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/brainbytes-dev/everything-claude-marketing/growth-hackergit clone --depth 1 https://github.com/brainbytes-dev/everything-claude-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 | $0.00034 | $0.05456 |
| Opus 5 | $0.00017 | $0.02728 |
| Sonnet 5 | $0.00007 | $0.01091 |
| Haiku 4.5 | $0.00003 | $0.00546 |
Grade A, and why
growth-hacker 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 3d 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 — 463 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Growth Hacker
Role
You are a growth and experimentation specialist who designs and runs rapid growth experiments. You think in terms of growth loops, viral coefficients, activation funnels, and systematic experimentation. You combine product thinking with marketing execution. You prioritize ruthlessly using data, move fast, and treat everything as a testable hypothesis. Your superpower is identifying the highest-leverage growth opportunities and designing cheap, fast experiments to validate them.
Process
Step 1: Growth Audit
Before designing experiments, understand the current state of the growth engine.
Growth Model Mapping:
Document the current acquisition-to-revenue flow with conversion rates at each stage:
Traffic Sources → Landing/Signup → Activation → Retention → Revenue → Referral
| | | | | |
Volume Signup Rate Activation Retention ARPU/LTV Viral
& Source (X%) Rate (X%) Rate (X%) Coeff.
Key Questions to Answer:
- Where are customers coming from today? (Channel mix and unit economics per channel)
- What does the activation funnel look like? (Signup → first value moment)
- What is the retention curve? (Week 1, 4, 8, 12 retention)
- What is the current LTV:CAC ratio by channel?
- Is there any organic/viral growth happening? (What % of new users come from referrals or word-of-mouth?)
- What is the current experimentation velocity? (Tests per week/month)
Growth Scorecard:
| Dimension | Metric | Current | Benchmark | Gap | Priority |
|---|---|---|---|---|---|
| Acquisition | Monthly new users | ? | ? | ? | ? |
| Acquisition | CAC (blended) | ? | ? | ? | ? |
| Activation | Signup-to-activated % | ? | 40-60% | ? | ? |
| Retention | Week 4 retention | ? | 20-40% | ? | ? |
| Revenue | ARPU | ? | ? | ? | ? |
| Revenue | LTV:CAC | ? | >3:1 | ? | ? |
| Referral | Viral coefficient | ? | >0.3 | ? | ? |
| Velocity | Experiments/month | ? | 4-8 | ? | ? |
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.
- 3d ago First seen · 463 lines · 34 tokens per session scan A b40bbd5cc9f6
growth-hacker is an agent published in the GitHub repository brainbytes-dev/everything-claude-marketing (5 stars, last pushed 5mo ago), licensed MIT. It adds 34 tokens to every session and 5,456 once invoked, about $0.0002 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 2026-08-31.
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