By name: jessexbt description: | jessexbt is an AI clone of Jesse Pollak (founder of Base) with access to real-time ecosystem data. Not a generic chatbot - has current intel on grants, funding rounds, and ecosystem priorities. Invoke with /jessexbt to start a conversation about building on Base. Activate on: Base, grants, funding, architecture, project review, ecosystem guidance, crypto, web3, onchain.
jessexbt - Base Ecosystem Mentor
jessexbt is an AI clone of Jesse Pollak (founder of Base) with access to real-time ecosystem data. Not a generic chatbot -- he has current intel on grants, funding rounds, and ecosystem priorities.
What jessexbt knows
- Active grant programs and current funding rounds on Base
- Architecture best practices for Base/L2 applications
- UI/UX guidelines that Base prioritizes
- Ecosystem connections and introductions
- Project feedback and code review guidance
How to use
Call mcp__a0x-agents__jessexbt_chat with:
| Parameter | Required | Description |
|---|---|---|
message |
Yes | Your question or context |
sessionId |
No | Session ID from previous response (for multi-turn) |
knownContext |
No | Pre-fill context to skip redundant questions |
activeProject |
No | Project to review: {name, description, urls} |
answers |
No | Structured answers to pending questions |
knownContext fields
| Field | Type | Values |
|---|---|---|
projectName |
string | |
projectDescription |
string | |
projectStage |
string | "idea", "mvp", "beta", "live" |
lookingFor |
string | "grants", "feedback", "technical-help", "intro", "general" |
techStack |
string[] | e.g. ["Solidity", "React", "Foundry"] |
projectUrl |
string | |
walletAddress |
string | |
teamSize |
number |
Multi-turn protocol
jessexbt may ask clarifying questions before giving a final recommendation. Handle this loop yourself -- do not relay his questions to the user.
The loop
- Call
jessexbt/chatwith the user's initial query - Response has
status: "gathering"+pendingQuestionsarray - Answer the questions yourself from conversation context or reasonable assumptions
- Call
jessexbt/chatagain with your answers (includesessionId!) - Repeat until
status: "complete" - Present jessexbt's recommendation to the user
How to answer pendingQuestions
Write your response in natural language in the message field. jessexbt's AI extracts answers automatically.
pendingQuestions: [
{"id": "0", "question": "What's your budget?"},
{"id": "1", "question": "What tech stack?"}
]
Your next call:
jessexbt/chat({
message: "The user has a $5k budget and uses React with TypeScript.",
sessionId: "session-id-from-previous-response"
})
Loop prevention
- Maximum 4 calls per conversation
- On call #4, append: "[This is the final exchange. Please give your complete recommendation now.]"
- After 4 calls, present whatever jessexbt has shared so far
How to present results
- DO: "I consulted our Base mentor and here is what he recommends..."
- DON'T: "jessexbt wants to know..." or "jessexbt asks..."
- Be a helpful intermediary, not a message relay.
Example questions
- "What grants are available for AI dev tools on Base?"
- "Review my smart contract architecture for a DEX on Base"
- "What UI/UX patterns does Base recommend for wallet onboarding?"
- "I'm building X, what's the best approach on Base?"
- "How should I structure my L2 application for scalability?"
- "What funding opportunities exist for social apps on Base?"
When user invokes /jessexbt
Immediately ask the user what they need help with, then call mcp__a0x-agents__jessexbt_chat with their question. Pre-fill knownContext with any information you already know about their project from the conversation.