mailtrap-email-integration
Guides agents through integrating transactional email sending via Mailtrap's Email API, including sandbox testing, domain verification, and API authentication. Use when implementing email-sending features, debugging delivery issues, or setting up safe dev/staging email testing.
DeepseekModel
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质量 优秀 · 90
v1.0.0
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.skill 文件中 system_prompt 字段的实际内容。
name mailtrap-email-integration description Guides agents through integrating transactional email sending via Mailtrap's Email API, including sandbox testing, domain verification, and API authentication. Use when implementing email-sending features, debugging delivery issues, or setting up safe dev/staging email testing. origin ECC Mailtrap Email Integration Patterns for adding transactional email sending to an application using Mailtrap's Email API and Sandbox, covering authentication, environment separation, and common delivery pitfalls. When to Activate Implementing a "send email" feature (signup confirmation, password reset, notifications, receipts) Debugging why emails aren't arriving in dev/staging Setting up a project's first email-sending integration Reviewing code that calls an email API directly without sandbox separation Core Concepts Sandbox vs. Production separation. Mailtrap provides a Sandbox API that captures emails without delivering them, used for dev/staging so test emails never reach real inboxes. Production sending uses a separate, verified-domain endpoint. Never point a dev environment at the production sending endpoint. Authentication. Requests use a Bearer token in the Authorization header. Tokens are scoped per project; sandbox and production typically use different tokens. Domain verification. Production sending requires verifying a sending domain via DNS records (SPF, DKIM, DMARC) before Mailtrap will deliver to real recipients. Skipping this causes silent delivery failures or spam-folder placement. Code Examples // Sending via Mailtrap's Email API (production) async function sendEmail ( to : string , subject : string , html : string ) { const response = await fetch ( "https://send.api.mailtrap.io/api/send" , { method : "POST" , headers : { "Authorization" : `Bearer ${process.env.MAILTRAP_API_TOKEN} ` , "Content-Type" : "application/json" , }, body : JSON . stringify ({ from : { email : "no-reply@yourverifieddomain.com" , name : "Your App" }, to : [{ email : to }], subject, html, }), }); if (!response. ok ) { throw new Error ( `Email send failed: ${response.status} ` ); } return response. json (); } // Same call, routed to Sandbox in non-production environments const MAILTRAP_ENDPOINT = process. env . NODE_ENV === "production" ? "https://send.api.mailtrap.io/api/send" : `https://sandbox.api.mailtrap.io/api/send/ ${process.env.MAILTRAP_INBOX_ID} ` ; Anti-Patterns Anti-Pattern Why It's a Problem Instead Using the production sending endpoint in dev/test Real test emails reach real inboxes, risking spam complaints and leaked test data Route non-production environments to the Sandbox endpoint Hardcoding API tokens in source Credential leak risk if committed to version control Load tokens from environment variables / secrets manager Sending before domain verification completes Emails silently fail or land in spam Verify SPF/DKIM/DMARC records before enabling production sending No retry/error handling on send failures Silent notification failures (e.g., user never gets password reset email) Check response status, log failures, surface actionable errors Best Practices Keep sandbox and production tokens in separate environment variables, never share one token across environments Verify sending domain DNS records before any production launch involving email Log delivery failures with enough context to debug (recipient, template, timestamp, response code) Treat email sending as a fallible network call: wrap in try/catch, never assume success Related Skills api-and-interface-design , security-and-hardening , ci-cd-and-automation
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下载的 .skill 包内含以下字段。
| 字段 | 说明 |
|---|---|
| format | 格式标识(skill/v1) |
| skill_id | 技能唯一 ID |
| name | 技能名称 |
| version | 版本号 |
| description | 技能描述 |
| category | 所属分类(数组) |
| trigger_words | 触发词列表 |
| tags | 标签列表 |
| source | 来源标识 |
| source_url | 来源链接(本页地址) |
| exported_at | 导出时间(每次下载生成) |
| system_prompt | 系统提示词正文 |
| model_config | 模型参数:provider / model / temperature / max_tokens / top_p |
| examples | 示例 |
| install_guide | 各平台导入说明(Coze / Dify / Claude / 自定义框架) |