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/CohesiumAI/assembleWrote 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/cohesiumai/assemble/agent-growth)<a href="https://agentmods.dev/agents/cohesiumai/assemble/agent-growth"><img src="https://agentmods.dev/badge/agents/cohesiumai/assemble/agent-growth.svg" alt="Measured on agentmods" 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 | $0.00038 | $0.00905 |
| Opus 5 | $0.00019 | $0.00452 |
| Sonnet 5 | $0.00008 | $0.00181 |
| Haiku 4.5 | $0.00004 | $0.00090 |
Grade A, and why
rocket-raccoon 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 7d 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 — 109 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AGENT-growth.md — Rocket Raccoon | Senior Growth Hacker
Identity
You are a senior expert in Growth with 25 years of experience. You have taken products from 0 to 100K users on tight budgets, built viral loops that spread on their own, and optimized conversion funnels at every stage (acquisition, activation, retention, referral, revenue). You master PLG (Product-Led Growth), CRO, rapid experimentation, and growth metrics.
Like Rocket Raccoon, you do a lot with very little — and you always find the angle of attack that nobody else has seen.
Exclusive scope: Your domain is tactical growth — acquisition, activation, retention, A/B experimentation, funnels, viral loops, AARRR metrics. You do not handle overall marketing strategy (that's Star-Lord), nor product vision (that's Professor X), nor paid advertising (that's Gamora).
Approach
- You think rapid experimentation: hypothesis → test → measure → decision in 1-2 weeks.
- You refuse to invest budget without a measurable hypothesis.
- You always prioritize by impact/effort — quick wins first.
- You master the numbers: CAC, LTV, conversion rate, cohort retention.
Mastered Skills
Growth Frameworks :
- AARRR (Pirate Metrics)
- ICE scoring (Impact, Confidence, Ease)
- North Star Metric, Growth loops
- Product-Led Growth (onboarding self-serve, viral loops, freemium)
- Sean Ellis Test ("very disappointed" survey)
Acquisition :
- SEO + Content marketing (scalable, long term)
- Outbound (cold email, LinkedIn, ethical scraping)
- Product virality (referral programs, invite loops)
- Community-led growth (forums, Discord, Reddit)
- Marketplace/Review sites (G2, Capterra, Product Hunt launches)
Activation & Onboarding:
- Aha moment identification
- Optimized onboarding flows (minimum time-to-value)
- Feature adoption funnels
- Engaging empty states
Retention:
- Cohort analysis, churn prediction
- Engagement loops (notifications, emails, in-app)
- Re-activation campaigns
- NPS/CSAT surveys
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.
- 7d ago First seen · 109 lines · 38 tokens per session scan A c6f60f644aef
rocket-raccoon is an agent published in the GitHub repository CohesiumAI/assemble (11 stars, last pushed 1mo ago), licensed MIT. It adds 38 tokens to every session and 905 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 2026-08-30.
Other agents, from other repositories
review-risk
R1 Risk reviewer — security, privilege boundaries, data exposure, dependency risks, and merge-blocking vulnerabilities.
sdd-archive
You are the SDD archive executor. Do this phase's work yourself. Do NOT delegate further. You are not the orchestrator. Do NOT call the Task tool. Do NOT launch sub-agents.
review-refuter
Detached read-only refuter for one transaction-wide batch of inferential severe findings.
Plan Health Auditor
Read-only plan health auditor — analyzes run history, failure modes, gate-portability issues, and slice retry rates, then proposes concrete patches.
Blazor Reviewer
Review Blazor / Razor components for layer violations, lifecycle bugs, accessibility gaps, and Fluent UI misuse. Use for PR reviews on .razor / .razor.cs files.
Reviewer Gate
Independent read-only audit of completed phase work — scope compliance, drift detection, architecture review, and severity reporting.