Get to know Rovo
Write instructions for your Rovo Agent
Instructions are used when creating (or editing) an Agent to customize it to your needs. They define things like:
The expectations or the purpose of your Agent.
The limitations - what you’d like the Agent to do and not do.
How the Agent might respond to various inputs (for example, when asked a specific thing, it should reply in a specific way).
How the Agent should interact with people (for example, you may want your Agent to have a particular tone - like “always respond like a pirate”).
If you’re looking for tips on chatting with Agents and the kinds of prompts you’d write day-to-day, see Chat to an Agent.
Tips and best practices
Writing good instructions is an art, and you’ll most likely need to iterate on your instructions a few times to get your Agent working just right.
To make your instructions more effective:
Keep your instructions relatively short to start with
Shorter prompts are easier to iterate on (you can track how small changes to the prompt improve or worsen the Agent’s performance). It can be harder to troubleshoot or iterate on a longer prompt.
Agents should tackle specific jobs, so longer prompts with too many instructions can lead to inconsistent outputs. This is because, rather than actioning the full list of instructions, the Agent will choose parts to prioritize.
Provide a role, tasks, and the relevant context to completing that job
Role: The Agent’s role is the name for the job you’re giving them. For example, if you’re making an Agent to help you make decisions on projects, you might say:
“You are a project manager who’s great at making unbiased decisions.”Job: Jobs can be written as one or multiple scenarios where you expect your Agent can help people. To use the previous example, you might say:
“You have the following jobs: Reviewing an existing decision, Finding related decisions, Providing additional resources or best practices to help with effective decision making.”Context: This is where you can choose to go very detailed, or keep it light. Context is essentially any extra detail you think your Agent might need to deliver on its jobs. Context could include referencing the Agent's knowledge or actions, and giving specific examples with example outputs.
Examples
The examples below are a great place to start but it’s important to know that sometimes more advanced instructions will have much longer, more detailed prompts.
Agent use case | Example instructions |
---|---|
Atlassian Rovo Support Agent | You are an expert research Agent that is great at finding answers to user questions. You help the user with the following tasks:
Use the attached Confluence space to find answers to the user's questions. If you cannot find anything, tell the user you were unable to find an answer. When the user wants explanations to AI or ML concepts, explain the topics in simple language that a non-technical user can easily understand. When a technical term is encountered, give the user an explanation of what it means. Atlassian Rovo is a new AI product by Atlassian. It includes Rovo Agents, autonomous AI teammates that help users automate workflows, take action across Atlassian products, and accelerate work. You will help the user find answers to questions on Rovo. Potential topics include:
|
Team Onboarding Buddy | You are a member of the Atlassian Rovo Search team and help new teammates onboard to the team. You are friendly and are able to translate company jargon into language any newcomer can understand. You help users walk through the team onboarding process and answer any questions they might have on the team, rituals, necessary software, and sharing general company knowledge. The Atlassian Rovo Search team works on building and improving the Rovo search experience for Atlassian customers. Use the attached Confluence space to search for onboarding guides and documentation that will help answer the user's questions. Always assume that the user does not have any context on the team, technology used, or people to interact with. |
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