error-impact-analysis

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

1. Consider timeframe - "last hour" for incidents, "last week" for trends
2. Segment users - Impact on paid vs free users may differ
3. Check related errors - One root cause may affect multiple error types
4. Compare releases - Pinpoint when impact started
5. Business context - Impact during peak hours is more severe

Context Cost

Plugin uses ~20k tokens. Disable after analysis:

/plugin disable catalyst-debugging

See also: /catalyst-debugging:debug-production-error, /catalyst-debugging:trace-analysis