> 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/agent/session-workspace.md). # Session workspace Use the Agent session workspace to follow work, provide input and inspect the result. A session keeps one piece of Agent work together: the conversation, visible activity, files, questions, feedback and result. The exact controls can vary with your Project access and the capabilities available to the session. ## Conversation and activity The centre of the session can contain: * your messages and the Agent's replies; * expandable activity while the Agent works; * a run timer and stop control while work is live; * questions or choices that need your input; * files, cards and other outputs; * the final result. Activity helps you understand the route the Agent took. The resulting business-system state or output remains the strongest proof of what actually happened. ![A live Agent session with the activity steps visible while the task is still running.](https://3370306531-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FlgSglJDQZxDZdn20CUcl%2Fuploads%2FldjCMsZZYm3w6bM3h5p1%2Fsession-in-progress.png?alt=media) ## The composer Use the composer to: * type your next instruction; * attach files; * use speech-to-text dictation; * invoke an available Skill explicitly with **/skill**; * choose from model options available to you; * answer when the Agent is waiting for input. Dictation prepares a text message that you can review before sending. It is separate from Call with Agent. ## Questions and choices The Agent can pause with a structured question when it needs information or judgement. A question can contain selectable options and a free-text answer. **Skip** means you are choosing not to provide that input and allowing the Agent to continue with what it already knows; that is different from rejecting a required approval. An Agent question is part of the current task. It is different from a Workflow Request assigned through the Request Inbox. ![A structured Agent question with selectable options and room for a free-text answer.](https://3370306531-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FlgSglJDQZxDZdn20CUcl%2Fuploads%2FTFydb6Dhqo1mdRYNiHsu%2Fagent-question-options.png?alt=media) ## Files and outputs Files created or used during the task can appear directly in the conversation and in the session's Files view. Supported files can open in an inline preview. Open important outputs and inspect them directly. A file appearing in a session does not automatically make it maintained Project knowledge or a system of record. See Working with files. ## Progress, Context and Memory For longer work, the right-hand rail can show supporting views around the task. * **Progress** gives a compact view of the run. It is useful for following work, not proof that every downstream action completed. * **Context** helps show tools and referenced material around the session. An empty Context view is not proof that nothing contributed. * **Memory** shows persistent context that may contribute beyond the current conversation. Remembered information is useful context, not automatically the authoritative business record. See [What the Agent can use](/run-operations/agent/agent-context.md). ## Give feedback on a response or the whole session Use **response feedback** when your judgement is about one specific completed answer. Responses can show **How was this response?** with thumbs up, thumbs down and an optional comment. Use **session outcome feedback** when your judgement is about the piece of work as a whole. You can return later to edit or remove your own session feedback. ![The Agent session feedback dialog in production.](https://3370306531-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FlgSglJDQZxDZdn20CUcl%2Fuploads%2Fx1xLAXdsxQsFcrNsXJJY%2Fagent-session-feedback-dialog.png?alt=media) Feedback records human judgement of the result. It does **not** rewrite technical execution status. A technically successful run can still be a bad business outcome. Authorised builders can review response and session feedback alongside execution evidence in [Monitoring](/build-and-improve/monitoring.md). ## Failed turns can be retried A persisted failed Agent response can expose **Retry**, letting you regenerate from the failed point instead of reconstructing the conversation manually. Use Retry for a failed turn. If the same underlying problem keeps recurring, fix the relevant Skill, Connection, context or execution path rather than normalising repeated retries. ## Use the workspace as evidence, not the system of record For important work, verify in this order: 1. the actual business-system result or required post-condition; 2. produced files, records and other concrete outputs; 3. visible Agent activity and the sources it used; 4. Monitoring or Activity evidence where deeper inspection is needed; 5. the session rail as supporting context. The workspace makes Agent work inspectable. It does not replace the systems that own operational truth. --- # 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/agent/session-workspace.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.