User Story Management and Integration

Core Agent provides comprehensive user story management capabilities, including integration with project management tools like Jira, automated story extraction from designs, and intelligent story generation from application screenshots. This enables seamless conversion of requirements into actionable test cases and development tasks.

Jira Integration

Connecting to Jira

Core Agent can connect to Jira instances to extract user stories, epics, and tasks, providing a direct bridge between project management and test automation.

Authentication Setup

# Jira Configuration
jira_config:
  server_url: "https://your-company.atlassian.net"
  authentication:
    type: "api_token"  # or "oauth", "basic_auth"
    username: "[email protected]"
    api_token: "your-api-token"
  
  project_settings:
    default_project: "ECOM"
    issue_types: ["Story", "Epic", "Task", "Bug"]
    custom_fields:
      - "acceptance_criteria"
      - "test_scenarios"
      - "business_value"

Story Extraction Process

🎫 Jira Integration Workflow:
├── 🔍 Connect to Jira instance
├── 📋 Query stories by project/filter
├── 📊 Extract story details and metadata
├── 🧪 Analyze acceptance criteria
├── 🎯 Identify test scenarios
└── 📝 Generate test cases and documentation

Story Analysis and Processing

Story Structure Recognition

📝 Jira Story Analysis:
├── Story Title and Description
├── Acceptance Criteria (Given-When-Then)
├── Story Points and Priority
├── Labels and Components
├── Linked Issues and Dependencies
├── Comments and Attachments
└── Custom Fields and Metadata

Example: Jira Story Processing

🎫 ECOM-456: User Account Registration

📋 Story Details:
- Type: Story
- Priority: High
- Story Points: 5
- Sprint: Sprint 23
- Assignee: John Developer
- Reporter: Jane Product Owner

📝 Description:
"As a new user, I want to create an account on the e-commerce platform 
so that I can save my preferences and track my orders."

✅ Acceptance Criteria:
1. Given I am on the registration page
   When I enter valid email, password, and personal details
   Then my account should be created successfully

2. Given I am registering with an existing email
   When I submit the registration form
   Then I should see an error message "Email already exists"

3. Given I enter an invalid email format
   When I submit the registration form
   Then I should see validation error for email format

🧪 Generated Test Cases:
├── ✅ Valid User Registration
├── ❌ Registration with Existing Email
├── ❌ Registration with Invalid Email Format
├── ❌ Registration with Weak Password
├── 🔒 Registration Without Required Fields
└── 📊 Registration with Various Data Combinations

Bulk Story Processing

# Bulk Story Extraction Configuration
bulk_extraction:
  query: "project = ECOM AND status IN ('To Do', 'In Progress') AND type = Story"
  batch_size: 50
  processing_options:
    extract_acceptance_criteria: true
    generate_test_cases: true
    create_test_data: true
    link_dependencies: true
    
  output_format:
    test_suites: "feature_based"
    documentation: "markdown"
    traceability_matrix: "excel"
    
  filters:
    priority: ["High", "Medium"]
    components: ["User Management", "Shopping Cart", "Payment"]
    labels: ["testing-required", "automation-candidate"]

Figma Design Integration

Design Analysis Capabilities

Core Agent can analyze Figma designs to extract UI components, user flows, and generate corresponding user stories and test cases.

Figma API Integration

# Figma Configuration
figma_config:
  api_token: "your-figma-api-token"
  team_id: "your-team-id"
  
  analysis_settings:
    extract_components: true
    identify_interactions: true
    analyze_user_flows: true
    generate_responsive_tests: true
    
  supported_elements:
    - buttons
    - forms
    - navigation
    - modals
    - dropdowns
    - image_galleries
    - data_tables

Design-to-Story Generation Process

🎨 Figma Analysis Workflow:
├── 🔗 Connect to Figma file/project
├── 📊 Extract design components and layouts
├── 🔍 Identify interactive elements
├── 🗺️ Map user interaction flows
├── 📝 Generate user stories from interactions
├── 🧪 Create corresponding test cases
└── 📋 Build comprehensive test plans

Practical Example: E-commerce Checkout Flow

Figma Design Analysis

🎨 Figma File: "E-commerce Checkout Flow"

🔍 Identified Screens:
├── 📄 Shopping Cart Review
├── 🚚 Shipping Information
├── 💳 Payment Details
├── 📋 Order Summary
└── ✅ Confirmation Page

🖱️ Interactive Elements Detected:
├── Quantity Selectors (+ / - buttons)
├── Remove Item Buttons
├── Shipping Method Radio Buttons
├── Payment Method Selection
├── Credit Card Form Fields
├── Promo Code Input
├── Place Order Button
└── Continue Shopping Link

📱 Responsive Breakpoints:
├── Desktop: 1200px+
├── Tablet: 768px - 1199px
└── Mobile: 320px - 767px

Generated User Stories

📝 Generated User Stories from Figma Design:

🎫 ECOM-501: Shopping Cart Quantity Management
"As a customer, I want to adjust item quantities in my cart 
so that I can purchase the exact amount I need."

Acceptance Criteria:
✅ User can increase quantity using + button
✅ User can decrease quantity using - button
✅ Quantity cannot go below 1
✅ Price updates automatically when quantity changes
✅ Total cart value recalculates correctly

🎫 ECOM-502: Shipping Method Selection
"As a customer, I want to choose my preferred shipping method 
so that I can balance cost and delivery speed."

Acceptance Criteria:
✅ Multiple shipping options are displayed with costs
✅ User can select one shipping method
✅ Delivery estimates are shown for each option
✅ Total order cost updates with shipping selection
✅ Default shipping method is pre-selected

🎫 ECOM-503: Payment Information Entry
"As a customer, I want to securely enter my payment details 
so that I can complete my purchase."

Acceptance Criteria:
✅ Credit card form validates card number format
✅ Expiry date validation prevents past dates
✅ CVV field is masked for security
✅ Billing address can be same as shipping
✅ Payment form shows security indicators

Application Screenshot Analysis

Screenshot Processing Capabilities

Core Agent can analyze application screenshots to understand existing functionality and generate corresponding user stories and test cases.

Screenshot Analysis Process

📸 Screenshot Analysis Workflow:
├── 🖼️ Upload application screenshots
├── 🔍 Identify UI elements and components
├── 📊 Analyze layout and information architecture
├── 🎯 Infer user interactions and workflows
├── 📝 Generate user stories for identified features
├── 🧪 Create test cases for functionality
└── 📋 Build regression test suites

Element Recognition Technology

🤖 AI-Powered Element Detection:
├── Buttons and Clickable Elements
├── Form Fields and Input Controls
├── Navigation Menus and Links
├── Data Tables and Lists
├── Modal Dialogs and Popups
├── Image Galleries and Carousels
├── Search Bars and Filters
└── Status Indicators and Badges

Example: Mobile App Screenshot Analysis

Screenshot Input

📱 Mobile App Screenshots: "Food Delivery App"

🖼️ Analyzed Screens:
├── 🏠 Home Screen (Restaurant listings)
├── 🍕 Restaurant Detail Page
├── 🛒 Menu and Cart
├── 📍 Delivery Address Selection
└── 💳 Payment and Checkout

Generated Analysis Report

📊 Screenshot Analysis Report:

🔍 Identified Features:
├── Restaurant Search and Filtering
├── Menu Item Selection and Customization
├── Shopping Cart Management
├── Address and Location Services
├── Payment Processing
├── Order Tracking
└── User Account Management

🖱️ Interactive Elements:
├── Search Bar with Filter Options
├── Restaurant Cards (Clickable)
├── Add to Cart Buttons
├── Quantity Selectors
├── Customization Options (Size, Toppings)
├── Address Selection Map
├── Payment Method Cards
└── Order Status Indicators

📱 Mobile-Specific Patterns:
├── Bottom Navigation Tabs
├── Swipe Gestures for Image Galleries
├── Pull-to-Refresh on Restaurant List
├── Floating Action Button for Cart
└── Modal Overlays for Item Details

Generated User Stories

📝 User Stories from Screenshot Analysis:

🎫 FOOD-101: Restaurant Discovery
"As a hungry customer, I want to browse nearby restaurants 
so that I can find food options that appeal to me."

Acceptance Criteria:
✅ Restaurants are displayed with photos and ratings
✅ Filter options include cuisine type, price range, delivery time
✅ Search functionality works with restaurant names and food types
✅ Location-based sorting shows nearest restaurants first
✅ Restaurant cards show key information (rating, delivery fee, time)

🎫 FOOD-102: Menu Item Customization
"As a customer, I want to customize my food order 
so that I can get exactly what I want."

Acceptance Criteria:
✅ Menu items show customization options (size, toppings, etc.)
✅ Price updates automatically with customizations
✅ Special instructions field is available
✅ Dietary restrictions and allergen info is displayed
✅ Add to cart button is prominent and functional

🎫 FOOD-103: Cart Management
"As a customer, I want to review and modify my order 
before checkout so that I can ensure it's correct."

Acceptance Criteria:
✅ Cart shows all selected items with customizations
✅ Quantity can be adjusted for each item
✅ Items can be removed from cart
✅ Subtotal, taxes, and delivery fees are clearly displayed
✅ Promo codes can be applied and validated

Integration Workflows

End-to-End Story Processing

name: story-to-test-pipeline
description: Complete pipeline from story extraction to test execution

steps:
  - name: story-extraction
    sources: ["jira", "figma", "screenshots"]
    actions:
      - extract_stories: "all_active_sprints"
      - analyze_acceptance_criteria: "detailed_parsing"
      - identify_test_scenarios: "comprehensive_coverage"
      
  - name: test-generation
    actions:
      - generate_functional_tests: "positive_and_negative"
      - create_integration_tests: "api_and_ui"
      - build_performance_tests: "load_scenarios"
      - generate_test_data: "realistic_datasets"
      
  - name: test-organization
    actions:
      - create_test_suites: "story_based_grouping"
      - setup_execution_order: "dependency_aware"
      - configure_environments: "multi_environment"
      
  - name: documentation
    actions:
      - generate_test_plans: "comprehensive_coverage"
      - create_traceability_matrix: "story_to_test_mapping"
      - build_execution_reports: "detailed_results"

Cross-Platform Story Analysis

# Multi-Source Story Integration
integration_config:
  sources:
    jira:
      projects: ["ECOM", "MOBILE", "API"]
      issue_types: ["Story", "Epic", "Task"]
      
    figma:
      teams: ["Design Team", "UX Research"]
      projects: ["Web App", "Mobile App"]
      
    screenshots:
      applications: ["Production App", "Staging App"]
      platforms: ["Web", "iOS", "Android"]
      
  consolidation:
    merge_duplicate_stories: true
    resolve_conflicts: "manual_review"
    maintain_source_links: true
    
  output:
    unified_backlog: "priority_ordered"
    test_coverage_matrix: "comprehensive"
    execution_roadmap: "sprint_aligned"

Related Documentation

• Test Case Generation - Converting stories to test cases
• Rules and Workflows - Automating story processing workflows

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User story management with Core Agent provides seamless integration between project management tools, design systems, and test automation, ensuring comprehensive coverage from requirements to execution.