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Install in OpenClaw
/install stock-strategy-backtester
Description
Backtest stock trading strategies on historical OHLCV data and report win rate, return, CAGR, drawdown, Sharpe ratio, and trade logs. Use when evaluating or...
Usage Guidance
Install only if you trust the publisher, and point it only at market-price CSV files you intend to analyze. Treat its output as research support, not financial advice.
Capability Analysis
Type: OpenClaw Skill
Name: stock-strategy-backtester
Version: 1.0.4
The `scripts/backtest_strategy.py` script takes a `--csv` argument, which is a file path. While the script's intended purpose is to read OHLCV data, an AI agent could potentially be prompted to supply a path to an arbitrary, sensitive CSV-formatted file on the system. The script would then read and process this file, and its contents (transformed into backtest metrics) would be included in the JSON output to stdout. This constitutes a data disclosure vulnerability, as an attacker could potentially trick the agent into revealing sensitive local file contents. However, the script itself does not exfiltrate data to external endpoints, install backdoors, or execute arbitrary commands, indicating a vulnerability rather than intentional malice.
Capability Assessment
Purpose & Capability
The stated purpose, agent prompt, reference material, and Python script consistently align around backtesting long-only stock strategies from OHLCV CSV files and reporting metrics and trade logs.
Instruction Scope
The instructions are user-directed examples for running a bundled script with explicit CSV and strategy parameters; they do not ask the agent to access unrelated files, credentials, accounts, or external services.
Install Mechanism
The package includes an executable Python script, so users should trust the publisher before running it, but the script uses only standard-library local CSV parsing and calculation.
Credentials
Local file reading is limited to the user-supplied --csv path and is proportional to the backtesting purpose; review found no network calls, package installs, environment-variable access, credential handling, or broad local indexing.
Persistence & Privilege
No background workers, startup hooks, persistent storage, privilege escalation, protected-path writes, credential/session access, or destructive file operations are evidenced.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install stock-strategy-backtester - After installation, invoke the skill by name or use
/stock-strategy-backtester - Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.4
Security hardening: simplified runtime script, removed optional file-output features, removed non-essential assets to reduce suspicious pattern surface.
v1.0.3
Deprecate 1.0.0 and 1.0.1; recommend 1.0.2+ only. Added explicit version notice in SKILL.md.
v1.0.2
Remove marketplace/publish scripts and keep only backtesting runtime to resolve suspicious pattern flag.
v1.0.1
Add A/B marketplace copy variants and Chinese listing text for conversion optimization.
v1.0.0
Initial release: stock strategy backtesting with win-rate and return analytics.
Metadata
Frequently Asked Questions
What is Stock Strategy Backtester?
Backtest stock trading strategies on historical OHLCV data and report win rate, return, CAGR, drawdown, Sharpe ratio, and trade logs. Use when evaluating or... It is an AI Agent Skill for Claude Code / OpenClaw, with 4501 downloads so far.
How do I install Stock Strategy Backtester?
Run "/install stock-strategy-backtester" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Stock Strategy Backtester free?
Yes, Stock Strategy Backtester is completely free (open-source). You can download, install and use it at no cost.
Which platforms does Stock Strategy Backtester support?
Stock Strategy Backtester is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created Stock Strategy Backtester?
It is built and maintained by taylen (@taylen); the current version is v1.0.4.
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