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Features Overview
Smart Issue Analyzer provides 12+ AI-powered capabilities to streamline your issue management workflow.
What it does: Identifies if a new issue duplicates existing issues
How it works: Compares against all repository issues using semantic similarity
Action taken: Auto-closes duplicate with reference to original
Example:
Issue #23: "Login not working on mobile"
→ Detected duplicate of #12
→ Auto-closed with comment: "Duplicate of #12"
What it does: Applies relevant topic labels automatically
Labels applied:
- bug - Defects and errors
- enhancement - New features
- documentation - Documentation updates
- security - Security concerns
- performance - Performance issues
- ui/ux - Interface improvements
Example:
"The dashboard loads slowly for 100+ items"
→ Labels: performance, ui/ux
What it does: Assigns priority levels (P0-P3) based on impact and urgency
Priority Levels:
- P0 - Critical: Production down, security breach, data loss
- P1 - High: Major feature broken, significant user impact
- P2 - Medium: Minor bugs, non-critical enhancements
- P3 - Low: Nice-to-have features, minor improvements
Example:
"Users cannot checkout - payment system down"
→ Priority: P0 (payment critical for business)
What it does: Estimates development effort using t-shirt sizes
Size Scale:
- XS (1-2 hours): Simple config change, typo fix
- S (2-4 hours): Small bug fix, minor feature
- M (1-2 days): Moderate feature, complex bug
- L (3-5 days): Large feature, architectural change
- XL (1+ week): Epic-level work, major refactor
Example:
"Add dark mode theme support"
→ Size: L (CSS overhaul, state management, persistence)
What it does: Detects urgency, frustration, or critical tone
Flags applied: needs-attention for negative sentiment
Example:
"This is EXTREMELY frustrating! Lost all my work!!!"
→ Sentiment: Negative
→ Flag: needs-attention
→ Priority: Elevated
What it does: Identifies gaps in issue description
Prompts for:
- Screenshots
- Reproduction steps
- Error messages/logs
- Environment details (browser, OS, version)
Example:
"App crashes when I click submit"
→ Missing: error logs, browser version, repro steps
What it does: Identifies large initiatives that should be broken down
Suggests: Sub-issues for better tracking
Example:
"Rebuild entire authentication system with OAuth2, SSO, MFA"
→ Type: epic
→ Suggested sub-issues:
- Implement OAuth2 provider integration
- Add SSO support for enterprise
- Build MFA enrollment flow
- Update security documentation
What it does: Identifies issue dependencies and blockers
Detects:
- Blocks: Issues that must be completed first
- Blocked by: Issues preventing progress
Example:
"Add user profile page (requires #45 user API endpoint)"
→ Blocked by: #45
What it does: Links to similar past issues
Benefits:
- Reuse solutions from previous work
- Avoid duplicate effort
- Learn from past mistakes
Example:
"Database migration failing on startup"
→ Similar to: #67, #82, #103
→ Solution found in: #103
What it does: Recommends team members based on expertise
Considers:
- Issue type and labels
- Team member specializations
- Workload distribution
Example:
"PostgreSQL query timeout on reports page"
→ Suggested assignee: @database-team
What it does: Provides Spanish translation of title and description
Use case: International teams, accessibility
Example:
Original: "Login button not responsive on mobile"
Spanish: "Botón de inicio de sesión no responde en móvil"
What it does: When duplicates found, suggests consolidating discussions
Example:
Issue #50 duplicates #30 (has 12 comments)
→ Proposal: Close #50, move discussion to #30
→ Action: Auto-comment with link to original
- 3-5 seconds average analysis time
- 4 parallel LLM calls for speed
- 99%+ success rate on valid issues
New Issue Created
↓
[Fetch All Issues Context]
↓
┌────────────────────────────────┐
│ 4 Parallel LLM Analyses: │
│ 1. Duplicate Detection │
│ 2. Classification │
│ 3. Context Analysis │
│ 4. Spanish Translation │
└────────────────────────────────┘
↓
[Apply Labels & Priority]
↓
[Post Comprehensive Comment]
↓
[Close if Duplicate]
- Architecture - Technical deep dive
- Examples - Real-world use cases
- Best Practices - Optimization tips