# MOVE X AI Safety Audit
MarketMove uses BERT (developed by Google), GPT-3 (developed by OpenAI), along with our proprietary algorithms to show you exactly what each function in the contract does. The model was trained on more than 9,700 smart contracts and manually labeled. This way, we describe each function in a very simple language. The audit scans contracts for potential risk factors, which could result in a rug pull or honeypot. The engine includes a glossary of the most popular terms related to smart contracts. We don’t want you to solely rely on MarketMove. We want to teach you what honeypots are and how to spot them on your own.
The AI Safety Audit not only scans the contract but also highlights other important components to a project such as top holders, liquidity status, and fees associated with buy and sell transactions.
These additional features were requested by the MarketMove community since many projects without dangerous functions in their contract can still "pull the rug" on the project.
MarketMove’s AI Safety Audit is already the ultimate tool to verify all key aspects of a token on the Binance Smart Chain. With MOVE X’s cross-chain integration, the feature will be available for all tokens regardless of the native blockchain. This will even further increase the viral potential of MOVE X and the MOVE token. Both investors and developers use the AI Safety Audit as proof of legitimacy and share it across various social media platforms.
---
# 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://marketmove.gitbook.io/marketmove/move-x-platform/move-x-ai-safety-audit.md?ask=
```
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.