> 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/run-operations.md). # Run operations - [Run operations](https://docs.lleverage.ai/run-operations/overview.md): Use Lleverage to carry operational work forward, respond when your judgement is needed, and verify what happened. - [Project overview](https://docs.lleverage.ai/run-operations/overview/project-dashboard.md): Use the project overview to understand the operational area, current work and capabilities available in a Lleverage project. - [Project navigation](https://docs.lleverage.ai/run-operations/overview/navigation.md): Find the right Lleverage surface from the operational situation you are dealing with. - [Agent](https://docs.lleverage.ai/run-operations/agent.md): Use the Agent for flexible operational work across conversations, files and business systems. - [Use the Agent](https://docs.lleverage.ai/run-operations/agent/getting-started.md): Run a useful first task with the Agent and learn the operating pattern you can reuse later. - [Agent task examples](https://docs.lleverage.ai/run-operations/agent/examples.md): See representative Agent tasks in operational terms: the outcome, evidence, human boundary and result. - [Session workspace](https://docs.lleverage.ai/run-operations/agent/session-workspace.md): Use the Agent session workspace to follow work, provide input and inspect the result. - [Call with Agent](https://docs.lleverage.ai/run-operations/agent/call-with-agent.md): Use Call with Agent for a live voice conversation during operational work. - [Sessions and continuity](https://docs.lleverage.ai/run-operations/agent/chat-and-sessions.md): Know when to continue an Agent session and when to start a new one. - [Agent usage guidelines](https://docs.lleverage.ai/run-operations/agent/tips-and-best-practices.md): Practical habits for getting dependable operational work from the Agent. - [Agent context and tools](https://docs.lleverage.ai/run-operations/agent/agent-context.md): Understand the main sources and capabilities the Agent can use during a task. - [Skills](https://docs.lleverage.ai/run-operations/agent/agent-context/skills.md): Understand how Skills give the Agent reusable ways of doing recurring work. - [Use Skills](https://docs.lleverage.ai/run-operations/agent/agent-context/skills/using-skills.md): Use Skills when you want the Agent to follow a reusable way of doing a job. - [Files](https://docs.lleverage.ai/run-operations/agent/agent-context/file-handling.md): Use files as Agent inputs, evidence and outputs, and understand where session files fit relative to durable Project knowledge. - [Connected systems](https://docs.lleverage.ai/run-operations/agent/agent-context/integrations.md): Understand how the Agent uses authorised Connections to work with external business systems. - [Knowledge](https://docs.lleverage.ai/run-operations/agent/agent-context/knowledge-bases.md): Understand how maintained reference material gives the Agent organisation- specific knowledge. - [Memory](https://docs.lleverage.ai/run-operations/agent/agent-context/memory.md): Understand how Memory carries useful context across Agent sessions. - [Permissions and approvals](https://docs.lleverage.ai/run-operations/agent/agent-context/access-and-approvals.md): Understand what gives the Agent authority to act and where approval is required. - [Agent in Slack](https://docs.lleverage.ai/run-operations/agent/agent-in-slack.md): Work with the Lleverage Agent from Slack when your organisation has connected the Channel. - [Agent in Microsoft Teams](https://docs.lleverage.ai/run-operations/agent/agent-in-microsoft-teams.md): Work with the Lleverage Agent from Microsoft Teams when your organisation has installed the app. - [Agent FAQ](https://docs.lleverage.ai/run-operations/agent/agent-faq.md): Answers to common questions about using, trusting and configuring the Lleverage Agent. - [Everyday use](https://docs.lleverage.ai/run-operations/agent/agent-faq/everyday-use.md): Common questions about everyday Agent use. - [Context, memory and learning](https://docs.lleverage.ai/run-operations/agent/agent-faq/context-memory-and-learning.md): Common questions about Agent context, Memory and learning. - [Access and permissions](https://docs.lleverage.ai/run-operations/agent/agent-faq/access-control-and-trust.md): Common questions about Agent access, permissions, approvals and trust. - [Building and automation](https://docs.lleverage.ai/run-operations/agent/agent-faq/building-and-automation.md): Common questions about building Skills and turning Agent work into automation. - [Workflow apps](https://docs.lleverage.ai/run-operations/workflow-apps.md): Use published Workflow apps to complete structured operational work without opening the Workflow builder. - [Requests](https://docs.lleverage.ai/run-operations/request-inbox.md): Handle the points in running operational processes where a person must decide, supply missing information or take responsibility for an exception. --- # 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/run-operations.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. 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