Introduction: A Faster Way to Build Jira Reports
If you’ve ever searched the Atlassian Community for “how to create a custom Jira report,” you’ve likely seen the same pattern. Jira’s native reports are useful, but they work very well for basic sprint tracking. While Jira teams need:
- cross-project visibility
- executive-ready dashboards
- custom metrics or logic
- reusable reporting workflows
Then things get complicated. Traditionally, there are a few options:
- export data to Excel,
- combine multiple Jira reports manually,
- install and configure multiple plugins,
- or ask developers to build a custom Jira app.
Today, there’s a more direct approach. AI Apps Builder for Jira is a no-code builder that allows users to build Jira apps, dashboards, and reports from a simple prompt.
This article walks through five high-value Jira custom reports you can create in minutes, along with practical prompts and use cases.
What Is AI Apps Builder for Jira
AI Apps Builder for Jira is an AI-powered tool that simplifies how teams create custom Jira functionality. With this tool, instead of writing code, you:
- Describe your idea in plain language
- The AI generates a complete Forge app
- You deploy it directly in Jira Cloud
What AI gets generated
| Component | Included |
|---|---|
| UI (gadgets, panels, dashboards) | ✅ |
| Business logic | ✅ |
| Data queries | ✅ |
| Permissions (Forge-based) | ✅ |
| Deployment-ready app | ✅ |
This allows business users, such as PMs, Product Owners, and Team Leads, to generate their own apps without knowledge of Forge or JavaScript.
Why Teams Look for Custom Jira Reports
Before diving into examples, it’s worth understanding why these reports are so frequently requested. Most Jira users are trying to answer simple but critical questions:
- Are we on track this sprint?
- What is slowing us down?
- Where are the risks?
- How is performance trending?
- Who is overloaded?
Jira contains this data, but not always in a form that’s easy to consume. That’s why teams end up:
- rebuilding reports every week
- switching between dashboards and filters
- exporting data for analysis
- relying on manual interpretation.
A custom dashboard in Jira solves this, but building one traditionally is time-consuming.
Team Performance (Velocity Trend) Report
Velocity is one of the most important planning signals in Agile teams. But Jira’s default Velocity Chart:
- is limited to a single board
- lacks trend analysis
- doesn’t provide long-term comparison.
Example AI prompt
Build a dashboard gadget to analyze our team’s performance across sprints. Show a velocity trend chart for the last 3 sprints, plotting story points committed versus completed in each sprint. Calculate and display the average velocity over this period, and include a trend line or percentage change to highlight improvements or declines in velocity.
What this report includes
- Committed vs. completed story points
- Velocity trend across sprints
- Average velocity
- Performance trend indicators.
This report supports:
- better sprint planning
- realistic forecasting
- identifying overcommitment patterns.
Sprint Health & Progress Report
Project managers need a clear snapshot of sprint status, especially for stakeholder updates. They typically want:
- planned vs. completed work
- a burndown chart
- time remaining
- a clear “on track / at risk / delayed” indicator.
Jira’s default Sprint Report provides part of this, but it’s not flexible enough for tailored reporting.
Example AI prompt
Create a dashboard gadget that shows the sprint health and progress. Add dropdowns to filter by project and by sprint. Include a burndown chart of remaining story points vs. time, a summary of committed vs. completed issues, and the number of days left in the sprint. Indicate whether the sprint is on track or delayed with color-coded status (green for on-track, yellow for at-risk, red for behind schedule).
- Burndown chart (story points vs. time)
- Summary of committed vs. completed work
- Days remaining in sprint
- Color-coded health status.
High-Risk Issues Tracker
Teams often struggle to answer: “What should we worry about right now?” Jira can show flagged or overdue issues, but not always in one consolidated, actionable view.
Example AI prompt
Generate a dashboard gadget that lists all unresolved issues in my project which are high-risk. Define high-risk as any issue that is either flagged (marked as impediment) or has a due date that is past due or coming up within the next 7 days. For each issue, display the issue key, summary, assignee, priority, and how many days it’s overdue or until due. Highlight overdue issues in red and issues due soon in yellow.
- Flagged (impediment) issues
- Overdue issues
- Issues due soon (e.g., next 7 days)
- Visual highlighting for urgency
This becomes a daily operational dashboard for standups or stakeholder syncs. It reduces the need to manually combine filters or track risks across multiple views.
Workload Usage Report
Jira tracks worklogs, but it’s difficult to answer: “Who is overloaded across all projects?” Worklog data is often fragmented across issues, boards, and filters.
What this report includes
- Total hours logged per user
- Date range filtering
- Project and assignee filters
- Drill down into issue-level details.
Example AI prompt
Create a “Workload Usage” dashboard gadget that shows total hours logged per user within a selected date range. Add multi-select filters for project and assignee, and show only users who logged time in the selected period. When I click a user, open a table with issue key, summary, and hours logged for each issue.
This report helps teams:
- identify workload imbalance
- support resource planning
- replace manual Excel analysis.
Cycle Time Tracker
Cycle time is critical for understanding delivery speed. But Jira’s Control Chart:
- is board-specific
- focuses on visualization
- doesn’t provide a structured table view.
Example AI prompt
Create a “Cycle Time Tracker” dashboard gadget. Add a dropdown to select a project. For the selected project, show a summary with total issues, number of issues with cycle time, and average cycle time in days. Below, list all issues in a table with columns: key, summary, issue type, status, cycle time from “In Progress” to “Done.”
- Project-level cycle time data
- Summary metrics (total issues, average cycle time)
- Issue-level breakdown.
This report allows teams to:
- compare delivery speed across issues
- identify outliers
- improve workflow efficiency.
How to Build a Custom Jira App with AI (Step-by-Step)
If you’re wondering how to build your own Jira app without coding, here’s the short answer:
Step-by-step workflow
- Install AI Apps Builder from Atlassian Marketplace
- Open the app in Jira Cloud
- Start a new conversation
- Describe your report or app idea
- The system generates a Forge app
- Deploy it to your Jira instance
No coding, no manual configuration.
From Idea to Jira App in Minutes
Custom Jira reporting has traditionally required time, technical knowledge, or workarounds. AI Apps Builder simplifies this process. If you want to build your own custom Jira reports, install AI Apps Builder for Jira from the Atlassian Marketplace and let AI generate the report that exactly meets your needs.
