Grok Shill Simulator
Writing engaging crypto content is hard. Copying successful influencer styles? That's smart. We built an AI that does exactly that.
The Problem
Every whale knows the pain. You're sitting on a fat bag, but your shilling game is weak. Meanwhile, some anon with 100k followers posts "lfg $TOKEN to the moon đ" and gets more engagement than your entire portfolio's market cap.
The truth is, certain influencers have cracked the code. They know exactly how to craft posts that make degens ape, whales curious, and the algo happy. Their style is their alpha.
So why reinvent the wheel when you can learn from the masters?
Stage 1 - Project Intelligence
First, we need to understand what makes your project special. Feed the AI everything: your litepaper, tokenomics, dApp URLs, even your shower thoughts about the protocol.
What You Can Input
- Raw text descriptions of your project
- URLs to documentation sites
- Whitepaper links
- Token URLs from CoinGecko or CoinMarketCap
- Random thoughts about why it's revolutionary
The AI uses Claude Sonnet 4.0 with Firecrawl integration to dynamically scrape and analyze web content.
How It Processes
Our research engine doesn't just summarize - it extracts the narratives that sell:
- Technology Innovation: What makes this different from the 10,000 other tokens
- Market Opportunity: The "why now" that gets people excited
- Team Credibility: Doxxed chads or based anons?
- Token Utility: Beyond "number go up" hopium
- Community Vibes: Diamond hands or paper hands waiting room?
Stage 2 - Style Transfer
This is where the magic happens. Pick any crypto influencer, and we'll teach our AI to write exactly like them. Not just similar - indistinguishable.
Influencer Analysis
We fetch their recent posts via (unofficial) Twitter API and analyze everything:
- Vocabulary: Do they say "bullish" or "mega bullish af"?
- Structure: Short punchy lines or long threads?
- Emoji Game: đ spam or subtle đ drops?
- Hashtag Strategy: #WAGMI or no tags at all?
- Engagement Hooks: Questions, calls to action, or pure hopium?
Style DNA Extraction
Our prompt engineering captures the essence of each influencer:
- Sentence length patterns
- Punctuation habits (lots of !!! or cool cucumber periods)
- Meme integration frequency
- Technical depth vs. vibes ratio
- Unique catchphrases and verbal tics
The AI doesn't just copy - it understands the underlying patterns that make their content work.
Generation Process
This is where both stages come together. The AI takes the positive project research from Stage 1 and filters it through the influencer's style patterns.
The result? Multiple post variations that sound exactly like your chosen influencer discovered your project and got genuinely excited about it. No hallucinations, no generic templates - just posts that could fool even the influencer themselves.
The Tech Stack
We kept it lean and mean. No over-engineering, just what gets the job done:
5hrs
Build Time
~500
Lines of Code
2
Stage Pipeline
â
Shill Potential
# Core Stack
- Python 3.12+ (async all the things)
- LiteLLM (Claude Sonnet 4.0 integration)
- Firecrawl API (web scraping that actually works)
- RapidAPI Twitter/X API (influencer post fetching)
- Streamlit (because we're not frontend devs)See It In Action
Ready to generate some fire posts? The demo is completely unrestricted. Input any project info, pick any influencer, and watch the magic happen.
Pre-loaded with examples like $VIRTUAL, $REI, and $TAO for quick testing. Or go wild with your own project.
Get the code for free on GitHub â