Knowledge sources for Rovo agent scenarios
An agent’s scenario contains the trigger, instructions, knowledge, and skills that guide it in specific situations.
Knowledge is effectively all the source information the agent can use to answer user prompts. Knowledge can include links to Confluence and Jira spaces, individual pages, Google Drive workspaces, and other relevant resources.
No matter the knowledge source, agent’s won’t return answers with information from sources the user doesn’t have clearance to view. It respects the permissions of the user who prompted it because it is acting on their behalf.
Configure knowledge scope
Every agent has access to all organizational knowledge unless you configure it differently. This constitutes all of the organization-wide resources that your org administrators have connected via Teamwork Graph and Rovo.
You can also choose to toggle on web search, which allows the agent to search public websites for information. This is either in lieu of organizational knowledge or in addition to the scope you define.
To configure the knowledge scope of an agent’s scenario:
Add or select a scenario
Scroll down to the Knowledge block
Select one the following:
All organizational knowledge (everything the organization allows)
Custom knowledge (specific resources you choose)
No organizational knowledge
(optional) Toggle on Web search
Add custom knowledge
If you configure an agent with custom knowledge, you narrow the scope of knowledge by specifying which resources it should look at. Although this may sound limiting, it can make responses more accurate and helpful by focusing the agent on information most relevant to skills it was built to perform.
To add custom knowledge sources to an agent’s scenario:
Select Custom knowledge
Select the Add knowledge button
Select the checkboxes of sources you want your agent to access
Select Add
(optional) Toggle on Deep research mode
If you select Confluence, Jira, or Jira Service Management, you can focus the scope even further to specific spaces — or to a specific branch in a Confluence content tree.
Selecting the Select content under option for Confluence let’s you search for parent content and add it along with all its child content items.
Deep research mode
When you customize agent knowledge, you can also enable Deep research mode to enhance how your agent “thinks” about that information. This mode is most useful in special scenarios where your agent needs to conduct heavyweight evidence-based research.
It’s similar to selecting Deep research mode in Rovo Chat, effectively turning your agent into a research assistant. It considers user prompts more broadly and deeply — and it responds with comprehensive reports that follow the formatting, tone, and structure you outline in the agent instructions.
You can’t add Deep research to the Default scenario because research mode is an exception to be triggered when deeper thinking is warranted.
Considerations for Deep research
By tying an agent’s research capability to specific custom scenarios, you control which questions trigger this mode, but the agent will respond in Deep research mode any time a user’s prompt triggers that scenario. This differs from Rovo Chat, where users select the mode as part of their prompt.
Agents with deep research–enabled scenarios can also be triggered in automations, allowing agents to generate in-depth research reports as part of automated workflows or scheduled processes.
However, before you add Deep research, consider this:
Deep research mode takes longer to respond — up to 15 minutes — while it analyzes and compiles an in-depth report
Automation currently times out after 15-minutes, so if deep research runs for longer the automation will fail
Each user or automation is limited to 30 deep research requests a day
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