3.4 KiB
3.4 KiB
description, category, tools, model, version
| description | category | tools | model | version |
|---|---|---|---|---|
| Analyze the impact and scope of production errors | debugging | Task, TodoWrite | inherit | 1.0.0 |
Error Impact Analysis
Assess the severity, reach, and business impact of production errors.
Usage
/error-impact-analysis <error-or-timeframe>
Examples:
/error-impact-analysis "ISSUE-789"
/error-impact-analysis "checkout errors last 7 days"
/error-impact-analysis "critical errors this week"
/error-impact-analysis "impact of recent deployment"
What This Analyzes
Quantitative Impact
- Number of occurrences
- Number of users affected
- Error rate over time
- Affected environments/releases
Qualitative Impact
- Error severity (critical, high, medium, low)
- Affected user workflows
- Business function impact (checkout, signup, etc.)
- User experience degradation
Trend Analysis
- Is it increasing or decreasing?
- When did it start?
- Related to specific release?
- Correlation with traffic/usage
Example Analyses
Single Issue Impact
/error-impact-analysis "What's the impact of MYAPP-123? How many users, revenue impact?"
Category Impact
/error-impact-analysis "Overall impact of all payment-related errors this month"
Release Health
/error-impact-analysis "Error impact comparison: current release vs previous release"
Critical Errors
/error-impact-analysis "Show all critical errors and their combined user impact"
Output Format
Analysis includes:
Scope:
- Total occurrences
- Unique users affected
- Affected countries/regions
- Browser/device breakdown
Severity Assessment:
- Error frequency
- User impact score
- Business criticality
- Blocking vs non-blocking
Trends:
- Occurrence over time (chart/data)
- Peak times
- Growth rate
- Comparison to baseline
Business Impact:
- Affected revenue-generating flows
- Customer support tickets related
- SLA implications
- Reputation risk
Prioritization:
- Recommendation on urgency
- Comparison with other errors
- ROI of fixing
Integration with Analytics
Enable both plugins for deeper impact analysis:
/plugin enable catalyst-debugging
/plugin enable catalyst-analytics
/error-impact-analysis "How many users who hit error X churned vs users who didn't?"
This combines:
- Sentry error data (who hit the error)
- PostHog behavior data (did they churn)
Incident Response Workflow
1. Assess Impact
/error-impact-analysis "new spike in errors at 3pm"
2. Determine Severity
Based on output:
- Critical: >1000 users, blocking checkout/signup
- High: >100 users, degraded experience
- Medium: <100 users, minor inconvenience
- Low: <10 users, edge case
3. Prioritize Response
> "Based on this impact, should we rollback or hotfix?"
4. Track Resolution
> "After fix, compare error rates before and after"
Tips for Impact Analysis
- Consider timeframe - "last hour" for incidents, "last week" for trends
- Segment users - Impact on paid vs free users may differ
- Check related errors - One root cause may affect multiple error types
- Compare releases - Pinpoint when impact started
- Business context - Impact during peak hours is more severe
Context Cost
Plugin uses ~20k tokens. Disable after analysis:
/plugin disable catalyst-debugging
See also: /debug-production-error, /trace-analysis