{
    "format": "skillpro/v1",
    "skill_id": "caffeinelabs-skills-skills-extension-email-skill-md",
    "name": "extension-email",
    "version": "1.0.0",
    "description": "Support for sending service/transactional emails. Don't use this for sending marketing emails or verification emails.",
    "category": [
        "内容创作"
    ],
    "trigger_words": [],
    "tags": [
        "marketing",
        "email",
        "ai"
    ],
    "source": "DeepseekModel",
    "source_url": "https://deepseekmodel.com/skill?id=caffeinelabs-skills-skills-extension-email-skill-md",
    "exported_at": "2026-09-16T16:37:30+08:00",
    "system_prompt": "name extension-email description Support for sending service/transactional emails. Don't use this for sending marketing emails or verification emails. version 0.2.0 compatibility {\"mops\":{\"caffeineai-email\":\"~0.2.0\"}} caffeineai-subscription [\"plus\",\"pro\"] Email — Service/Transactional Service/transactional email extension for Caffeine AI . Overview This skill adds support for sending service and transactional emails from the backend canister. Use sendServiceEmail for order confirmations, notifications, and similar one-off emails. Backend This component is for sending service/transactional emails. There is the prefabricated module mo:caffeineai-email/emailClient.mo which cannot be modified. Use the sendServiceEmail function. Each recipient is sent an individual email It returns a SendResult which is #ok if the email is sent successfully otherwise #err(error) with the error text. module { public type SendResult = { #ok; #err : Text; }; public func sendServiceEmail( fromUsername : Text, recipients : [Text], subject : Text, htmlBody : Text, ) : async SendResult; }; Usage for sendServiceEmail : import Runtime \"mo:core/Runtime\"; import EmailClient \"mo:caffeineai-email/emailClient\"; actor { public func sendOrderConfirmationEmail(recipientEmailAddress : Text, username : Text, orderReference : Text) : async () { let result = await EmailClient.sendServiceEmail( \"no-reply\", [recipientEmailAddress], \"Order \" # orderReference # \" confirmed\", \"Hello \" # username # \",\\nYour order \" # orderReference # \" has been confirmed. Your items will ship tomorrow.\", ); switch (result) { case (#ok) {}; case (#err(error)) { Runtime.trap(\"Failed to send order confirmation email: \" # error); }; }; }; };",
    "model_config": {
        "provider": "deepseek",
        "model": "deepseek-chat",
        "temperature": 0.7,
        "max_tokens": 4096,
        "top_p": 0.9
    },
    "examples": [
        {
            "input": "请用extension-email帮我处理问题",
            "output": "好的，我是extension-email。Support for sending service/transactional emails. Don't use this for sending marketing emails or verification emails. 我会根据你的需求提供专业帮助。"
        },
        {
            "input": "介绍一下你的能力",
            "output": "我是extension-email，专注于内容创作领域。Support for sending service/transactional emails. Don't use this for sending marketing emails or verification emails."
        }
    ],
    "install_guide": {
        "coze": "在 Coze 平台创建 Bot -> 技能配置 -> 导入此 .skill 文件",
        "dify": "在 Dify 平台创建应用 -> 添加知识库 -> 导入此 .skill 配置",
        "claude": "将 system_prompt 字段内容复制到 Claude 自定义指令中",
        "custom": "将此 .skill 文件加载到你的 AI Agent 框架中，解析 system_prompt 和 model_config 即可使用"
    },
    "scripts": {
        "python": "# extension-email - Python extension\n# Add custom Python logic here\ndef process(input_data):\n    return input_data\n",
        "javascript": "// extension-email - JavaScript extension\n// Add custom JS logic here\nfunction process(inputData) {\n    return inputData;\n}\n"
    },
    "tools": {
        "mcp_servers": [],
        "api_endpoints": []
    },
    "dependencies": {
        "python": [],
        "node": []
    },
    "hooks": {
        "on_load": "echo \"Skill loaded: extension-email\"",
        "on_call": "",
        "on_error": "echo \"Skill error: please check logs\""
    }
}