According to AlphaMoat, as of 2026-09, Agent Content Pipeline has 4,850 downloads and 6 stars — ranked #1,936 of 5,078 AI skills overall, and #366 of 969 in AI Agent.
| Platform | Installs | Downloads | Stars | Comments |
|---|---|---|---|---|
| ClawHub ↗ | 151 | 4.5K | 6 | 2 |
| SkillHub ↗ | 657 | 4.8K | 6 | — |
Platforms count differently and update at different times.
Content passes through draft, reviewed, revised, approved, and posted folders, and the approval step can only be done by a human. The CLI lists, moves, and reviews items and posts to social platforms, and posting can be previewed without actually sending. The agent cannot approve or post content itself; a human approves, and posting is handled manually through the CLI. Preview before posting and review account credentials and public-content risks.
Profile published 2026-10-27
Generated from the skill’s documentation as examples; not results of actual runs.
The counting method changed in 2026-09: skills with the same name are now counted separately by author, and the full catalog is covered. Dashed lines show months before the change; they are not compared with later months, and no growth is computed across the change.
| Month | Downloads | MoM | Stars |
|---|---|---|---|
| 2026-09 | 4.8K | — | 6 |
| 2026-08 | 4.4K | +1.7% | 6 |
| 2026-07 | 4.3K | — | 6 |
| 2026-05 | 4.1K | — | 5 |
| 2026-03 | 3.7K | — | 5 |
The author’s original file, shown as plain text without edits or review by AlphaMoat. Links are not clickable; check commands before running them. Fetched 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.
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Data month: 2026-09 · Downloads, stars and installs are aggregated monthly from public skill registries (ClawHub, SkillHub). See methodology.