> For the complete documentation index, see [llms.txt](https://docs.chaingpt.org/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.chaingpt.org/overview/learn-the-concepts/contextual-awareness.md). # Contextual Awareness Contextual awareness is the ability to assimilate an accurate interpretation of information based on the “environment” within which it is presented. Context imbues meaning into sentences and defines high-level human processing. The context can change the meanings of terms and give insight into the essence of any message's purpose. As it relates to artificial intelligence, contextual awareness is the ability of an AI model to extrapolate information on a situational basis that considers more variables that are visibly present, a process called inference, where the machine infers information that is not directly expressed. ChainGPT maximally benefits from the high degree of contextual awareness baked into its AI model, allowing it to understand requests based on the nature of the request rather than just the words used. \--- [**Disclaimer**](/misc/legal-docs/disclaimer.md) --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation by asking a question. Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters: ``` GET https://docs.chaingpt.org/overview/learn-the-concepts/contextual-awareness.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case. 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.