Test Failure Analysis & Root Cause Diagnosis
Diagnose Test Failures in Minutes—Pinpoint Bugs vs. Flaky Tests
What You Can Do
Paste a failed test log and get instant diagnosis: is this a real bug, a flaky test, an environment misconfiguration, or something else? The skill parses stack traces, correlates with historical runs, and generates debugging steps—turning cryptic CI failures into clear action items. Save your team hours of manual investigation per incident.
Features
Instantly categorize failures as real bugs, flaky tests, environment issues, or data problems
Parse stack traces and logs to identify the exact line of code causing the failure
Compare historical runs to spot intermittent failures and isolation problems
Produce actionable next steps: what to check, how to reproduce, where to look
Extract relevant context from GitHub Actions, Jenkins, GitLab CI, or custom pipeline logs
Identify if a failure is new or regressed from a known issue
Generate minimal reproduction steps for developers to fix locally
Example Output
Real Bug Diagnosis
Failure Type: Real Bug (92% confidence)
Root Cause: NullPointerException in UserAuthService.authenticate() at line 247
- User object is null after database query
- Likely cause: Race condition in concurrent login attempts
Debugging Steps:
- Check database connection pool settings (max_connections=20?)
- Add defensive null check:
if (user == null) throw new AuthenticationException() - Reproduce locally with concurrent login test
- Search logs for "Connection reset by peer" errors
Flaky Test Diagnosis
Failure Type: Flaky Test (72% confidence)
Symptoms:
- Test passes 8/10 runs, fails 2/10
- No pattern by time of day
- Only fails on CI runner, passes locally
Root Cause: Race condition in async mock setup—mock response not ready when API call fires
Fix: Move mock setup to beforeEach() hook
Historical Trend: First seen 14 days ago, 3 failures in last 50 runs
What's Included
- SKILL.md: Complete diagnostic workflow with decision trees for failure classification
- Root cause analyzer template:
- CI/CD log parser examples (GitHub Actions, Jenkins, GitLab, CircleCI):
- Flakiness scoring model:
- Debugging checklist generator:
- Failure categorization reference guide:
Who It's For
- QA engineers and test automation specialists
- DevOps engineers managing CI/CD pipelines
- Backend and full-stack developers debugging test failures
- Release managers triaging build failures
- Engineering leads reducing flaky test noise
Best For
- Triaging flaky tests in CI/CD pipelines
- Determining if a failure is a real bug or environment issue
- Generating reproducible steps for failing tests
- Reducing false negatives in test suites
- Automating failure incident analysis
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