majiayu000 Fix Sentry Issues
Discover, analyze, and fix production issues using Sentry's full debugging capabilities.
Invoke This Skill When
- User asks to "fix Sentry issues" or "resolve Sentry errors"
- User wants to "debug production bugs" or "investigate exceptions"
- User mentions issue IDs, error messages, or asks about recent failures
- User wants to triage or work through their Sentry backlog
Prerequisites
- Sentry MCP server configured and connected
- Access to the Sentry project/organization
Phase 1: Issue Discovery
Use Sentry MCP to find issues. Confirm with user which issue(s) to fix before proceeding.
| Search Type | MCP Call |
|---|---|
| Recent unresolved | sentry_search_issues query: "is:unresolved" sort: "date" |
| Specific error type | sentry_search_issues query: "is:unresolved error.type:TypeError" |
| By ID | sentry_get_issue issue_id: "PROJECT-123" |
Phase 2: Deep Issue Analysis
Gather ALL available context for each issue:
| Data Source | MCP Call | Extract |
|---|---|---|
| Core Error | sentry_get_issue |
Exception type/message, full stack trace, file paths, line numbers, function names |
| Event Details | sentry_get_event |
Breadcrumbs, tags, custom context, request data |
| Trace (if available) | sentry_get_trace |
Parent transaction, spans, DB queries, API calls, error location |
| Replay (if available) | sentry_get_replay |
User actions, UI state, network requests |
Phase 3: Root Cause Hypothesis
Before touching code, document:
- Error Summary: One sentence describing what went wrong
- Immediate Cause: The direct code path that threw
- Root Cause Hypothesis: Why the code reached this state
- Supporting Evidence: Breadcrumbs, traces, or context supporting this
- Alternative Hypotheses: What else could explain this? Why is yours more likely?
Challenge yourself: Is this a symptom of a deeper issue? Check for similar errors elsewhere, related issues, or upstream failures in traces.
Phase 4: Code Investigation
| Step | Actions |
|---|---|
| Locate Code | Read every file in stack trace from top down |
| Trace Data Flow | Find value origins, transformations, assumptions, validations |
| Error Boundaries | Check for try/catch - why didn't it handle this case? |
| Related Code | Find similar patterns, check tests, review recent commits (git log, git blame) |
Phase 5: Implement Fix
Before writing code, confirm your fix will:
- Handle the specific case that caused the error
- Not break existing functionality
- Handle edge cases (null, undefined, empty, malformed)
- Provide meaningful error messages
- Be consistent with codebase patterns
Apply the fix: Prefer input validation > try/catch, graceful degradation > hard failures, specific > generic handling, root cause > symptom fixes.
Add tests reproducing exact Sentry event conditions and verifying edge cases.
Phase 6: Verification Audit
Complete before declaring fixed:
| Check | Questions |
|---|---|
| Evidence | Does fix address exact error message? Handle data state shown? Prevent ALL events? |
| Regression | Could fix break existing functionality? Other code paths affected? Backward compatible? |
| Completeness | Similar patterns elsewhere? Related Sentry issues? Add monitoring/logging? |
| Self-Challenge | Root cause or symptom? Considered all event data? Will handle if occurs again? |
Phase 7: Report Results
Format:
## Fixed: [ISSUE_ID] - [Error Type]
- Error: [message], Frequency: [X events, Y users], First/Last: [dates]
- Root Cause: [one paragraph]
- Evidence: Stack trace [key frames], breadcrumbs [actions], context [data]
- Fix: File(s) [paths], Change [description]
- Verification: [ ] Exact condition [ ] Edge cases [ ] No regressions [ ] Tests [y/n]
- Follow-up: [additional issues, monitoring, related code]
Quick Reference
MCP Tools: sentry_search_issues, sentry_get_issue, sentry_get_event, sentry_get_trace, sentry_get_replay, sentry_list_projects, sentry_get_project
Common Patterns: TypeError (check data flow, API responses, race conditions) • Promise Rejection (trace async, error boundaries) • Network Error (breadcrumbs, CORS, timeouts) • ChunkLoadError (deployment, caching, splitting) • Rate Limit (trace patterns, throttling) • Memory/Performance (trace spans, N+1 queries)