Super Trend Analysis
v1.0.1综合趋势分析技能，融合移动平均线、MACD、RSI、布林带等多种技术分析方法，生成趋势判断、买卖信号和可视化图表。使用场景：(1) "分析贵州茅台的趋势"，(2) "生成药明康德的技术分析报告"，(3) "判断当前是买入还是卖出信号"。
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by军舰@wang-junjian
MIT-0
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LicenseMIT-0 · Free to use, modify, and redistribute. No attribution required.
Security Scan
OpenClaw
Benign
high confidencePurpose & Capability
The name/description claim a multi-indicator technical analysis tool and the code + SKILL.md implement that: indicators.py computes SMA/EMA/MACD/RSI/Bollinger, analyze_trend.py generates reports, batch_analyze.py processes directories. Required capabilities (pandas/numpy/etc.) are proportional and expected for this purpose. There are no unrelated requirements (no cloud credentials, no unrelated binaries).
Instruction Scope
SKILL.md instructs the agent to run local Python scripts against local CSV files and to optionally generate plots; the actual scripts read CSVs, compute indicators, write markdown reports and CSVs to a local 'trend_reports' directory. There are no instructions to read unrelated system files, access environment secrets, or transmit data externally. Note: the --plot flag is present but plot generation is 'coming soon' in code (prints a placeholder).
Install Mechanism
This is instruction-only (no install spec). Dependencies are standard Python libs installed via 'pip install pandas numpy matplotlib seaborn ta' per SKILL.md — this is expected and traceable. No remote downloads or archive extraction are present in the skill bundle.
Credentials
The skill does not declare or use any environment variables, credentials, or config paths. All file access is limited to CSV inputs provided by the user and the local output directory. No secrets or external service tokens are requested.
Persistence & Privilege
Flags show no 'always' privilege and the skill does not modify other skills or system-wide agent settings. It creates a local output directory for reports (trend_reports) which is appropriate for its function. Autonomous invocation is allowed by default but not unusual for this type of skill.
Assessment
What to consider before installing: (1) This tool runs arbitrary Python code locally and will read any CSV file path you pass (or many CSVs if you run batch), and it writes reports under 'trend_reports' — only run it on datasets you trust. (2) It has no network calls or credential requests, so it won't exfiltrate data by itself, but because it executes Python code you should inspect the scripts (already provided) or run them in a sandbox/virtualenv. (3) The SKILL requires Python libraries (pandas, numpy, matplotlib, seaborn, ta); installing third-party packages can pull additional dependencies — prefer a virtualenv. (4) This is an analysis aid, not investment advice; outputs include a disclaimer. (5) If you need higher assurance, run the scripts in an isolated VM/container and review the code lines that read/write files (load_data, find_csv_files, output path creation).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.