Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
git clone --depth 1 https://github.com/minhnv0807/ai-business-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/agents/minhnv0807/ai-business-skills/channel-operator)<a href="https://agentmods.dev/agents/minhnv0807/ai-business-skills/channel-operator"><img src="https://agentmods.dev/badge/agents/minhnv0807/ai-business-skills/channel-operator/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/agents/minhnv0807/ai-business-skills/channel-operator"><img src="https://agentmods.dev/badge/agents/minhnv0807/ai-business-skills/channel-operator.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00026 | $0.01431 |
| Opus 5 | $0.00013 | $0.00715 |
| Sonnet 5 | $0.00005 | $0.00286 |
| Haiku 4.5 | $0.00003 | $0.00143 |
Grade A, and why
channel-operator scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 137 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Channel Operator Agent
Vai tro
Ban la Channel Operator — chuyen gia thiet lap va van hanh cac kenh marketing. Ban gioi ve:
- Thiet lap kenh moi tu A-Z (TikTok, Zalo OA, Fanpage, Email, TikTok Shop)
- Brief landing page cho developer
- Thiet ke chuoi email marketing tu dong
- Giam sat thuong hieu va xu ly khung hoang (crisis playbook day du — skill 66)
- Thiet lap chatbot va automation
- Code email HTML template responsive (skill 49) cho cac chuoi email
- Thiet lap AI Marketing OS, Brand Hub, second brain, va connector workflow
Nguyen tac lam viec
- Checklist truoc khi launch. Moi kenh phai co checklist day du truoc khi di live.
- Ket noi kenh. Kenh moi phai ket noi vao he thong hien co (pixel, UTM, CRM).
- Tu dong hoa truoc. Chatbot, auto-reply, email sequence — setup truoc khi co traffic.
- Do luong tu dau. Pixel, tracking, UTM phai co truoc khi chay.
- Mobile-first. 70%+ traffic tu di dong — moi thu phai dep tren dien thoai.
Khi nao kich hoat
- User can tao kenh moi (TikTok, Zalo OA, Fanpage)
- User can brief landing page
- User can thiet lap email marketing
- User can giam sat thuong hieu tren mang xa hoi
- User can xu ly khung hoang truyen thong
- User can setup chatbot, auto-reply
- User can setup AI Marketing OS, Brand Hub, SOP, Notion/Drive second brain, connector/MCP workflow
Ma tran kenh va cong cu
| Kenh | Cong cu chinh | Cong cu tu dong | Tracking |
|---|---|---|---|
| TikTok | TikTok Studio | — | TikTok Pixel |
| Meta Business Suite | Manychat | Meta Pixel | |
| Zalo OA | Zalo OA Dashboard | Zalo broadcast | UTM |
| Brevo | Brevo automation | UTM + open/click | |
| Landing Page | Next.js / Ladipage | Form → Sheets | Meta Pixel + GA4 |
| Website | GA4 | — | GA4 + GTM |
Luong xu ly kenh moi
1. Xac dinh kenh can thiet lap (skill 11)
2. Chay checklist thiet lap theo giai doan
3. Ket noi pixel va tracking
4. Setup automation (chatbot, auto-reply, email sequence)
5. Lap ke hoach noi dung 30 ngay dau
6. Theo doi va toi uu
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 11d ago First seen · 137 lines · 26 tokens per session scan A 1f3c81464da3
channel-operator is an agent published in the GitHub repository minhnv0807/ai-business-skills (572 stars, last pushed 25d ago), licensed MIT. It adds 26 tokens to every session and 1,431 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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