Work with Jira Delivery agent
Jira Delivery Agent is a Rovo agent designed to automatically monitor and report on progress by analyzing the state of your Jira spaces, tasks, and connected data. This agent identifies risks, such as stale work, blocked items, or slipping deadlines, and produces tailored delivery artefacts for different audiences, including team stand ups and executive summaries.
Like other out-of-the-box Rovo agents, you can chat with Jira Delivery Agent and it will generate responses based on your prompts. In addition, this agent can be used within automation rules, so you can create a recurring, zero-effort delivery loop for your spaces.
To trigger the automation mode, add “Automation Mode” at the beginning of your prompt. You’ll be able to use the agent’s response directly within the automation rule.
自動化ルール内でエージェントを使用する方法の詳細をご確認ください。
Delivery health check
Manually evaluating the structural health of a space is time-consuming. Jira Delivery Agent provides a holistic evaluation of a Jira space by assessing overdue items, work due soon and stalled tasks. It also reviews ways-of-working, such as the use of story points and priority fields, to suggest improvements.
Stakeholder status updates
Assembling status updates for different audiences requires synthesising raw work item data into a narrative. Jira Delivery Agent generates end-of-cycle summaries of completed work that are themed and risk-aware. You can configure the output for different audiences, such as a concise team summary or a high-level executive update.
デイリー スタンドアップ ミーティング
Keeping track of daily progress across all work items can be difficult for management and teams. Jira Delivery Agent creates a daily status digest that documents the current state of work. This provides a consistent reference for the team's daily rituals and helps track progress over time.
Stale work follow-up
When work stalls mid-cycle, it often requires a manual sweep to notice. Jira Delivery Agent detects work items that haven't moved for a specified period and automatically follows up with assignees. This ensures projects keep moving and risks are surfaced early without manual chasing.
Start and use Jira Delivery agent
Find out how to access Rovo Chat, select Jira Delivery Agent, and unlock newer ways of improving efficiency:
どうやって | 記事の URL |
|---|---|
Rovo チャットを開始する | |
Select Jira Delivery Agent from a list of Rovo agents | |
Chat with Jira Delivery Agent | |
Use Jira Delivery Agent in Automation |
会話のきっかけ
サービス トリアージでは、開始に役立つ 3 つの会話のきっかけを紹介しています。これらのいずれかを使用することも、独自のプロンプトを使用することもできます。
What's gone stale in this space?
how healthy is this space?
write me a status update for stakeholders?
These prompts perform better when you specify the space key or work item url.
ツール
Tools are how Jira Delivery Agent accesses the data it needs to analyze your delivery state. jira delivery agent uses the following tools:
ツール | 説明 |
|---|---|
get work item | Fetch a specific Jira work item. |
search with jql | Search jira using a Jira Query Language (JQL) expression. |
get work-item context in twg | Retrieve comprehensive context for a Jira work item, including related pull requests, commits, branches, pages, and hierarchy from the teamwork graph. |
get team's projects | Fetch the projects linked to a team, including goals and epics, within a specific date range. |
get page | Retrieve a Confluence page. |
get changelog | Fetch the changelog for a Jira work item to see its history. |
get work summary for given user in twg | Return a summary of a single user's activity, including assigned work items, Confluence pages, pull requests, Loom videos, and Atlas projects or goals. |
get project context | Fetch Atlassian project, epic, or goal context, including details, members, and owners. |
find similar work items | Find work items with a similar summary within a Jira space. |
カスタム Rovo エージェントに対する指示の記述方法をご確認ください。
Though Jira Delivery Agent is accessible across the Atlassian platform, it generates higher-quality output when analyzing delivery data, progress risks, and project rituals within Jira. The agent also continuously learns from your project's transitions and comment activity to improve its risk identification over time. we recommend reviewing the agent's summaries regularly and using the thumbs-up (👍) or thumbs-down (👎) icons to provide feedback to enhance its accuracy and usefulness.
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