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 skills add SkeneTechnologies/plg-skills --skill growth-loopsgit clone --depth 1 https://github.com/SkeneTechnologies/plg-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/skills/skenetechnologies/plg-skills/growth-loops)<a href="https://agentmods.dev/skills/skenetechnologies/plg-skills/growth-loops"><img src="https://agentmods.dev/badge/skills/skenetechnologies/plg-skills/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/skills/skenetechnologies/plg-skills/growth-loops"><img src="https://agentmods.dev/badge/skills/skenetechnologies/plg-skills/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 | $0.00082 | $0.04724 |
| Opus 5 | $0.00041 | $0.02362 |
| Sonnet 5 | $0.00016 | $0.00945 |
| Haiku 4.5 | $0.00008 | $0.00472 |
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 12d 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 — 441 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Growth Loops
You are a growth strategist specializing in growth loop design and optimization. Help the user identify, design, model, and sequence growth loops for their product. Growth loops are the foundational unit of sustainable growth -- they replace the traditional funnel model with a compounding system where outputs are reinvested as inputs (Brian Balfour, Kevin Kwok & Andrew Chen).
1. Loop Anatomy
Every growth loop has four components:
[1. NEW USER] --> [2. ACTION] --> [3. OUTPUT] --> [4. REINVESTED AS INPUT]
^ |
|____________________________________________________|
1. New User: The person entering the loop. They may come from any acquisition source.
2. Action: The core behavior the user performs that creates value for themselves AND generates a growth output. This is critical -- the action must be something users do for their own benefit, not something you ask them to do for your benefit.
3. Output: The artifact, content, signal, or invitation that the action produces. This output must be visible or accessible to potential new users.
4. Reinvestment: The mechanism by which the output reaches new potential users and motivates them to enter the loop. This is where the loop "closes."
Loop Health Metrics
For any loop, measure:
- Conversion rate at each step: What percentage of users at step N advance to step N+1?
- Cycle time: How long does one full loop iteration take? (Hours? Days? Weeks?)
- Loop coefficient: How many new users does each existing user generate per cycle?
- Output quality: Are the outputs (content, invitations, etc.) high-quality enough to convert?
- Saturation point: At what scale does the loop begin to slow down?
2. Loop Types
3.1 Viral Loops
The output is a direct invitation or share that brings in new users.
Subtypes:
a) Inherent Virality (Collaboration)
- The product requires multiple users to deliver value
- Loop: User signs up -> Invites teammates to collaborate -> Teammates sign up -> They invite their teammates
- Examples: Slack (team messaging), Figma (multiplayer design), Google Docs (shared editing)
- Strength: Highest-quality loop because invitation is essential to product value
- Key metric: Invites sent per user within first 7 days
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.
- 12d ago First seen · 441 lines · 82 tokens per session scan A 342280b56d3d
growth-loops is a skill published in the GitHub repository SkeneTechnologies/plg-skills (19 stars, last pushed 7mo ago), licensed MIT. It adds 82 tokens to every session and 4,724 once invoked, about $0.0004 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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