System Data Intelligence — File · Analysis · Visualization

专为文件操作、数据分析、可视化、数据库连接、API 接入和敏感数据处理设计的系统级 Agent Skill。 【强制触发场景】： - 用户提及任何文件操作：Excel / WPS / Word / TXT / Markdown / RTZ / CSV / JSON - 「分析」「读取」「提取」「处理」「建模」「预...

This package appears coherent for file parsing, DB queries, API ingestion, analysis and visualization — the included scripts implement what the SKILL.md promises. However: - SKILL.md / AGENTS.md mandate automatic activation for many common triggers and say 'do not ask user' — that means an agent using this skill could read local files, open Office via COM/AppleScript, connect to DBs/APIs, and write outputs without asking explicit consent each time. Consider whether you want that behavior. - The skill will accept raw DB URLs and API tokens and can send/receive network data. Only provide credentials to this skill if you trust it and the execution environment. Prefer short-lived credentials or read-only accounts for testing. - Inspect and, if possible, run the code in a sandbox/container first (the repo includes docker-compose). Verify that temporary files are actually deleted and that logs don't leak secrets. Run the tests and review scripts/security_utils.py to confirm masking behavior meets your requirements. - On macOS/Windows the readers require granting automation/accessibility permissions; consider the impact before enabling them. - If you want safer operation: require user confirmation before any network/DB call or file access, run the skill with least privilege (container, network restrictions), and do not give production credentials until you are satisfied with its behavior. Given the forced/automatic activation policy and the broad I/O/network capabilities, treat this skill with caution rather than installing it into a fully-trusted, always-connected agent without additional controls.

Type: OpenClaw Skill Name: system-data-intelligence Version: 1.0.3 The bundle is a comprehensive data intelligence toolkit designed for file parsing, database connectivity, API integration, and advanced visualization. While it utilizes high-privilege capabilities such as COM automation (win32com in win_excel_reader.py), AppleScript (osascript in mac_excel_reader.py), and external network requests (api_loader.py), these are strictly aligned with the stated purpose of cross-platform data processing. The inclusion of proactive security utilities for PII masking and secure temporary file cleanup (security_utils.py), along with credential masking in database logs (db_connector.py), demonstrates a focus on safety rather than malice. No evidence of data exfiltration, unauthorized persistence, or malicious prompt injection was found.