> For the complete documentation index, see [llms.txt](https://docs.lleverage.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.lleverage.ai/administer-and-govern/control/connections/google-docs.md). # Google Docs Google Docs integration in Lleverage connects your workflows and agents to your documents, so they can create and edit docs, pull content out for processing, and export finished documents automatically. ### How to Connect 1. **Go to Control → Connections** in your project 2. **Pick Google Docs** from the list of apps 3. **Choose which actions** the connection should allow and who should have access (shared or personal) 4. **Choose "Connect Now"** and sign in with Google, or send an authentication link so a colleague can connect on your behalf ### What Google Docs Can Do * **Creating and finding** - create new documents and find existing ones * **Reading** - retrieve a document's details and its full content * **Editing** - append content, insert text at a position, and replace text throughout a document * **Exporting** - export a document to other formats for sharing or storage > 💡 **Use case**: Generate a report from workflow data, fill in a template by replacing placeholder text, or pull a document's content into an AI step for summarising. ### Important Considerations * The connection works with documents the signed-in Google account can access * Replace text is handy for template-style documents: keep placeholders in the doc and let the workflow fill them in --- # 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.lleverage.ai/administer-and-govern/control/connections/google-docs.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.