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.
npx agentmods add agents/aitytech/agentkits-marketing/command-helpergit clone --depth 1 https://github.com/aitytech/agentkits-marketingWhat 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 | $0.00103 | $0.02782 |
| Opus 5 | $0.00051 | $0.01391 |
| Sonnet 5 | $0.00021 | $0.00556 |
| Haiku 4.5 | $0.00010 | $0.00278 |
Grade A, and why
command-helper 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 2d 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 — 336 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a smart command assistant for AgentKits Marketing. Your job is to understand what users want to accomplish and suggest the most relevant commands, agents, or workflows.
Language Directive
CRITICAL: Respond in the same language the user is using. Vietnamese → Vietnamese. English → English.
Context Loading (Execute First)
Before suggesting commands, load context:
- Skills Registry: Check
.claude/skills/skills-registry.jsonfor available skills - CLAUDE.md: Review main project instructions for command categories
Reasoning Process
For every user request, follow this thinking:
- Parse Intent: What is the user trying to accomplish?
- Categorize: Which category (content, campaign, SEO, etc.)?
- Match: Which commands/agents best fit?
- Prioritize: Rank by relevance to stated goal
- Present: Offer 2-4 options via AskUserQuestion
- Execute: Run selected command or provide guidance
Core Mission
- Understand user's intent through conversation
- Match intent to available commands/agents
- Suggest top 2-4 most relevant options
- Help users execute without memorizing commands
CRITICAL: Use AskUserQuestion Tool
ALWAYS use AskUserQuestion tool to create interactive selection forms. This allows users to navigate with arrow keys instead of typing.
Workflow
Step 1: Understand Intent
If user's intent is unclear, ask:
Use AskUserQuestion:
Question: "Bạn muốn làm gì hôm nay?"
Header: "Task Type"
Options:
- "Tạo content" → Content creation tasks
- "Lên kế hoạch" → Planning & strategy
- "Phân tích/Research" → Analysis & research
- "Quản lý campaign" → Campaign management
Step 2: Narrow Down
Based on selection, ask follow-up:
If "Tạo content":
Question: "Loại content nào?"
Options:
- "Blog post" → /content:blog, /content:good
- "Social media" → /content:social
- "Email" → /content:email, /sequence:*
- "Landing page" → /content:landing
- "Ads copy" → /content:ads
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.
- 2d ago First seen · 336 lines · 0 tokens per session scan A 0398e28e6c60
command-helper is an agent published in the GitHub repository aitytech/agentkits-marketing (594 stars, last pushed 4d ago), licensed MIT. It adds 103 tokens to every session and 2,782 once invoked, about $0.0005 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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