Mental Models Cn V2.1.0 Backup

💡 3秒匹配最佳思维模型 | 108个模型覆盖商业分析、投资决策、心理学、系统思考 | 告别拍脑袋决策

What to consider before installing: - The package is primarily documentation and does not request secrets, which is good. - Red flag 1: SKILL.md contains hidden unicode control characters (prompt‑injection signal). Open the file in a hex/visible-control-character viewer and remove/verify any control characters before use. Do not trust the file if you cannot explain them. - Red flag 2: The docs refer to scripts (e.g., scripts/recommend.py) and to git clone steps that are not present in the provided manifest. Do not run any python scripts or clone/execute code from the upstream repo without first reviewing that code. - If you want to use the recommendation script: get the exact script file, inspect it for network calls, eval/exec usage, shell execution, or credentials exfiltration, and run it only in an isolated sandbox. - Prefer to use the skill as read-only (open the markdown files) rather than executing scripts until you verify the external code. - Check the GitHub homepage/maintainer: verify repo commits, contributors, and recent changes. Ask the maintainer to provide the missing scripts within the skill package or to explain why external cloning is required. - If you are not comfortable auditing code or if hidden characters remain unexplained, avoid installing/running the automated parts and use only the static markdown content.

Type: OpenClaw Skill Name: mental-models-cn-v2-1-0-backup Version: 2.6.2 The 'mental-models-cn' skill bundle is a comprehensive library of 108 mental models (e.g., PESTEL, SWOT, Game Theory, and Antifragility) designed to help an AI agent perform structured business and psychological analysis. The documentation, including SKILL.md, README.md, and TEMPLATES.md, provides educational content, case studies, and analytical frameworks consistent with its stated purpose. While the documentation mentions a Python script (scripts/recommend.py) for model recommendations, no executable code was provided for review, and all analyzed markdown files show no signs of malicious intent, data exfiltration, or prompt injection.