General
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### CI/CD Pipeline Logs (Jenkins
GitHub Actions
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Explore
Find agent skills by outcome
101,273 skills indexed with the new KISS metadata standard.
Showing 24 of 101,273Categories: Data, General, Openclaw
General
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- Focus coverage improvement on high-risk areas: payment flows
authentication
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- Classify flaky root causes: timing/async issues
test isolation
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- Use statistical methods (chi-squared
correlation) to validate suspected patterns before reporting
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- [ ] Recommendations are specific
actionable
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After completing analysis
verify:
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- Provide specific
actionable next steps for each recommendation (not generic advice)
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- Detect cyclical patterns (end-of-sprint degradation
day-of-week effects)
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- Correlate failure clusters with specific components
teams
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- Categorize all failures: genuine bugs
flaky tests
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Data
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- Verify data completeness: no missing test runs
coverage reports
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- **Yellow flags**: Declining pass rates
stagnant coverage
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- **Red flags**: Pass rate below 85%
coverage below 50%
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- **Green flags**: Consistent high pass rates
coverage trending upward
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- **Coverage**: >80% (green)
>60% (yellow)
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- **Flaky Rate**: <1% (green)
<5% (yellow)
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- **Pass Rate**: >95% (green)
>90% (yellow)
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- Generate detailed technical report with metrics
trends
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- Calculate pass rates
flaky rates
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- Identify degradation trends: increasing execution times
declining pass rates
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- Detect environmental factors: time-of-day patterns
CI runner differences
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- Parse test execution logs and reports from CI/CD pipelines (JUnit
pytest
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- Gather coverage reports from instrumentation tools (Istanbul
Coverage.py
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- Group test failures by component
module
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