AI Agent

The core idea is simple: agents should not have to watch the market themselves. MemePerfect already provides the infrastructure needed to act as the continuous evaluation layer.

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The direction

Autonomous systems are good at deciding what to do next. They are usually not good at:

• continuous market scanning
• strategy state management
• reliable long-running monitoring
• delivering clean triggers at the right time

That is the layer MemePerfect already covers.

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What becomes possible

Developers can use MemePerfect as the part of the stack that:

• observes the market continuously
• evaluates conditions across strategies
• emits clear trigger events
• passes qualified opportunities into agents

In that model:

• MemePerfect handles observe + evaluate + trigger
• your agent handles act + learn

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Example workflow

Imagine an agent that only trades when a strategy passes strict conditions. The flow would look like this:

1. The strategy runs continuously inside MemePerfect.
2. MemePerfect detects a match.
3. A webhook or API event is sent to your agent.
4. The agent decides whether to buy, ignore, wait, or gather more context.

This is powerful because it lets the agent focus on decision-making instead of raw market monitoring.

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Why this matters

This turns MemePerfect into more than a dashboard. It becomes infrastructure developers can build on top of:

• for bots
• for trading systems
• for research pipelines
• for autonomous memecoin agents

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Today

The building blocks are already here:

• strategies
• continuous evaluation
• APIs
• webhook delivery

That means developers can already use MemePerfect as:

• the sensing layer
• the evaluation layer
• the trigger layer

while their own agents handle:

• decision-making
• execution
• feedback loops

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Agent skill file

MemePerfect publishes an agent-oriented skill file at:

• skill.md

Use this file as the contract for what an AI agent should assume about MemePerfect capabilities. It is designed to keep agents aligned with the public external API instead of UI-only behavior. Recommended usage:

1. Load skill.md first.
2. Use APIs and Strategy Rules Spec for full endpoint and payload details.
3. Use API Walkthrough for end-to-end execution flow.