Email Check logo

Email Check

Community
AgriciDaniel
email-check

Intelligent inbox triage that connects to Gmail or Outlook, scores emails by importance (0-100) using sender recognition, urgency keywords, thread depth, time sensitivity, and business relevance, categorizes into Urgent/Important/Routine/Archive, and generates reply suggestions for top priority items. Use when the user wants to check email, review inbox, triage messages, see what's urgent, or get reply suggestions. Triggers on check email, inbox triage, what's important, email summary, unread emails, priority inbox.

Overview

PublisherAgriciDaniel
Repositoryclaude-email
Skill nameemail-check
Stars
132
Forks
32
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by AgriciDaniel on GitHub. Read the source before you install it.

Installation

Install the Email Check AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/AgriciDaniel/claude-email/tree/main/skills/email-check
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/AgriciDaniel/claude-email.git /tmp/claude-email
mkdir -p .claude/skills
cp -r /tmp/claude-email/skills/email-check .claude/skills/email-check
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Email Check in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Email Check on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Email Check is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Email Check Sub-Skill

Purpose

This sub-skill handles intelligent inbox triage by connecting to Gmail or Outlook via MCP, analyzing unread emails, scoring them by importance, categorizing them, and generating reply suggestions for high-priority items.

Workflow

1. Detect Available Email Provider

Check which MCP tools are available:

  • Gmail: search_gmail_messages, get_gmail_messages_content_batch, get_gmail_thread_content, list_gmail_labels
  • Outlook: list-mail-messages, list-mail-folder-messages, get-mail-message

Prefer Gmail if both are available (better batch operations).

2. Fetch Unread Emails

For Gmail:

search_gmail_messages(query="is:unread", max_results=50)

For Outlook:

list-mail-messages (defaults to recent messages, filter for unread)

3. Batch Fetch Email Content

For Gmail:

get_gmail_messages_content_batch(message_ids=[...])  # Up to 25 at a time

If more than 25 unread, prioritize most recent first.

For Outlook:

get-mail-message for each message (sequential)

Limit to 25 emails maximum to avoid overwhelming analysis.

4. Score Each Email (0-100)

Apply the following scoring algorithm:

Base Score: 50
Sender Recognition (+20 to -20)
  • +20: VIP/known contact (domain matches user's company, appears in sent folder frequently)
  • +10: Recognized sender (has prior thread history)
  • 0: Unknown sender with legitimate domain
  • -15: Newsletter/automated sender (bulk email headers, unsubscribe links)
  • -20: Notification sender (no-reply@, noreply@, automated@)
Direct Address (+15 to -10)
  • +15: Primary recipient (To: field)
  • 0: CC'd (CC: field)
  • -10: BCC'd or mass email (many recipients)
Thread Depth (+10)
  • +10: Reply in active thread (Re: subject, multiple messages in thread)
  • 0: New email (no thread history)
Urgency Keywords (+15)

Check subject and first 200 characters for:

  • urgent, ASAP, deadline, action required, immediate, time-sensitive, expiring, expires, due
  • +15 if any urgency keyword found
Calendar/Meeting (+20)
  • +20: Calendar invite, meeting request, event notification
  • Detect via attachments (ics file) or subject patterns (Invitation:, Meeting:)
Deadline Detection (+25)

Parse email body for dates/deadlines:

  • +25: Deadline within 48 hours
  • +10: Deadline within 7 days
  • 0: No deadline or deadline > 7 days
Business Relevance (+15 to -10)

If email-profile.md exists in parent directory:

  • +15: Mentions user's key topics, clients, projects
  • +5: Industry-relevant keywords
  • -10: Off-topic or personal (if business inbox)
Final Score Calculation

Sum all adjustments to base score of 50. Clamp to 0-100 range.

5. Categorize Emails

Based on final score:

Score RangeCategoryAction
85-100UrgentImmediate attention, generate reply suggestions
65-84ImportantReview soon, may need action
40-64RoutineNormal priority, review when available
20-39Low PrioritySkim or defer
0-19ArchiveLikely noise or automated

6. Generate Reply Suggestions

For emails scored 85+ (Urgent category):

  1. Read full thread context using get_gmail_thread_content or equivalent
  2. Check for email-profile.md in parent directory for user's:
    • Brand voice (professional, casual, direct, warm)
    • Common sign-off
    • Industry/role context
  3. Draft two reply options:
    • Brief: 1-2 sentences, direct answer
    • Detailed: 1 paragraph with context

Do NOT draft replies if:

  • Email requires research beyond available context
  • Email needs user decision (approve/decline, choose option)
  • Email is FYI/informational only
  • Email is calendar invite (suggest accept/decline/tentative instead)

In these cases, output: "This email requires your personal attention: [reason]"

7. Output Format

markdown
## Inbox Summary

**X unread emails** | Y Urgent | Z Important | W Routine | V Low Priority

### Urgent (Action Required)

| # | From | Subject | Score | Suggested Action |
|---|------|---------|-------|------------------|
| 1 | sender@domain.com | Subject line | 95 | [Reply/Review/Respond] |
| 2 | ... | ... | 88 | ... |

---

### Important

| # | From | Subject | Score | Category |
|---|------|---------|-------|----------|
| 3 | ... | ... | 78 | Meeting follow-up |
| 4 | ... | ... | 70 | Client inquiry |

---

### Routine & Low Priority

- **Routine (40-64)**: X emails - [grouped summary by sender/topic]
- **Low Priority (20-39)**: Y emails - newsletters, notifications
- **Archive (<20)**: Z emails - automated/noise

---

### Suggested Replies

#### 1. Re: [Subject] (to: sender@domain.com)

**Context:** [Why this email scored high, key points]

**Brief Option:**
> [1-2 sentence reply]
>
> [Sign-off]

**Detailed Option:**
> [Paragraph with more context/explanation]
>
> [Sign-off]

#### 2. Re: [Next urgent email]

[Repeat format]

---

### Emails Requiring Personal Attention

- **#X - [Subject]**: Needs decision on [topic]
- **#Y - [Subject]**: Requires research before responding

Scoring Signal Reference

SignalScore ImpactDetection
Direct To: address+15Check To: field
VIP/known sender+20Domain match, sent folder history
Active thread+10Thread ID, Re: in subject
Urgency keywords+15Subject/body scan
Calendar invite+20.ics attachment, invite headers
Deadline <48h+25Date parsing in body
Deadline <7d+10Date parsing in body
Business relevance+15Match email-profile.md topics
CC'd (not primary)-10CC: field
Newsletter-20Unsubscribe link, bulk headers
Notification-15no-reply@ sender
Unknown sender-10No thread history

Reply Suggestion Guidelines

Tone Adaptation

If email-profile.md exists, adapt replies to match:

  • Professional: Formal, structured, clear
  • Casual: Friendly, conversational
  • Direct: Brief, action-oriented
  • Warm: Personable, relationship-focused

Default to professional-friendly if no profile exists.

Reply Structure

Brief Option:

  • Answer the core question/request
  • 1-2 sentences maximum
  • Clear next step if needed

Detailed Option:

  • Address all points raised
  • Provide context or explanation
  • 1 paragraph (3-5 sentences)
  • Suggest next steps or timeline

When NOT to Draft

  • Email asks for approval/decision → Suggest: "Review and approve/decline X"
  • Email requires data you don't have → "This email requires your personal attention: needs [data/info]"
  • Email is complex multi-part → "This email requires your personal attention: multiple decisions needed"
  • Email is FYI only → Suggested Action: "Review (no response needed)"

Error Handling

No MCP Connection

If neither Gmail nor Outlook MCP is available:

Error: No email provider connected. Please ensure Gmail MCP or Outlook MCP is configured.

Empty Inbox

## Inbox Summary
**0 unread emails** - Your inbox is clear!

MCP Rate Limits

If batch fetch fails, fall back to individual message retrieval (slower but reliable).

Thread Context Unavailable

If get_gmail_thread_content fails, draft replies based on single message only (note: "Limited context - single message view").

Integration Points

email-profile.md (optional)

If exists in parent directory (../email-profile.md), use for:

  • Brand voice detection
  • Business relevance scoring
  • Reply tone/style matching
  • Common topics/clients list

Gmail-Specific Features

  • Use labels to refine categorization (e.g., skip "Promotions" labeled emails)
  • Check sent folder for sender recognition

Outlook-Specific Features

  • Use folder structure for context (Inbox vs Focused)
  • Leverage categories if available

Performance Optimization

  • Batch fetch 25 emails at a time (Gmail)
  • Limit analysis to 50 most recent unread
  • Cache sender recognition data during session
  • Prioritize most recent emails if >50 unread

Output Constraints

  • Keep total output under 2000 lines
  • Group routine/low priority emails by topic/sender
  • Only show full details for Urgent and Important categories
  • Collapse archived emails into summary count

Quality Gates

Before outputting digest:

  1. Verify all urgency scores are justified with signal breakdown
  2. Ensure reply suggestions are actionable (not generic)
  3. Check that "personal attention" notes explain why
  4. Confirm categories align with score ranges
  5. Validate that batch operations completed successfully

Success Criteria

A successful email check session should:

  • Identify all truly urgent emails (no false negatives)
  • Minimize false positives in Urgent category (precision > 80%)
  • Provide actionable reply drafts for top 3-5 emails
  • Complete analysis in <30 seconds for 25 emails
  • Output clear next actions for each category

Frequently asked questions

What does the Email Check AI skill do?

Intelligent inbox triage that connects to Gmail or Outlook, scores emails by importance (0-100) using sender recognition, urgency keywords, thread depth, time sensitivity, and business relevance, categorizes into Urgent/Important/Routine/Archive, and generates reply suggestions for top priority items. Use when the user wants to check email, review inbox, triage messages, see what's urgent, or get reply suggestions. Triggers on check email, inbox triage, what's important, email summary, unread emails, priority inbox.

Why use Email Check on TypingMind?

Because you install it once and use it with any model. Email Check is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Email Check in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/AgriciDaniel/claude-email/tree/main/skills/email-check. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Email Check?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Email Check?

As many as you like. As long as a model supports skills, you can use Email Check with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Email Check AI skill free?

Yes. It is published on GitHub by AgriciDaniel under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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