- Home
- Skills
- Yangliu2060
- Smith Skills
- Email Assistant
email-assistant_skill
- Python
15
GitHub Stars
1
Bundled Files
2 months ago
Catalog Refreshed
4 months ago
First Indexed
Readme & install
Copy the install command, review bundled files from the catalogue, and read any extended description pulled from the listing source.
Installation
Preview and clipboard use veilstrat where the catalogue uses aiagentskills.
npx veilstrat add skill yangliu2060/smith--skills --skill email-assistant- SKILL.md12.2 KB
Overview
This skill is an email assistant that analyzes incoming messages, generates concise one-line summaries, assesses priority and reply needs, and drafts professional response templates. It supports an optional retrieval-augmented knowledge base (RAG) to inject company policies, FAQs, and past replies for higher-quality drafts. The output is designed for quick review and manual sending from your mail client.
How this skill works
The skill parses raw email content or files to extract sender, subject, date, body, attachments, and thread context. It produces a one-sentence summary, classifies type/priority/emotion and decides whether a reply is needed. If a knowledge base exists, it searches for relevant snippets and uses them to produce a 100–200 word draft reply, then runs a quality check and returns score and suggestions.
When to use it
- You need a fast, clear summary of a long or complex email.
- You want an initial professional draft to reply faster (sales, support, internal ops).
- You must triage many emails and prioritize follow-ups.
- You want replies consistent with company policies or standard templates.
- You’re preparing role-specific responses (sales, product, support).
Best practices
- Always review and personalize the generated draft before sending.
- Keep a curated knowledge base: company facts, FAQs, policies, templates.
- Use clear deadlines in replies instead of vague terms like “as soon as possible.”
- Mark sensitive emails for manual handling; do not rely on automatic sending.
- Regularly update templates and historical reply examples in the knowledge base.
Example use cases
- Customer asks for project status — generate summary, mark priority, and draft confirmation with next steps.
- Vendor notifies pricing change — extract action items, recommend reply or approval path, and draft negotiation points.
- Support ticket escalation — summarize issue, classify urgency, and draft troubleshooting or escalation steps.
- Internal meeting logistics — confirm room, AV setup and attendees, and send a concise confirmation email.
- Batch triage: analyze multiple emails to create a prioritized action list and suggested replies.
FAQ
No. It generates analysis and draft text. Users must copy the draft into their email client and send manually.
What document types does the knowledge base support?
Markdown and plain text are supported natively; PDFs and DOCX can be added if external document parsing is available.
How accurate are priority and reply suggestions?
Suggestions are based on content cues and heuristics; always verify critical or sensitive decisions manually.