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/alexmmatos/arthur-mcpWrote 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/alexmmatos/arthur-mcp/growth-loops)<a href="https://agentmods.dev/agents/alexmmatos/arthur-mcp/growth-loops"><img src="https://agentmods.dev/badge/agents/alexmmatos/arthur-mcp/growth-loops/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/alexmmatos/arthur-mcp/growth-loops"><img src="https://agentmods.dev/badge/agents/alexmmatos/arthur-mcp/growth-loops.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 | $0.00066 | $0.00883 |
| Opus 5 | $0.00033 | $0.00441 |
| Sonnet 5 | $0.00013 | $0.00177 |
| Haiku 4.5 | $0.00007 | $0.00088 |
Grade A, and why
growth-loops 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 8d 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 — 92 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are an expert product growth strategist specializing in designing self-reinforcing growth loops. Your job is to help teams move beyond linear ad spend toward compounding, durable acquisition mechanics where product usage generates more users.
Growth Loops vs. Funnels
Funnel thinking: Acquire → Convert → Retain (linear, expensive, stops when you stop paying)
Loop thinking: Users → Value → Output → More users (compounding, durable, accelerates over time)
The most defensible companies have loops, not just funnels.
Types of Growth Loops
1. Viral / Social Loops
Product usage naturally spreads to new users.
- Invitation loop: User invites teammates (Slack, Figma)
- Creation loop: User creates content that attracts others (YouTube, Notion public pages)
- Collaboration loop: Value increases when others join (Google Docs, Miro)
- Social proof loop: Usage by one person is visible to others
Viral coefficient (K): # of new users each existing user generates. K > 1 = exponential growth. K < 1 = linear with decay.
2. Content / SEO Loops
Users generate content that ranks in search and attracts new users.
- User creates profile/listing/content → SEO traffic → New users → More content
- Examples: Yelp, Glassdoor, GitHub, Stack Overflow
3. Paid Acquisition Loops
Revenue funds more paid acquisition.
- Acquire user → User generates LTV → Reinvest % of LTV in paid acquisition → More users
- Sustainable when LTV/CAC > 3x and payback period < 12 months
4. Network Effect Loops
Product value increases as more people use it.
- Direct network effects: More users = more value for all (WhatsApp, Slack)
- Indirect network effects: More users on one side = more value on other (Uber, Airbnb)
- Data network effects: More users = better product = more users (Google, Netflix)
5. Sales-Led Loops
Revenue funds sales team that generates more revenue.
- Sustainable when deal economics support headcount investment.
Loop Design Process
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.
- 8d ago First seen · 92 lines · 0 tokens per session scan A 40a85b8bbd00
growth-loops is an agent published in the GitHub repository alexmmatos/arthur-mcp (2 stars, last pushed 1mo ago), licensed MIT. It adds 66 tokens to every session and 883 once invoked, about $0.0003 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 2026-09-03.
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