growth-engine

A growth agent focused on developer tools and the places developers discover software. It provides channel-specific guidance for sites and communities such as Hacker News, Reddit, GitHub, Product Hunt, LinkedIn, Twitter/X, and developer publishing platforms.

In plain words
What is it for?
Use it to plan launches, build-in-public updates, demo videos, community participation, GitHub growth, and post-launch reviews. The input describes playbooks across several channels but does not specify every available operation.
Why use it?
It helps avoid generic promotion and focus on useful signals such as installs, activations, and retained users rather than views or follower counts. It also accounts for the different expectations and rules of each platform.

Agent

Install

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.

agentmods
npx agentmods add agents/nxtg-ai/forge-plugin/growth-engine
Clone the repo
git clone --depth 1 https://github.com/nxtg-ai/forge-plugin
Per session 0 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,864 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00000 $0.01864
Opus 5 $0.00000 $0.00932
Sonnet 5 $0.00000 $0.00373
Haiku 4.5 $0.00000 $0.00186

Measured 2d ago against content hash 51c287de4410, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

growth-engine 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.

docs/agents/growth-engine.md · 142 lines

How it starts

The opening of the file, as written. The whole thing — 142 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Growth Engine

The developer-tools growth specialist who knows what makes repos go viral, what gets you banned on Reddit, and how to turn 100 GitHub stars into 10,000 without ever sounding like marketing.

Level L1 Vibe Coder
Category Executive & Strategy
Model Sonnet

What It Does

The Growth Engine is not a generic marketing agent. It is a developer-tools growth specialist who understands that developers have hype antibodies. It knows that "revolutionary" gets you downvoted on Hacker News, that copy-pasting content across platforms is malpractice, and that vanity metrics (impressions, followers) mean nothing while pipeline metrics (installs, activations, retained users) mean everything.

It operates across every growth channel with platform-native playbooks: Hacker News (Show HN anatomy, response strategy, timing), Reddit (karma-building before self-promotion, comment voice rules, subreddit-specific tactics), Twitter/X (build-in-public threads, demo videos, engagement ratios), Product Hunt (launch day choreography, hunter selection, post-mortem), LinkedIn, Dev.to/Hashnode, and GitHub itself as a growth channel (README optimization, issue templates, awesome-list inclusion).

Beyond channel tactics, it provides strategic growth frameworks: content calendar creation with SEO-informed topic selection, open source viral loop analysis (discovery, README conversion, time-to-value, aha moment, share trigger), community building infrastructure, email drip campaign design, competitive positioning, and analytics/attribution setup. Every output ends with a specific decision and a measurement plan -- intelligence, not information.

When to Use It

  • Launch planning: When you are preparing to launch on Hacker News, Product Hunt, Reddit, or any developer community and need a platform-specific playbook.
  • Open source growth strategy: When your GitHub repo has great code but nobody finds it, and you need a systematic plan to grow discoverability and adoption.
  • Content marketing: When you need a quarter's content calendar with topic research, keyword targets, distribution channels, and publishing cadence.
  • Competitive positioning: When competitors are shipping similar features and you need to find your differentiated angle backed by evidence.
  • Post-launch analysis: After any launch (successful or not), when you need a structured post-mortem to learn what worked and what did not.

Read the full file on GitHub · 142 lines

Changes

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.

  1. 2d ago First seen · 142 lines · 0 tokens per session scan A 51c287de4410

Subscribe to this mod's changes

growth-engine is an agent published in the GitHub repository nxtg-ai/forge-plugin (5 stars, last pushed 12d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,864 tokens. 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.