# Agent Autonomy

Example:

* You say: “Analyze the liquidity of aixrp and execute a trade if slippage is under 1%.”
* The agent:
  1. Checks the liquidity pool.
  2. Calculates slippage.
  3. Executes the trade if conditions are met.
  4. Confirms results back to you.

No need to run tools step by step, the agent handles the workflow.

***

### **Real-World Scenarios**

1. **Trading**
   * “Sell 50% of the aixrp in your agent wallet if the price has dropped 5% or more over the last hour.”
   * The agent monitors markets, executes automatically, and reports the outcome.
2. **Dapp Usage**
   * “Deposit 20 XRP into the platform with the highest XRP yield right now from; Doppler, Strobe, or MoreMarkets”
   * The agent checks current yield on selected Dapps, deposits according to the user's intent, and then provides onchain verification upon successful deposit.
3. **Blockchain Exploration**
   * “Which memecoins have the highest number of tokens being sold onto the DEX by their issuing addresses?”
   * The agent uses the indexer to find relevant onchain data and processes it into a digestible response message to the user.
4. **Research & Analysis**
   * “Highlight and analyze the top three XRPL tokens based on price increase over the last 7 days.”
   * The agent pulls data from the indexer, analyzes it, and delivers a concise report.

***

### **Why It’s Better Than Traditional UI**

Traditional DEX workflows:

* Navigate to site → Connect wallet → Find pool → Analyze Data → Execute trade.

With aigent.run:

* You just say: **“Swap 500 RLUSD into XRP at best rate.”**
* The agent does all of the above instantly.

This is **faster, more intuitive, and more accessible** for both power users and newcomers.


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# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://docs.aigent.run/ai-agent-terminal/agent-autonomy.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.