Weekly Report (OpenClaw)

自动化工作周报生成系统。支持自动登录周报系统、获取团队周报数据、使用 AI 进行内容提炼总结、生成格式化的 Word 文档。 触发场景：(1) 用户要求生成周报 (2) 用户询问本周/上周工作总结 (3) 用户提到"周报"、"weekly report"、"工作总结" (4) 用户需要汇总团队成员工作内容

This skill largely does what it says, but take precautions before installing or running it: - Inspect scripts/setup.sh before running; it uses remote installers (curl|sh / PowerShell) which can execute arbitrary code. Prefer manual, vetted installation of dependencies. - Verify and, if needed, change the configured base_url and API IDs: defaults point to a specific IP (http://120.210.237.117:7006) and app/worksheet/view IDs — supplying your corporate credentials without confirming the endpoint could leak access to that host. - Be aware the login routine intercepts network requests and saves the authorization header and cookies to .token_cache. Run the tool in an isolated environment (VM or container) if you must provide real credentials, and delete cache files after use. - If you don't trust the hard-coded defaults, pass an explicit config file (--config) that points to your own instance or remove the default values. - Consider creating a limited-permission service account for the report system and a dedicated LLM API key rather than using a full-privilege personal credential. If you want, I can: (1) summarize exactly what setup.sh does, (2) list the external domains the scripts download from, or (3) produce a checklist of safe install steps (run in VM, inspect files, run in offline mode) to reduce risk.

Type: OpenClaw Skill Name: weekly-report-openclaw Version: 1.0.0 The skill bundle is a well-structured automation tool designed to generate weekly reports by fetching data from a specific internal system (hosted at 120.210.237.117), summarizing it via LLM (DeepSeek/OpenAI), and producing Word documents. It utilizes Playwright in `lib/login.py` and `lib/fetcher.py` for browser-based authentication and data extraction, which is consistent with its stated purpose of automating interactions with a report system. No evidence of malicious intent, unauthorized data exfiltration, or prompt injection was found; the code follows modern Python practices and uses standard dependencies.