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gmail-labelerGmail labeler 安全

Agent Skill

gmail-labeler 用于辅助前端页面、组件、样式和交互逻辑开发,适合在 OpenClaw 中需要维护前端项目、生成组件或检查界面实现时使用。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

4,375

周安装

177

GitHub Stars

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下载量

1,374
OpenClaw

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

2

许可证

MIT-0

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-labeler(Gmail labeler 安全)
来源仓库:https://github.com/felipematos/gmail-labeler
安装命令:
openclaw skills install gmail-labeler
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。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install gmail-labeler

简介

gmail-labeler 使用轻量级 LLM 对 Gmail 收件箱进行分类和安全归档,兼顾效率与智能。

  • 适用于企业级邮件自动化处理,强调隐私保护和合规性。
  • 结合 gog CLI 工具和可配置模型层,实现精准标签分配。
  • 使用前需授权 API 访问并设置模型参数,注意数据加密存储。
  • 建议定期更新模型版本并审计日志,确保系统稳定运行。

SKILL.md

name
gmail-labeler
description
Gmail inbox triage, labeling, and safe archiving with gog plus a configurable lightweight LLM review layer. Use when building or running Gmail automation that separates actionable vs non-actionable mail, applies Gmail labels, archives low-value messages, keeps important human replies in Inbox, routes urgent items for notification, supports multilingual inboxes (English, Portuguese, Spanish), and needs a clean publishable skill with private local overlays kept outside the skill folder.
metadata

Gmail Labeler

A production-oriented Gmail labeling workflow built around:

  • gog for Gmail access
  • a local overlay for private rules/accounts/routes
  • a hybrid review flow: heuristics first, lightweight LLM review for ambiguity-band messages
  • a 15-minute cron-friendly runner

What it does

  • Classifies inbox items into non-actionable vs actionable buckets
  • Applies Gmail labels and archives non-actionable mail
  • Keeps replies, opportunities, urgent billing items, and other actionable mail in Inbox
  • Supports English, Portuguese, and Spanish keyword coverage out of the box
  • Logs every decision to JSONL for auditability and tuning
  • Purges logs older than 30 days
  • Supports a daily self-improvement review loop based on prior decisions and user corrections

Default categories

Non-actionable

  • Newsletters
  • Promotions
  • Notifications
  • Ordinary receipts

Actionable

  • Billing issues
  • Replies
  • Opportunities
  • Action Required

What stays local/private

Keep user-specific editorial, business, or inbox-policy rules in the local overlay, not in the shared skill defaults. Examples of local-only rules:

  • PR / press release handling
  • press trip or media invitation routing
  • VIP sender policies
  • business-specific labels
  • custom notification routes

Operating model

1. Sender-type-first routing

Classify sender as:

  • person
  • company
  • person_or_unknown

This keeps bulk automated mail cheap to classify and reserves deeper review for ambiguous or human-origin messages.

2. Inbox-by-exception policy

Treat Inbox as an action queue, not a reading queue. Recommended default:

  • processed mail always gets Auto/Triaged
  • mail stays in Inbox only when it is clearly actionable / important
  • everything else should leave Inbox, even when the category is still somewhat generic

Practical effect:

  • important/actionable mail → keep in Inbox and add category labels when possible
  • non-important mail → remove INBOX, keep Auto/Triaged, then add a best-fit category label (Notification, Newsletter, Receipt, Press Releases, etc.)

3. Confidence-band review

Use heuristics first. Then send only ambiguity-band messages to a lightweight LLM review.

Recommended pattern:

  • high confidence → trust heuristics
  • medium confidence → LLM review
  • low confidence → conservative fallback

4. Conservative-but-useful fallback

If a message is clearly automated/company-origin but no specific filter matches, prefer a generic non-actionable classification (for example Notification) over leaving it untouched in Inbox.

5. Label normalization

Use a small canonical label set and avoid near-duplicates caused by translation, singular/plural, or typos. Example normalization targets:

  • Press ReleasePress Releases
  • finance label variants → one canonical finance label
  • keep Auto/Triaged as the universal processed marker

Gmail-native labels to prefer

Use Gmail system labels when possible:

  • CATEGORY_PROMOTIONS
  • CATEGORY_UPDATES
  • IMPORTANT
  • STARRED
  • INBOX

Create custom labels only when needed, for example:

  • Newsletter
  • Notification
  • Receipt
  • Opportunity
  • Action Required
  • Auto/Triaged

Local overlay design

Keep the skill publishable by storing private configuration outside the skill directory.

Recommended local overlay path:

~/.openclaw/local/gmail-labeler.config.json

Store private values only in the local overlay:

  • email accounts
  • VIP senders/domains
  • notification targets
  • business-specific opportunity rules
  • personal/custom labels

Logging and review

Decision logs should live outside the skill source tree, for example:

/home/ubuntu/.openclaw/gmail-labeler-logs/

Recommended format:

  • one JSONL file per day
  • one row per decision
  • separate error rows

Suggested daily review inputs:

  • yesterday's decision log
  • false positives / false negatives
  • over-aggressive archiving
  • missed billing urgency
  • missed opportunities
  • user-requested corrections

Files to read

  • references/default-config.json
  • references/config-guide.md
  • references/filter-catalog.md
  • references/implementation-notes.md
  • references/logging-and-review.md
  • references/llm-review.md
  • references/cron-example.md
  • references/ain-email-review.schema.json

Runners

  • Main runner: scripts/gmail_labeler_runner.py
  • Launcher example: scripts/gmail_labeler_run.sh

Publishing guidance

Before publishing:

  • keep only generic defaults in the skill
  • remove personal accounts, chat ids, private domains, and custom user rules
  • keep examples generic
  • document clearly that private configuration belongs in the local overlay
  • keep PR / press-release handling user-specific when it reflects private editorial policy; do not publish those local heuristics by default
  • validate cron/non-interactive execution via the launcher, not only via direct Python invocation

适合场景

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用户想查找某类 Agent Skill 时

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能力概览

能力 1

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能力 2

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能力 3

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能力 4

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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

OpenClaw

95.61%
按下载量换算1,314

安全审计

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通过

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只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

安装前确认

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