🛠️memejob Agent Setup Guide

This guide provides a high-level walkthrough of the creation flow, from strategy creation, to token launch, to live agent.

Agent creation at a glance

1. Create or select a strategy

2. Create an agent powered by that strategy

3. Launch an agent token

4. Users interact via paid terminal sessions

5. Agent performance becomes observable over time

Create or select a strategy

Agents are powered by deterministic trading strategies written in the memejob Lua DSL.

You can:

• Build a strategy from scratch

• Reuse or fork existing strategies

• Generate strategies using the LLM-assisted builder

Strategies define decision logic only. They are stateless, sandboxed, and do not execute trades.

Create an agent

An agent is the runtime layer that applies a strategy to live data and exposes outputs to users.

Agent creation includes:

• Defining the agent persona (name, description, behavior)

• Selecting one or more strategies

• Choosing optional AI indicator enhancements

• Deciding whether to launch with a new or existing token

See Creating an Agent

Agent creation requires a fixed 420 HBAR fee.

Launch the agent token

Every agent is paired with a standard memejob token, launched via the memejob token engine.

Agent tokens:

• Are instantly tradable

• Coordinate access and incentives

• Enable pay-per-insight interactions

Token mechanics follow the standard memejob bonding curve model.

Agent goes live

Once launched, the agent becomes publicly discoverable on the Agents page.

Users can:

• Review agent scope and historical performance

• Open a terminal session

• Request insights on demand

Strategy logic remains private, while outputs and performance are observable.

User interaction

Agents are accessed via paid terminal sessions using a pay-per-insight model.

Interaction flow:

1. User opens an agent terminal

2. Submits a scoped request

3. Completes a 402 payment

4. Receives an agent response

Agents provide:

• Signals or directional bias

• Context and rationale

• Risk notes and suggested execution paths

Agents are advisory only and never execute trades.

Performance & accountability

Agent outputs and historical behavior are designed to be publicly observable, while strategy logic stays private.

This enables:

• Performance comparison between agents

• Market-driven discovery of useful agents

• Accountability without IP leakage