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gmail-integrationGmail 集成

Agent Skill

gmail-integration 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

832

周安装

34

GitHub Stars

93

下载量

269
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

3

许可证

MIT

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:gmail-integration(Gmail 集成)
来源仓库:https://github.com/letta-ai/skills
仓库路径:skills/gmail-integration
安装命令:
npx skills add https://github.com/letta-ai/skills --skill gmail-integration
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/letta-ai/skills --skill gmail-integration

简介

gmail-integration 用于查找、检索和筛选相关信息,支持关键词匹配。

  • 适用于 Codex、Claude、Cursor、Gemini CLI 中的信息定位需求。
  • 结合来源仓库和原始 README 可进一步核验具体用法。
  • 安装命令:npx skills add https://github.com/letta-ai/skills --skill gmail-integration。
  • 建议确认权限范围和维护状态,避免触发联网或文件操作。

SKILL.md

Gmail Integration

This skill enables Gmail integration via the Google Gmail API with OAuth 2.0 authentication. It provides scripts for searching emails, reading content, creating drafts, finding emails needing replies, and archiving messages.

Prerequisites

Before using this skill, ensure:

  1. Python 3.10+ is available
  2. A Google Cloud project with Gmail API enabled
  3. OAuth 2.0 credentials (credentials.json) downloaded
  4. Required packages installed: google-api-python-client, google-auth-httplib2, google-auth-oauthlib

OAuth Setup Walkthrough

If the user hasn't set up Gmail API access yet, guide them through these steps:

Step 1: Create Google Cloud Project

  1. Go to https://console.cloud.google.com/
  2. Create a new project or select existing one
  3. Navigate to APIs & ServicesLibrary
  4. Search for "Gmail API" and click Enable

Step 2: Configure OAuth Consent Screen

  1. Go to APIs & ServicesOAuth consent screen
  2. Select External user type
  3. Fill in app name and support email
  4. Add scopes:

- https://www.googleapis.com/auth/gmail.readonly - https://www.googleapis.com/auth/gmail.compose - https://www.googleapis.com/auth/gmail.modify (for archiving/labeling)

  1. Add user's email as a test user
  2. Save and continue

Step 3: Create OAuth Credentials

  1. Go to APIs & ServicesCredentials
  2. Click Create CredentialsOAuth client ID
  3. Select Desktop app as application type
  4. Download JSON and rename to credentials.json
  5. Place in project directory

Step 4: Install Dependencies

uv add google-api-python-client google-auth-httplib2 google-auth-oauthlib
# or
pip install google-api-python-client google-auth-httplib2 google-auth-oauthlib

Step 5: First Authentication

Run any script (e.g., search_emails.py) - it will open a browser for OAuth consent. After authorization, a token.json is saved for future use.

Email Operations

All scripts are in the scripts/ directory. They share authentication logic and expect credentials.json in the same directory (or path specified via --credentials).

Search Emails

python scripts/search_emails.py "from:someone@example.com" --max-results 10
python scripts/search_emails.py "subject:meeting after:2024/01/01"
python scripts/search_emails.py "is:unread"
python scripts/search_emails.py "in:inbox" --json  # Output as JSON

Read Email

python scripts/read_email.py <message_id>
python scripts/read_email.py <message_id> --format full  # includes attachments info

Create Draft

# New email
python scripts/create_draft.py --to "recipient@example.com" --subject "Hello" --body "Message content"
python scripts/create_draft.py --to "a@example.com" --cc "b@example.com" --subject "Update" --body-file message.txt

# HTML email with links
python scripts/create_draft.py --to "recipient@example.com" --subject "Hello" --body "<a href='https://example.com'>link</a>" --html

# IMPORTANT: Reply in same thread (required for proper threading!)
python scripts/create_draft.py --to "person@email.com" --subject "Re: Original Subject" \
  --reply-to "<message-id-header@mail.gmail.com>" \
  --thread-id "thread_id_here" \
  --body "Your reply"

⚠️ Threading replies: To reply in the same email thread (not create a new conversation), you MUST include:

  • --reply-to: The Message-ID header from the email you're replying to
  • --thread-id: The Gmail thread ID

To get these values, read the email with read_email.py and check the message metadata, or use this Python snippet:

msg_data = service.users().messages().get(userId="me", id=msg_id, format="metadata", metadataHeaders=["Message-ID"]).execute()
thread_id = msg_data.get("threadId")
message_id_header = next(h["value"] for h in msg_data["payload"]["headers"] if h["name"] == "Message-ID")

Find Emails Needing Reply

Identifies emails where you haven't replied, or your only reply is an unsent draft:

python scripts/needs_reply.py                          # Check inbox for emails needing reply
python scripts/needs_reply.py --max-results 30         # Check more emails
python scripts/needs_reply.py --query "is:important"   # Filter to important emails
python scripts/needs_reply.py --json                   # Output as JSON
python scripts/needs_reply.py --include-automated      # Include newsletters/notifications

Important: By default, needs_reply.py automatically filters out automated/notification emails:

  • Emails from noreply@, notifications@, alerts@, etc.
  • Emails with List-Unsubscribe headers (newsletters)
  • Common SaaS notification patterns (monitoring, dev tools, finance, calendar, etc.)

Use --include-automated to see all emails including these.

Status indicators:

  • 🔴 UNREAD - New email you haven't read
  • 📝 DRAFT UNSENT - You started a reply but never sent it
  • ⏳ NEEDS REPLY - Read but not replied to

Archive Emails

Archive emails by removing the INBOX label (requires gmail.modify scope):

service.users().messages().modify(
    userId="me",
    id=msg_id,
    body={"removeLabelIds": ["INBOX"]}
).execute()

For bulk archiving, use batch requests (max 100 per batch):

batch = service.new_batch_http_request()
for msg in messages[:50]:  # Keep under 100 limit
    batch.add(service.users().messages().modify(
        userId="me", id=msg["id"], body={"removeLabelIds": ["INBOX"]}
    ))
batch.execute()

Common Workflows

Find and reply to an email (properly threaded)

  1. Search for the email: search_emails.py "from:person subject:topic" --json
  2. Get the message ID from results, then read it: read_email.py <message_id>
  3. Get threading info (thread_id and Message-ID header) from the email metadata
  4. Create a threaded draft reply: create_draft.py --to "person@email.com" --subject "Re: topic" \ --reply-to "<Message-ID-header>" --thread-id "<thread_id>" \ --body "Your reply"

Find emails needing reply

  1. Run: needs_reply.py --max-results 30
  2. Review emails marked as 🔴 UNREAD, 📝 DRAFT UNSENT, or ⏳ NEEDS REPLY
  3. For each email needing reply, get its thread_id and Message-ID, then draft a threaded response

Inbox triage (complete workflow)

  1. Run needs_reply.py --max-results 50 to get all emails needing attention
  2. Filter out noise - Identify and archive:

- Newsletters (from: noreply, notifications, news@, etc.) - Receipts and invoices (from: receipts@, invoice@) - Automated alerts (from: alerts@, alert@) - Marketing emails (promotions, etc.) - Transaction notifications (banking, expense tools)

  1. Categorize real emails:

- 📝 DRAFT UNSENT - You started but didn't send (finish or delete draft) - 🔴 UNREAD from real people - Read and respond - ⏳ NEEDS REPLY - Prioritize by importance

  1. Draft threaded responses (always use --reply-to and --thread-id)
  2. Archive remaining notifications in bulk

Identifying newsletters vs real emails

Common newsletter/notification patterns to archive:

  • from:noreply or from:no-reply
  • from:notifications@ or from:alerts@
  • from:news@ or from:newsletter@
  • from:*@substack.com (newsletters)
  • from:receipts@ or from:invoice@
  • from:*@stripe.com (payment receipts)
  • Monitoring: Datadog, PlanetScale, Better Stack, etc.

Drafting Emails Best Practices

When drafting emails:

  • Always use HTML format (--html) when including links
  • Hyperlink text like "here" rather than showing raw URLs
  • Include proper threading with --reply-to and --thread-id for replies
  • Consider creating a memory block to store the user's email style preferences (greeting, signature, tone)

Search Query Syntax

For complex searches, see reference/search_operators.md for Gmail search operators.

Common operators:

  • from: / to: - Filter by sender/recipient
  • subject: - Search in subject line
  • is:unread / is:read - Filter by read status
  • in:inbox / in:sent / in:drafts - Filter by location
  • after: / before: - Date filters (YYYY/MM/DD format)
  • has:attachment - Emails with attachments
  • larger: / smaller: - Filter by size

API Limits & Gotchas

  • Batch request limit: Max 100 requests per batch (use 50 to be safe)
  • Rate limits: Gmail API has daily quotas; batch operations help stay under limits
  • Threading gotcha: Drafts without --reply-to and --thread-id create NEW threads, not replies
  • Draft detection: Unsent drafts don't count as replies - needs_reply.py handles this correctly
  • Token expiry: Tokens auto-refresh, but if authentication fails, delete token.json and re-auth

Security Notes

  • credentials.json contains OAuth client secrets - do not commit to version control
  • token.json contains access tokens - do not share or commit
  • Add both to .gitignore
  • Tokens can be revoked at https://myaccount.google.com/permissions

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

04

需要参考平台分布和安装热度时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Claude Code

26.46%
按下载量换算71

OpenCode

24.77%
按下载量换算67

Gemini CLI

16.08%
按下载量换算43

windsurf

13.02%
按下载量换算35

Cursor

8.56%
按下载量换算23

Antigravity

3.42%
按下载量换算9

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。

来源信息

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