Log Analyzer Dashboard
v1.0.2纯本地日志分析系统，支持日志统计、重复检测、错误分析和异常识别
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byGodYoung@godyounger
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 (local log analysis) match the provided files and runtime requirements: a Streamlit Python app (log-analyzer.py) and a shell launcher. Required binary 'streamlit' and listed Python libs (pandas, plotly) are appropriate for the described functionality.
Instruction Scope
SKILL.md instructs running the Streamlit app from the skill workspace and describes selecting a local log directory. That matches the purpose. Note: the app is designed to read arbitrary local log directories (e.g., /var/log); this is expected but means the skill will access any files the user points it at, so users should avoid pointing it at sensitive directories unless they intend that. SKILL.md also states 'no external connection' — the code itself contains no outbound network calls, but Streamlit and installed libraries may include telemetry or could be configured to serve on a network interface; consider network exposure when running.
Install Mechanism
There is no high-risk remote download. Dependencies are normal Python packages (streamlit, pandas, plotly) listed in the SKILL.md 'install' section. Installation via pip is expected for this kind of skill and proportional to its function.
Credentials
The skill declares no required environment variables, no credentials, and no config paths. The files and instructions do not attempt to read environment secrets. That matches the local log-analysis purpose.
Persistence & Privilege
always is false, and the skill does not request special platform privileges or modify other skills. It runs as a local Streamlit app in the skill workspace, which is a normal level of persistence for a UI tool.
Assessment
This skill appears to be a straightforward local Streamlit log-analyzer. Before installing/running: 1) Inspect the included Python file yourself (it's present and readable) to confirm behavior; 2) Be mindful of which directories you point the tool at — it will read any files you allow (including system logs); 3) Install Python packages from a trusted environment (pip installs are required); 4) Run the Streamlit server on localhost only (or bind appropriately) to avoid exposing logs on the network; 5) If you need to analyze logs containing secrets or PII, run the tool on an isolated host or with restricted file permissions. If you want extra assurance, run it in a sandbox/container and review the code for any telemetry or network configuration before use.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.
Runtime requirements
📊 Clawdis
Binsstreamlit