gmail-automation▌
sickn33/antigravity-awesome-skills · updated Apr 8, 2026
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Lightweight Gmail integration with standalone OAuth authentication. No MCP server required.
Gmail
Lightweight Gmail integration with standalone OAuth authentication. No MCP server required.
⚠️ Requires Google Workspace account. Personal Gmail accounts are not supported.
When to Use
- You need to search, read, or send Gmail messages from the command line without an MCP server.
- You are automating inbox workflows for a Google Workspace account.
- You want a lightweight Gmail integration backed by standalone OAuth scripts.
First-Time Setup
Authenticate with Google (opens browser):
python scripts/auth.py login
Check authentication status:
python scripts/auth.py status
Logout when needed:
python scripts/auth.py logout
Commands
All operations via scripts/gmail.py. Auto-authenticates on first use if not logged in.
Search Emails
# Search with Gmail query syntax
python scripts/gmail.py search "from:[email protected] is:unread"
# Search recent emails (no query returns all)
python scripts/gmail.py search --limit 20
# Filter by label
python scripts/gmail.py search --label INBOX --limit 10
# Include spam and trash
python scripts/gmail.py search "subject:important" --include-spam-trash
Read Email Content
# Get full message content
python scripts/gmail.py get MESSAGE_ID
# Get just metadata (headers)
python scripts/gmail.py get MESSAGE_ID --format metadata
# Get minimal response (IDs only)
python scripts/gmail.py get MESSAGE_ID --format minimal
Send Emails
# Send a simple email
python scripts/gmail.py send --to "[email protected]" --subject "Hello" --body "Message body"
# Send with CC and BCC
python scripts/gmail.py send --to "[email protected]" --cc "[email protected]" --bcc "[email protected]" \
--subject "Team Update" --body "Update message"
# Send from an alias (must be configured in Gmail settings)
python scripts/gmail.py send --to "[email protected]" --subject "Hello" --body "Message" \
--from "Mile9 Accounts <[email protected]>"
# Send HTML email
python scripts/gmail.py send --to "[email protected]" --subject "HTML Email" \
--body "<h1>Hello</h1><p>HTML content</p>" --html
Draft Management
# Create a draft
python scripts/gmail.py create-draft --to "[email protected]" --subject "Draft Subject" \
--body "Draft content"
# Send an existing draft
python scripts/gmail.py send-draft DRAFT_ID
Modify Messages (Labels)
# Mark as read (remove UNREAD label)
python scripts/gmail.py modify MESSAGE_ID --remove-label UNREAD
# Mark as unread
python scripts/gmail.py modify MESSAGE_ID --add-label UNREAD
# Archive (remove from INBOX)
python scripts/gmail.py modify MESSAGE_ID --remove-label INBOX
# Star a message
python scripts/gmail.py modify MESSAGE_ID --add-label STARRED
# Unstar a message
python scripts/gmail.py modify MESSAGE_ID --remove-label STARRED
# Mark as important
python scripts/gmail.py modify MESSAGE_ID --add-label IMPORTANT
# Multiple label changes at once
python scripts/gmail.py modify MESSAGE_ID --remove-label UNREAD --add-label STARRED
List Labels
# List all Gmail labels (system and user-created)
python scripts/gmail.py list-labels
Gmail Query Syntax
Gmail supports powerful search operators:
| Query | Description |
|---|---|
from:[email protected] |
Emails from a specific sender |
to:[email protected] |
Emails to a specific recipient |
subject:meeting |
Emails with "meeting" in subject |
is:unread |
Unread emails |
is:starred |
Starred emails |
is:important |
Important emails |
has:attachment |
Emails with attachments |
after:2024/01/01 |
Emails after a date |
before:2024/12/31 |
Emails before a date |
newer_than:7d |
Emails from last 7 days |
older_than:1m |
Emails older than 1 month |
label:work |
Emails with a specific label |
in:inbox |
Emails in inbox |
in:sent |
Sent emails |
in:trash |
Trashed emails |
Combine with AND (space), OR, or - (NOT):
python scripts/gmail.py search "from:[email protected] is:unread newer_than:1d"
python scripts/gmail.py search "subject:urgent OR subject:important"
python scripts/gmail.py search "from:[email protected] -is:starred"
Common Label IDs
| Label | ID |
|---|---|
| Inbox | INBOX |
| Sent | SENT |
| Drafts | DRAFT |
| Spam | SPAM |
| Trash | TRASH |
| Starred | STARRED |
| Important | IMPORTANT |
| Unread | UNREAD |
Token Management
Tokens stored securely using the system keyring:
- macOS: Keychain
- Windows: Windows Credential Locker
- Linux: Secret Service API (GNOME Keyring, KDE Wallet, etc.)
Service name: gmail-skill-oauth
Tokens automatically refresh when expired using Google's cloud function.
How to use gmail-automation on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add gmail-automation
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches gmail-automation from GitHub repository sickn33/antigravity-awesome-skills and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate gmail-automation. Access the skill through slash commands (e.g., /gmail-automation) or your agent's skill management interface.
Security & Verification Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
List & Monetize Your Skill
Submit your Claude Code skill and start earning
Use Cases▌
Task Automation & Efficiency
Automate repetitive workflows and reduce manual effort
Example
Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
Knowledge Enhancement
Learn new skills, understand complex topics, get expert guidance
Example
Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Quality Improvement
Enhance output quality through reviews, suggestions, and refinements
Example
Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client with skill support
- ›Clear understanding of task or problem to solve
- ›Willingness to iterate and refine outputs
Time Estimate
15-45 minutes depending on use case complexity
Installation Steps
- 1.Install skill using provided installation command
- 2.Test with simple use case relevant to your work
- 3.Evaluate output quality and relevance
- 4.Iterate on prompts to improve results
- 5.Integrate into regular workflow if valuable
Common Pitfalls
- ⚠Expecting perfect results without iteration
- ⚠Not providing enough context in prompts
- ⚠Using skill for tasks outside its intended scope
- ⚠Accepting outputs without review and validation
Best Practices▌
✓ Do
- +Start with clear, specific prompts
- +Provide relevant context and constraints
- +Review and refine all outputs before using
- +Iterate to improve output quality
- +Document successful prompt patterns
✗ Don't
- −Don't use without understanding skill limitations
- −Don't skip validation of outputs
- −Don't share sensitive information in prompts
- −Don't expect skill to replace human judgment
💡 Pro Tips
- ★Be specific about desired format and style
- ★Ask for multiple options to choose from
- ★Request explanations to understand reasoning
- ★Combine AI efficiency with human expertise
When to Use This▌
✓ Use When
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid When
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
Learning Path▌
- 1Familiarize yourself with skill capabilities and limitations
- 2Start with low-risk, non-critical tasks
- 3Progress to more complex and valuable use cases
- 4Build expertise through regular use and experimentation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.5★★★★★69 reviews- ★★★★★Luis Jain· Dec 28, 2024
Solid pick for teams standardizing on skills: gmail-automation is focused, and the summary matches what you get after install.
- ★★★★★Luis Kapoor· Dec 12, 2024
gmail-automation fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Luis Gupta· Dec 12, 2024
gmail-automation reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Shikha Mishra· Dec 8, 2024
gmail-automation reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Sophia Sethi· Dec 8, 2024
We added gmail-automation from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Kaira Sanchez· Nov 27, 2024
Solid pick for teams standardizing on skills: gmail-automation is focused, and the summary matches what you get after install.
- ★★★★★Li Haddad· Nov 23, 2024
Registry listing for gmail-automation matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Li Khan· Nov 19, 2024
We added gmail-automation from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★William Thomas· Nov 19, 2024
gmail-automation reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Daniel Johnson· Nov 3, 2024
gmail-automation has been reliable in day-to-day use. Documentation quality is above average for community skills.
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