# Glossary * **AI Agent**: The autonomous system that powers SAG3, capable of performing research, analysis, and generating insights without human intervention. * **Analysis**: A comprehensive evaluation of a crypto project covering multiple aspects. * **Attributes**: The six main categories used to score a project (Fundamentals, Tokenomics, Decentralization, Market Position, Risk Profile, Community). * **Chain of Thought (CoT)**: A reasoning process used by the AI to work through complex problems step-by-step before arriving at conclusions. * **Community**: The group of users, holders, and contributors around a project. * **Decentralization**: The degree to which a project distributes control and decision-making across its network. * **Engagement**: Metrics measuring how users interact with content, including likes, retweets, comments, and shares. * **Fundamentals**: Core aspects of a project like team, technology, use case, and roadmap. * **Impressions**: The number of times content is displayed to users, regardless of whether they interact with it. * **Inference**: The process and time taken for an AI model to generate output. * **Market Position**: How a project compares to competitors and its standing in the market. * **Overall Score**: A weighted average of all attribute scores on a scale of 0-10. * **Research Report**: The raw data collected about a project before analysis. * **Risk Profile**: Assessment of potential risks associated with a project. * **RWA**: Real World Assets - physical assets represented on blockchain. * **SAG3 Chat Core**: The interactive chat interface that allows users to ask questions about analyses. * **Sentiment Analysis**: Evaluation of social media and community feelings about a project. * **Technical Analysis**: Evaluation of the project's technical architecture and implementation. * **Tokenomics**: The economic model of a cryptocurrency token, including distribution, utility, and incentive mechanisms. --- # 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.sag3.ai/getting-started/glossary.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.