メニュー
以证据为先的邮箱分类、草稿、发送验证及已发送邮件安全跟进工作流，适用于ECC。当用户希望整理邮件、通过真实邮件界面起草或发送、或证明已发送邮件内容时使用。
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
SOC 職業分類に基づく
| name | email-ops |
| description | 以证据为先的邮箱分类、草稿、发送验证及已发送邮件安全跟进工作流，适用于ECC。当用户希望整理邮件、通过真实邮件界面起草或发送、或证明已发送邮件内容时使用。 |
| origin | ECC |
当实际任务为邮箱工作时使用：分类、起草、回复、发送，或确认邮件已进入已发送文件夹。
这不是通用写作技能，而是围绕实际邮件界面的操作工作流。
在相关场景下调用这些ECC原生技能：
brand-voice 在起草任何面向用户的内容之前investor-outreach 用于面向投资者、合作伙伴或赞助商的邮件customer-billing-ops 当邮件线程属于账单/支持事件而非普通通信时knowledge-ops 当需要将消息或线程捕获到持久上下文中时research-ops 当回复依赖最新外部事实时messages-ops操作前明确：
若回复：
若创建新外发邮件：
brand-voice仅起草任务：
实时发送任务：
使用精确状态词：
若发送界面被阻止，保留草稿并报告确切阻止原因，而非未经说明即改用第二传输方式。
邮件界面
- 账户
- 邮件线程/收件人
- 请求的操作
草稿
- 主题
- 正文
状态
- 已草拟/已发送/已拦截
- 适用时附上发送证明
下一步
- 发送
- 跟进
- 归档/移动
Use after a complex task, failure, or when reviewing what was learned. Teaches how to write growth logs that extract reusable patterns — not diary entries.
Design a goal-oriented agent loop, and review it for the ways loops go wrong — spinning and burning tokens, Goodhart-gaming the verifier, or running a wrong answer to completion. Two actions: (1) WRITE a loop — gate whether to build it, define a machine-decidable goal, pick the loop type, pick a skeleton; (2) REVIEW a loop — run it past five failure modes plus decidability, boundaries, fallback, judge independence, and keep-judgment-with-the-human red lines. Use when designing an autonomous agent loop, or when you already have one and worry it will spin, cheat, or run a wrong answer to the end. Complements the mechanism-layer loop skills (autonomous-loops, continuous-agent-loop) by covering the judgment layer they don't. 中文触发：写 loop、设计 loop、做一个 loop、检查 loop 对不对、loop 体检、loop 会不会跑飞、可判定目标、五个崩法、plan build judge。English triggers: design an agent loop, write a loop, check a loop, loop review, prevent a runaway loop, goal-oriented loop, decidable goal, plan/build/judge.
Stop hook that blocks Claude from finishing until quality checks pass. Detects rationalization patterns (surface text heuristics), stale learning logs (filesystem mtime), and low disk space. Complements self-audit by mechanically enforcing learning capture habits.
React Native and Expo app patterns — Expo Router navigation, state separation (server/client/route/form), TanStack Query data fetching with Zod, performant lists, NativeWind/StyleSheet styling, native APIs, and secure storage. Use when building or editing React Native / Expo screens, components, navigation, or data layers.
Instinct-based learning system that observes sessions via hooks, creates atomic instincts with confidence scoring, and evolves them into skills/commands/agents. v2.1 adds project-scoped instincts to prevent cross-project contamination.
Use this skill when writing new features, fixing bugs, or refactoring code. Enforces test-driven development with 80%+ coverage including unit, integration, and E2E tests.