lesson生成今日菜单推荐。根据用户手头的食材、口味偏好、人数和烹饪时间， 从内置食材库和菜谱库中智能匹配，输出完整的菜单方案和分步烹饪指南。 当用户提到"今天吃什么""做什么菜""菜单""菜谱推荐""晚饭吃啥"等意图时触发。
Install via ClawdBot CLI:
clawdbot install yequanzheng/lessonGrade Fair — based on market validation, documentation quality, package completeness, maintenance status, and authenticity signals.
Generated Apr 9, 2026
Helps individuals or families plan daily meals based on available ingredients and preferences, reducing food waste and decision fatigue. It provides step-by-step cooking instructions tailored to time constraints and dietary needs.
Supports users on specific diets, such as weight loss or low-sodium plans, by generating menus with calorie estimates and healthy cooking methods. It ensures balanced nutrition while accommodating allergies or restrictions.
Acts as a virtual cooking tutor by offering detailed recipes and tips for beginners or enthusiasts. It guides users through techniques like timing and heat control, helping them improve their culinary skills over time.
Assists small restaurants or catering services in creating daily specials or personalized menus for clients based on inventory and customer preferences. It optimizes ingredient usage and streamlines kitchen workflows.
Offers basic menu generation for free, with premium features like advanced recipe libraries, nutritional analytics, and integration with grocery delivery services. Revenue comes from monthly or annual subscriptions.
Generates income by recommending specific ingredients, cookware, or grocery delivery services within the menu outputs. Partnerships with food brands or retailers drive commissions on sales.
Licenses the skill to other platforms, such as smart kitchen appliances, meal kit services, or health apps. This model provides a steady revenue stream through licensing fees or API usage charges.
💬 Integration Tip
Integrate with smart home devices or grocery apps to automate ingredient tracking and shopping lists, enhancing user convenience.
Scored Apr 28, 2026
对用户提供的任何学术论文（PDF附件或URL）进行双模式深度研读。当用户请求分析、研读、解读或总结一篇学术论文时，使用此技能。一次性生成两份报告：Part A 面向研究者的深度专业解析，Part B 面向快速理解的核心逻辑与价值提炼。
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Evidence-based endurance coaching protocol (v11.35). Use when analyzing training data, reviewing sessions, generating pre/post-workout reports, planning work...
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Adds equilibrium-constrained reasoning to OpenClaw, ensuring all operations maintain balance for coherent, self-validating, and consistent AI responses.