據 AlphaMoat 統計,截至 2026-09,Agent Content Pipeline 累計下載 4,850 次、獲 6 個星標,在全部 5,078 個 AI 技能中排名第 1,936 位,在「AI 智慧體」分類(969 個)中排名第 366 位。
| 平台 | 累計安裝 | 累計下載 | 星標 | 評論 |
|---|---|---|---|---|
| ClawHub ↗ | 151 | 4520 | 6 | 2 |
| SkillHub ↗ | 657 | 4850 | 6 | — |
各平台的計數口徑不同,統計時間不一致。
內容按草稿、已評審、已修改、已批准、已釋出的狀態在目錄間流轉,其中批准這一步只能由人來完成。命令列支援列出、移動、評審與釋出到社交平台,釋出前可先預覽而不真正發出。 agent 本身不能核准或發文;須由人核准,再透過 CLI 手動發布。發布前先預覽,並檢查帳號憑證及公開內容風險。
資料釋出於 2026-10-27
以下是根據技能文件生成的示例,不代表實際執行結果。
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 | 4850 | — | 6 |
| 2026-08 | 4373 | +1.7% | 6 |
| 2026-07 | 4301 | — | 6 |
| 2026-05 | 4073 | — | 5 |
| 2026-03 | 3720 | — | 5 |
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。
--- name: agent-content-pipeline description: Safe content workflow (drafts/reviewed/revised/approved/posted) with human-in-the-loop approval, plus CLI to list/move/review and post to LinkedIn/X. Use when setting up a content pipeline, drafting content, managing review threads, or posting approved content. --- # Content Pipeline Skill Safe content automation with human-in-the-loop approval. Draft → Review → Approve → Post. ## Setup
```bash
npm install -g agent-content-pipeline
content init . # Creates folders + global config (in current directory)
```
For cryptographic approval signatures (password-protected):
```bash
content init . --secure
```
This creates:
- `drafts/` — work in progress (one post per file)
- `reviewed/` — human reviewed, awaiting your revision
- `revised/` — you revised, ready for another look
- `approved/` — human-approved, ready to post
- `posted/` — archive after posting
- `templates/` — review and customize before use
- `.content-pipeline/threads/` — feedback thread logs (not posted)
## Your Permissions
✅ **Can do:**
- Write to `drafts/`
- Read all content directories
- Revise drafts based on feedback
- Move revised files to `revised/`
- Run `content list` to see pending content
❌ **Cannot do:**
- Move files to `approved/` (only the human can approve)
- Post content
- Set `status: approved`
## Creating Content
**One post per file.** Each suggestion or draft should be a single post, not a collection.
File naming: `YYYY-MM-DD-<platform>-<slug>.md`
Use frontmatter:
```yaml
---
platform: linkedin # linkedin | x | reddit (experimental)
title: Optional Title
status: draft
subreddit: programming # Required for Reddit
---
Your content here.
```
Tell the human: "Draft ready for review: `content review <filename>`"
## The Review Loop
```
drafts/ → reviewed/ → revised/ → approved/ → posted/
↑ │
└──────────┘
more feedback
```
1. You write draft to `drafts/`
2. Human runs `content review <file>`:
- **With feedback** → file moves to `reviewed/`, you get notified
- **No feedback** → human is asked "Approve?" → moves to `approved/`
3. If feedback: you revise and move to `revised/`
4. Human reviews from `revised/`:
- More feedback → back to `reviewed/`
- Approve → moves to `approved/`
5. Posting happens manually via `content post`
### After Receiving Feedback
When you get review feedback:
1. Read the file from `reviewed/`
2. Apply the feedback
3. Move the file to `revised/`
4. Confirm what you changed
5. (Optional) Add a note: `content thread <file> --from agent`
## Platform Guidelines
### LinkedIn
- Professional but human
- Idiomatic language (Dutch for NL audiences, don't be stiff)
- 1-3 paragraphs ideal
- End with question or CTA
- 3-5 hashtags at end
### X (Twitter)
- 280 chars per tweet (unless paid account)
- Punchy, direct
- 1-2 hashtags max
- Use threads sparingly
- If Firefox auth fails, you can paste `auth_token` and `ct0` manually
Manual cookie steps:
1) Open x.com and log in
2) Open DevTools → Application/Storage → Cookies → https://x.com
3) Copy `auth_token` and `ct0`
### Reddit (experimental)
- Treat as experimental; API and subreddit rules can change
- Requires `subreddit:` in frontmatter
- Title comes from frontmatter `title:` (or first line if missing)
- Match each subreddit's rules and tone
## Commands Reference
```bash
content list # Show drafts and approved
content review <file> # Review: feedback OR approve
content mv <dest> <file> # Move file to drafts/reviewed/revised/approved/posted
content edit <file> # Open in editor ($EDITOR or code)
content post <file> # Post (prompts for confirmation)
content post <file> --dry-run # Preview without posting
content thread <file> # Add a note to the feedback thread
```
## Security Model
The security model separates drafting (AI) from approval/posting (human):
- ✅ Agent drafts content
- ✅ Agent revises based on feedback
- ❌ Agent cannot approve (human approves via `content review`)
- ❌ Agent cannot post
Posting is handled manually via CLI — never by the agent directly.
### Platform-specific security
| Platform | Auth Storage | Encrypted? | Password Required? |
|----------|--------------|------------|-------------------|
| LinkedIn | Browser profile | ✅ Yes | ✅ Yes |
| X/Twitter | Firefox tokens | ✅ Yes | ✅ Yes |
Both platforms require password to post. Tokens are extracted from Firefox and encrypted locally.
將開發過程中的經驗、錯誤與修正記錄為 Markdown 檔案,供日後重用並提升為工作區記憶。
用自然語言描述需求,在本機與遠端技能市場尋找技能並取得推薦。
給 AI agent 用的瀏覽器自動化命令列技能。
將使用者明確糾正與自我檢視整理成分層記憶,並依使用情況升級或封存。
在安裝第三方技能之前,按清單審查來源、許可權與危險模式的技能。
將代理記憶與跨技能狀態整理成具型別與約束的知識圖譜。
規劃 AI 代理主動跟進、工作記憶與回顧流程的工作區設定指南。
指導如何建立與更新有效 Claude 技能的寫作指南。
資料月份:2026-09 · 下載/星標/安裝數聚合自公開技能註冊庫(ClawHub、SkillHub),按月更新。口徑說明見資料方法。