AgentSkillsCN

analyze-jira-ticket

分析 Jira 工单,评估其复杂度,识别所需代码变更,并估算工作量。

SKILL.md
--- frontmatter
name: analyze-jira-ticket
description: Analyze a Jira ticket to assess complexity, identify code changes needed, and estimate effort

Analyze Jira Ticket Workflow

Use this workflow to analyze a Jira ticket and provide a comprehensive assessment.

Steps

1. Fetch Jira Ticket Details

// turbo Use the Atlassian CLI to fetch the ticket:

code
acli jira auth login --web
acli jira workitem view <TICKET_ID> --json | cat

Extract key information:

  • Summary/Title
  • Description
  • Issue Type (Bug, Task, Story, etc.)
  • Priority
  • Status
  • Parent ticket (if any)
  • Attachments/screenshots

2. Identify Relevant Keywords

From the ticket description, identify:

  • Feature names (e.g., "Share App", "Search", "Profile")
  • UI components mentioned
  • Specific behaviors or flows
  • Error messages (for bugs)

3. Search Codebase for Related Code

// turbo Use grep_search and find_by_name to locate relevant files:

code
grep_search for feature keywords in lib/ directory
find_by_name for files matching feature patterns

Common search patterns:

  • Widget/screen names from the UI
  • Function names mentioned in the ticket
  • Localization keys
  • Test files for context

4. Analyze Code Structure

// turbo View the identified files to understand:

  • Current implementation
  • Data flow
  • Dependencies (imports, packages)
  • Related test files

5. Check Localization (if UI text changes needed)

// turbo The translations are in external package kwcon_translations:

yaml
kwcon_translations:
  git:
    url: git@github.com:KWRI/kwcon-translations.git
    path: l10n/flutter-app

Search for existing localization keys in the codebase.

6. Generate Analysis Report

Provide a structured response with:

Summary

Brief description of what the ticket is about.

Is It Easy to Fix?

Assessment with reasoning:

  • Easy: Single file change, text update, or simple logic modification
  • Medium: Multiple files, requires understanding of data flow
  • Hard: Architecture changes, multiple packages, complex logic

Where Changes Need to Be Made

File/LocationChange Description
path/to/fileWhat needs to change

Estimated Effort

  • Low: < 2 hours
  • Medium: 2-8 hours
  • High: > 8 hours

Additional Considerations

  • Testing requirements
  • Related tickets
  • Potential risks
  • Dependencies on external packages