bradtaylorsf Jira Ticket Analysis Skill
This skill provides methodology for analyzing Jira ticket quality and identifying areas for improvement.
Quality Dimensions
1. Clarity
Questions to assess:
- Is the goal obvious from the summary?
- Is the description free of jargon?
- Would a new team member understand this?
- Are acronyms explained?
Scoring:
- 5: Crystal clear, no questions needed
- 4: Clear with minor ambiguity
- 3: Understandable but needs context
- 2: Confusing, multiple interpretations
- 1: Cannot understand the request
2. Completeness
Questions to assess:
- Are acceptance criteria defined?
- Is the scope clear (what's in/out)?
- Are dependencies listed?
- Is technical context provided?
Scoring:
- 5: All information present, ready to implement
- 4: Minor details missing
- 3: Key information missing but discoverable
- 2: Significant gaps
- 1: Missing most required information
3. Actionability
Questions to assess:
- Can work start immediately?
- Are blockers identified and addressed?
- Is the scope achievable?
- Are success criteria measurable?
Scoring:
- 5: Can start now with confidence
- 4: One small clarification needed
- 3: Some research/clarification needed
- 2: Blocked or unclear how to proceed
- 1: Cannot start without major discovery
4. Context
Questions to assess:
- Is the "why" explained?
- Is user impact described?
- Are related tickets linked?
- Is there technical background?
Scoring:
- 5: Full context, understand importance
- 4: Good context, minor gaps
- 3: Basic context provided
- 2: Little context, unclear importance
- 1: No context, don't know why this matters
Analysis Process
Step 1: Initial Read
- Read summary and description
- Note first impressions
- Identify obvious issues
Step 2: Score Dimensions
Rate each dimension 1-5 and note specific issues:
| Dimension | Score | Issues |
|-----------|-------|--------|
| Clarity | 3 | Acronyms undefined, vague scope |
| Completeness | 2 | No acceptance criteria |
| Actionability | 2 | Blocked by design |
| Context | 4 | Good background |
| **Overall** | **2.75** | Needs refinement |
Step 3: Identify Improvements
For each issue, provide:
- What's wrong
- How to fix it
- Example improved text
Step 4: Provide Recommendations
Prioritize fixes by impact:
- Critical (blocks understanding)
- Important (delays work)
- Nice-to-have (polish)
Common Issues and Fixes
Issue: Vague Summary
Before: "Fix the thing" After: "Fix payment processing timeout for orders over $1000"
Pattern: [Action] [specific thing] [condition/context]
Issue: Missing Acceptance Criteria
Before:
Make the page faster
After:
h2. Acceptance Criteria
* Page load time < 2 seconds on 3G connection
* Lighthouse performance score > 80
* No layout shift during load
* Images lazy-loaded below fold
Issue: No Context/Why
Before:
Add retry logic to API calls
After:
h2. Context
Users are experiencing intermittent failures when the payment service is slow to respond. This causes checkout abandonment and support tickets.
h2. Problem
When the payment API times out (typically 2-3 times per day during peak hours), the user sees an error with no recovery path.
h2. Solution
Add retry logic with exponential backoff to handle transient failures gracefully.
Issue: Code-Heavy Description
Before:
Change this:
function processOrder(order) {
// 50 lines of code
}
To this:
function processOrder(order) {
// 50 different lines of code
}
After:
h2. Change Required
Modify {{src/services/orderProcessor.ts}} to validate order totals before processing.
h2. Technical Notes
* Add validation in processOrder function
* Throw OrderValidationError for invalid totals
* Log validation failures for monitoring
Issue: Scope Creep
Before:
Add user notifications. Also we should probably redo the entire notification system and add email preferences and maybe webhooks too.
After:
h2. Scope
Add email notification when order ships.
h2. Out of Scope (Future Tickets)
* Notification preferences UI
* Webhook integrations
* Push notifications
Analysis Report Template
## Ticket Quality Analysis: PROJ-123
### Summary
[Brief description of the ticket]
### Quality Scores
| Dimension | Score | Status |
|-----------|-------|--------|
| Clarity | X/5 | [Good/Needs Work/Poor] |
| Completeness | X/5 | [Good/Needs Work/Poor] |
| Actionability | X/5 | [Good/Needs Work/Poor] |
| Context | X/5 | [Good/Needs Work/Poor] |
| **Overall** | **X/5** | |
### Issues Found
#### Critical Issues
1. [Issue description]
- Impact: [Why this matters]
- Fix: [How to resolve]
#### Important Issues
1. [Issue description]
- Impact: [Why this matters]
- Fix: [How to resolve]
#### Minor Issues
1. [Issue description]
### Recommended Improvements
1. **[Most Important Fix]**
Current: [What it says now]
Improved: [What it should say]
2. **[Second Fix]**
[Details]
### Readiness Assessment
- [ ] Ready for sprint planning
- [x] Needs refinement first
- [ ] Needs product clarification
- [ ] Needs technical discovery
Batch Analysis Patterns
Finding Low-Quality Tickets
# Missing description
project = PROJ AND description IS EMPTY
# Short descriptions (< 100 chars approximation)
project = PROJ AND description ~ "[a-zA-Z]" AND NOT description ~ "*\\n*"
# No acceptance criteria pattern
project = PROJ AND description !~ "acceptance" AND description !~ "criteria" AND type = Story
# Old unrefined tickets
project = PROJ AND status = "To Do" AND created <= -60d AND labels NOT IN ("refined", "ready")
Quality Dashboard Metrics
Track over time:
- % tickets with acceptance criteria
- Average quality score
- Tickets needing refinement
- Time from creation to ready status
Integration with Refinement
Pre-Refinement Analysis
- Run batch analysis on sprint candidates
- Generate quality report
- Prioritize tickets needing work
- Estimate refinement effort
During Refinement
- Review analysis findings
- Discuss improvements with team
- Update tickets in real-time
- Re-score after improvements
Post-Refinement Verification
- Verify all critical issues addressed
- Confirm acceptance criteria added
- Check technical context included
- Mark tickets as "refined"