv) to the current directory and then removes it — file I/O is limited and proportional to its stated purpose. No sensitive environment access or unrelated credentials are requested.
Persistence & Privilege
The skill does not request persistent or elevated privileges. always is false, and there are no install hooks or configuration changes in the repository. The skill does not attempt to modify other skills or system-wide agent settings.
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 quant-trading-backtrader - 安装完成后,直接呼叫该 Skill 的名称或使用
/quant-trading-backtrader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 quant-trading-backtrader.
- Build and backtest quantitative trading strategies using the Backtrader framework in Python.
- Includes structured examples for indicator-based strategies, risk management (stop-loss, take-profit, position sizing), and reporting (trade logs, PNL).
- Supports flexible data input (CSV, pandas DataFrame).
- Provides template code and best practices for robust, research-driven strategy development.
- Example strategies included, such as a basic SMA crossover with stop-loss.
元数据
常见问题
quant-trading-backtrader 是什么?
Build, backtest, and optimize quantitative trading strategies in Python using Backtrader with support for indicators, risk management, and reporting. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 985 次。
如何安装 quant-trading-backtrader?
在 OpenClaw 或 Claude Code 对话框中运行命令「/install quant-trading-backtrader」即可一键安装,无需额外配置。
quant-trading-backtrader 是免费的吗?
是的,quant-trading-backtrader 完全免费(开源免费),可自由下载、安装和使用。
quant-trading-backtrader 支持哪些平台?
quant-trading-backtrader 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 quant-trading-backtrader?
由 gmsx000-cloud(@gmsx000-cloud)开发并维护,当前版本 v1.0.0。
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