AI-Powered Jira Sprint Review Tool (for "KIK" Project)

An application that analyzes Jira sprint data for a specific project (currently hardcoded to "KIK") and generates an AI-powered review of the sprint's progress in Japanese. This tool is aimed at project managers, scrum masters, and development teams to help them understand sprint dynamics and identify areas for improvement.

Features

• AI-Powered Sprint Review (in Japanese):

  • Generates a comprehensive sprint review using the OpenAI API (gpt-4.1 model).
  • The review is provided in Markdown format and displayed using the SummaryCard.tsx component.
  • Review Coverage (based on system prompt in src/app/api/review/route.ts):
    • Overall progress: Total ticket counts, progress by status (completed, in-progress, to-do) with counts and percentages.
    • Progress per assignee: Ticket counts and progress for each assignee.
    • Task concentration: Identifies if tasks are concentrated on specific members or if there are unassigned tickets.
    • Stale tickets: Pinpoints tickets that have not been updated for a certain period.
    • Work balance: Assesses the distribution of work among team members.
    • Recommended next actions: Suggests adjustments for the team based on the analysis.

• Jira Integration:

  • Fetches issues from open sprints for a specific Jira project (currently hardcoded to "KIK"). This includes fields like issue key, summary, status, assignee, created, and updated dates.
  • Sprint Selection & Review: The SprintTab component allows users to select a specific sprint, which then triggers the AI review generation for that sprint.
  • Employee-Specific View: The EmployeeTab component enables viewing issues assigned to a particular employee, visualized with a bar chart (IssueBarChartByEmployee.tsx) showing issue counts by status.
  • Data Visualization: Includes various charts for visualizing issue distributions and sprint progress, such as IssueChart.tsx (e.g., overall issue status distribution) and IssuesPieChart.tsx (e.g., issue distribution by assignee or status).

Technologies Used

• Frontend:
  • Next.js (v15.3.1)
  • TypeScript
  • Tailwind CSS
  • Zustand (for state management)
  • Chart.js/Recharts (for data visualization)
• Backend & Services:
  • OpenAI API (using the gpt-4.1 model for the AI review)
  • Jira API (using jira.js)
  • Supabase (for backend services like database and authentication)

Important Notes / Limitations

• Hardcoded Jira Project Key: The Jira project key is currently hardcoded as "KIK" in several API routes, including:
  • src/app/api/issues/route.ts
  • src/app/api/review/route.ts
  • src/app/api/issues/[employeeName]/route.ts
  • src/app/api/sprint/route.ts Users must modify this key in these files to point to their own Jira project.
• JQL Queries: The JQL queries (e.g., project = KIK AND sprint in openSprints()) used to fetch Jira data are specific to this hardcoded project. Users may need to adjust these queries based on their Jira project setup and desired filtering.
• AI Review Language: The AI-generated sprint review is currently configured to be in Japanese.

Getting Started / Setup Instructions

Prerequisites

• Node.js (v18.x or later recommended)
• npm or yarn

Setup

1. Clone the repository:

   git clone <repository-url>
   cd <repository-name>

2. Install dependencies:

   npm install
   # or
   yarn install

3. Set up environment variables: Create a .env.local file in the root of your project and add the following environment variables. You can copy the .env.local.example file (if provided) to get started.

   # OpenAI API Key
   OPENAI_API_KEY=your_openai_api_key
   
   # Jira Configuration
   JIRA_HOST=your_jira_instance_url # e.g., https://your-domain.atlassian.net
   JIRA_USERNAME=your_jira_email
   JIRA_API_TOKEN=your_jira_api_token
   
   # Supabase Configuration
   NEXT_PUBLIC_SUPABASE_URL=your_supabase_project_url
   NEXT_PUBLIC_SUPABASE_ANON_KEY=your_supabase_anon_key
   SUPABASE_SERVICE_ROLE_KEY=your_supabase_service_role_key # If needed for backend functions
   
   # Next.js specific (if any, otherwise Next.js defaults will be used)
   # PORT=3000

   Note: Obtain API keys and credentials from their respective services (OpenAI, Jira, Supabase).

4. Run the development server:

   npm run dev
   # or
   yarn dev

   Open http://localhost:3000 (or your configured port) in your browser to see the application.

Contributing

Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

License

This project is licensed under the MIT License - see the LICENSE.md file for details (if a LICENSE.md file is present).