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gh-coalesce-labs-catalyst-p…/commands/error_impact_analysis.md
2025-11-29 18:14:36 +08:00

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---
description: Analyze the impact and scope of production errors
category: debugging
tools: Task, TodoWrite
model: inherit
version: 1.0.0
---
# Error Impact Analysis
Assess the severity, reach, and business impact of production errors.
## Usage
```bash
/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
```bash
/error-impact-analysis "What's the impact of MYAPP-123? How many users, revenue impact?"
```
### Category Impact
```bash
/error-impact-analysis "Overall impact of all payment-related errors this month"
```
### Release Health
```bash
/error-impact-analysis "Error impact comparison: current release vs previous release"
```
### Critical Errors
```bash
/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:
```bash
/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
```bash
/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
```bash
> "Based on this impact, should we rollback or hotfix?"
```
### 4. Track Resolution
```bash
> "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:
```bash
/plugin disable catalyst-debugging
```
---
**See also**: `/debug-production-error`, `/trace-analysis`