Stock Analyzer
v1.0.0提供实时股价、技术指标、基本面数据分析及基于历史数据的价格预测，支持生成详细Markdown报告和图表。
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MIT-0
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LicenseMIT-0 · Free to use, modify, and redistribute. No attribution required.
Security Scan
OpenClaw
Benign
high confidencePurpose & Capability
Name/description (stock analysis, indicators, fundamentals, simple prediction) match the included Python implementation and SKILL.md. Required libraries (yfinance, pandas, numpy, matplotlib, sklearn for prediction) are appropriate and expected for the stated features.
Instruction Scope
SKILL.md instructs copying the skill into the skills directory and installing Python deps, and the code reads only the declared optional config file (~/.openclaw/secrets/stock-analyzer.json) and writes reports/charts to local output directories. There are no instructions to read unrelated system files, access credentials, or send data to external endpoints beyond yfinance (Yahoo Finance).
Install Mechanism
No remote download or archive extraction is used. The provided install.sh simply copies files into ~/.openclaw/skills/ and checks for Python dependencies. This local install behavior is low-risk compared to fetching and executing arbitrary remote code.
Credentials
The skill does not request environment variables or credentials. It uses a single optional config file in the user's home directory for defaults and an output_dir for reports; these are proportional to the functionality. Minor note: SKILL.md's pip install line omits scikit-learn while install.sh's dependency-check message references scikit-learn (used by predict), so the documentation/installer mismatch should be fixed but is not a security red flag.
Persistence & Privilege
always is false and the skill does not request elevated or persistent platform-wide privileges. The install copies files into the user's skills directory only and does not modify other skills or system-wide configs.
Assessment
This skill appears coherent and implements the advertised features using yfinance and common Python libraries. Before installing: (1) run installation in a virtualenv and install the listed deps (note: prediction uses scikit-learn, so install scikit-learn if you need predict); (2) review or run the included code in a safe environment if you don't trust the unknown source; (3) be aware it will read an optional config at ~/.openclaw/secrets/stock-analyzer.json and write report/chart files to the specified output_dir—do not put secrets in that config; (4) understand predictions are simple (linear regression by default) and the tool is not investment advice. If you are uncomfortable installing code from an unknown author, prefer running the script in an isolated environment or decline installation.Like a lobster shell, security has layers — review code before you run it.
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License
MIT-0
Free to use, modify, and redistribute. No attribution required.