Skip to main content
AI/MLcoalesce-labs

error-impact-analysis

Analyze the impact and scope of production errors

Stars
12
Source
coalesce-labs/catalyst
Updated
2026-05-31
Slug
coalesce-labs--catalyst--error-impact-analysis
View on GitHubRaw SKILL.md

// install — copy + paste into any project

mkdir -p .claude/skills && curl -fsSL https://raw.githubusercontent.com/coalesce-labs/catalyst/HEAD/plugins/debugging/skills/error-impact-analysis/SKILL.md -o .claude/skills/error-impact-analysis.md

Drops the SKILL.md into .claude/skills/error-impact-analysis.md. Works with Claude Code, Cursor, and any agent that loads SKILL.md files from .claude/skills/.

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