> For the complete documentation index, see [llms.txt](https://docs.trustlogix.io/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.trustlogix.io/trust-ai/ai-agents/resources.md). # Resources Data that AI Agents and Applications can access are defined as "resources". ## Discoverable Resources AI Agents can access data via "resources". If TrustLogix doesn't currently support discovery/import for a desired resource, they can be manually configured in the console. {% hint style="warning" %} Currently, TrustLogix only supports automatic discovery of database objects in registered data accounts and data products across all data domains. \ \ Additionally, we offer 4 resource types out of the box (File, Folder, API, Data Product) that can be used to manually configure resources. {% endhint %} ## Custom Resource Creation * Custom resource types can be defined in the **Resources Type** tab. Resource types consist of name, description, attributes, and actions. * Once the resource type is created, it can be selected during the manual resource creation in the **Resource** tab. * Along with any custom resources created here, resources that TrustLogix discovers will be automatically selectable during policy creation in the **Access Policies** tab. See [Access Policies](/trust-ai/ai-agents/access-policies.md) for more details. --- # 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.trustlogix.io/trust-ai/ai-agents/resources.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.