Email-Drafter
Email-Drafter是一款writing方向的AI技能,核心价值是Draft and review professional emails that match your personal writing style,可用于解决开发者在writing领域的实际问题,帮助用户提升效率、自动化重复任务或优化工作流。
Draft and review professional emails that match your personal writing style. Analyzes your sent emails for tone, greeting, structure, and sign-off patterns via WorkIQ, then generates context-aware dra
mkdir -p ./skills/email-drafter && curl -sfL https://raw.githubusercontent.com/github/awesome-copilot/main/skills/email-drafter/SKILL.md -o ./skills/email-drafter/SKILL.md Run in terminal / PowerShell. Requires curl (Unix) or PowerShell 5+ (Windows).
Skill Content
# Email Drafter
Draft professional emails that match your established writing style and tone. Uses WorkIQ to analyze your sent emails and prior correspondence with recipients, then produces context-aware drafts you can review and refine.
When to Use
- "Draft an email to [person] about [topic]"
- "Write a follow-up email to [customer] regarding [project]"
- "Reply to [person]'s email about [subject]"
- "Compose a proposal email for [initiative]"
- "Analyze my email tone with [recipient]"
Workflow
Step 1 — Gather Context
Before drafting, collect:
1. **Recipient(s)** — who is the email for?
2. **Purpose** — what is the email about? (proposal, follow-up, technical guidance, introduction, status update, etc.)
3. **Key points** — what needs to be communicated?
4. **Relationship context** — use WorkIQ to check prior email history with the recipient if available
If the user provides all of these upfront, proceed directly. Otherwise, ask clarifying questions (max 3).
Step 2 — Analyze Tone
When drafting for a recipient, use WorkIQ to understand the user's established communication patterns:
1. Pull 3–5 recent sent emails from the user to the same recipient or similar recipients
2. Identify patterns:
- **Greeting style** — formal ("Dear"), standard ("Hello"), casual ("Hi"), or direct (no greeting)
- **Structure** — short paragraphs vs. bullet lists vs. numbered steps
- **Sign-off** — what closing and name format the user typically uses
- **Formality level** — professional, friendly-professional, casual
- **Language** — which language the user writes in with this recipient
3. Apply those patterns to the draft
If WorkIQ is unavailable or no prior emails exist, use sensible professional defaults and note that the tone was inferred.
Step 3 — Draft the Email
Apply the discovered (or default) style rules:
**Greeting:**
- Match whatever greeting style was found in Step 2
- Default: "Hello [FirstName]," for external, "Hi [FirstName]," for internal
- For multiple recipients: "Hello [Name1], [Name2],"
**Tone:**
- Direct and concise — no filler language
- Friendly but professional
- Get to the point quickly
- Offer help proactively where appropriate ("Happy to discuss further", "Let me know if you need anything")
**Structure:**
- Short emails (1–2 points): simple paragraphs, no bullets needed
- Longer emails (proposals, multi-point updates): use bullet points or numbered lists
- Include context from prior conversations when relevant ("Following our recent conversation about...")
**Sign-off:**
- Match the user's established sign-off pattern from Step 2
- Default: "Best regards," followed by the user's first name on the next line
**Language:**
- Default to English unless the user specifies otherwise
- Match the recipient's language if prior correspondence was in another language
Step 4 — Output
1. Present the draft for review with a brief note on the tone/style applied
2. Apply edits as the user requests — iterate until satisfied
3. Save the final draft to `outputs/<year>/<month>/` with a descriptive filename (e.g., `2026-03-26-email-acme-followup.md`)
Important Rules
- **Never send emails** — only draft them as files for the user to review and send manually
- Always check WorkIQ for prior context with the recipient when available
- If the user says "draft email" or "write email", activate this skill automatically
- Save drafts using the `outputs/<year>/<month>/` folder convention
- Respect privacy: do not include sensitive information from unrelated email threads
Example Prompts
- "Draft an email to Sarah about the project timeline"
- "Write a follow-up to the customer about their migration questions"
- "Compose a proposal email for the new training initiative"
- "Reply to John's email — agree with his approach but suggest we add monitoring"
- "Analyze my email tone with the Acme team"
Requirements
- **WorkIQ MCP tool** is recommended for tone analysis and recipient context (Mi
🎯 Best For
- Engineering teams doing code reviews
- Open source maintainers
- Developers scaffolding new projects
- Prototype builders
- Data analysts
💡 Use Cases
- Reviewing pull requests for security vulnerabilities
- Checking code style consistency
- Bootstrapping React components
- Creating API route handlers
📖 How to Use This Skill
- 1
Install the Skill
Copy the install command from the Terminal tab and run it. The SKILL.md file downloads to your local skills directory.
- 2
Load into Your AI Assistant
Open Claude or GitHub Copilot and reference the skill. Paste the SKILL.md content or use the system prompt tab.
- 3
Apply Email-Drafter to Your Work
Provide context for your task — paste source material, describe your audience, or share existing work to guide the AI.
- 4
Review and Refine
Edit the AI output for accuracy, tone, and completeness. Add human insight where the AI lacks context.
❓ Frequently Asked Questions
Does this skill check for OWASP Top 10?
Security-focused review skills often include OWASP checks. Check the skill content for specific vulnerability categories covered.
Can I customize the generated output?
Yes — modify the skill's prompt instructions to match your project conventions and coding style.
Can this connect to my database directly?
Most data skills accept CSV or JSON input. Database connectors are listed in the Works With section.
Can Email-Drafter maintain my brand voice?
Yes — provide style guides or example content in your prompt for consistent brand-aligned output.
How do I install Email-Drafter?
Copy the install command from the Terminal tab and run it. The skill downloads to ./skills/email-drafter/SKILL.md, ready to use.
⚠️ Common Mistakes to Avoid
Blindly accepting AI suggestions
Always verify AI-generated review comments. Some suggestions may not apply to your specific codebase conventions.
Using generated code without understanding
Understand what generated code does before shipping it to production.
Not validating data quality
AI analysis is only as good as your input data. Profile and clean data before analysis.
Publishing unedited drafts
AI writing needs human editing for facts, flow, and authentic voice.