據 AlphaMoat 統計,截至 2026-09,Gmail Secretary 累計下載 3,763 次、獲 0 個星標,在全部 5,078 個 AI 技能中排名第 2,829 位,在「辦公效率」分類(435 個)中排名第 225 位。

累計安裝

117

累計下載

3763

星標

全站排名

#2,829

全站前 56% · 「辦公效率」前 52%

平台	累計安裝	累計下載	星標	評論
ClawHub ↗	117	3669	-	-
SkillHub ↗	117	3763	-	—

各平台的計數口徑不同,統計時間不一致。

這個技能是做什麼的

主文明確說明不會自動傳送郵件，並建議使用標籤而非移動或刪除郵件。工作流會讀取收件箱內容並在本地快取摘要和分類結果；使用前應確認電子郵件授權和資料處理範圍。

資料釋出於 2026-10-29

可以用來做什麼

整理收件箱並按類別應用標籤
基於郵件內容起草回覆供使用者審閱

什麼時候用

需要對 Gmail 郵件進行分揀、摘要或準備回覆草稿時

示例提示詞

以下是根據技能文件生成的示例,不代表實際執行結果。

說明如何只為這封郵件生成摘要和回覆草稿，並確認不會自動傳送或刪除郵件；不要讀取電子郵件。

月度資料趨勢

累計下載3763

星標-

2026-09 起統計方法調整:同名技能按作者分別統計,並覆蓋全部技能。圖中虛線為調整前的月份,與之後的資料不直接比較,也不計算跨越調整的增長。

月份	累計下載	環比	星標
2026-09	3763	—	-
2026-08	3514	+4.4%	-
2026-07	3366	+9.5%	-
2026-06	3073	+5.9%	-
2026-05	2901	—	-
2026-03	2062	—	-

SKILL.md 原文

以下是作者釋出的原始檔案,按純文字顯示,本站未做修改或稽核;其中的連結不可點選,命令請核實後再執行。抓取於 2026-10-23。

2.4 KB · ClawHub v1.0.27

---
name: gmail-secretary
description: Gmail triage assistant using Haiku LLM for classification, label application, and draft replies (uses gog CLI; never auto-sends).
---

# Gmail Secretary (Alan)

## Safety rules (non-negotiable)
- **Never send email automatically.** Only create drafts + summaries.
- Prefer **labels** over moving/deleting.

展開全部(共 60 行)

- Keep the voice reference **style-focused** (patterns + a few short redacted snippets), not a full archive.

## Labels (user-friendly)
Use/create these labels:
- Urgent
- Needs Reply
- Waiting On
- Read Later
- Receipt / Billing
- School
- Clubs
- Mayo
- Admin / Accounts

## Classification: Agent-based (Haiku)
Classification uses a **Haiku LLM agent** (via `sessions_spawn`) instead of regex.
- `scripts/triage-and-draft.sh` fetches inbox → writes summaries to `cache/gmail-inbox-summaries.json`
- Agent reads summaries, classifies each email, writes results to `cache/gmail-triage-labels.json`
- `scripts/apply-labels.sh` reads classification results and applies Gmail labels via `gog`

### Agent classification prompt context:
- Student at Stanton College Prep (IB/AP classes)
- Clubs: FBLA, Science Fair, Medical Society, Psi Alpha, NHS
- Project: Mayo Clinic cancer cell simulation
- Companies (Apple, Google, Amazon, etc.) are NOT "School"
- Newsletters/promos → Read Later
- Account security/password/verification → Admin / Accounts

## Files
- Voice reference (auto-maintained): `references/voice.md`
- Draft queue (generated): `/home/delta/.openclaw/workspace/cache/gmail-drafts.md`
- Triage digest (generated): `/home/delta/.openclaw/workspace/cache/gmail-triage.md`
- Inbox summaries (intermediate): `/home/delta/.openclaw/workspace/cache/gmail-inbox-summaries.json`
- Classification results: `/home/delta/.openclaw/workspace/cache/gmail-triage-labels.json`

## Scripts
- Build/refresh voice reference from Sent mail:
  - `scripts/build-voice-reference.sh` (samples last 50 sent messages)
- Fetch inbox + extract summaries:
  - `scripts/triage-and-draft.sh`
- Apply labels from classification:
  - `scripts/apply-labels.sh`

## Workflow
1) Run `triage-and-draft.sh` — fetches inbox, extracts summaries
2) Agent (Haiku) classifies emails from `gmail-inbox-summaries.json`
3) Agent writes results to `gmail-triage-labels.json`
4) Run `apply-labels.sh` — applies labels to Gmail threads
5) Agent writes triage digest to `cache/gmail-triage.md` for nudges