Aggregate CircleCI, Kubernetes, and monitoring data to diagnose pipeline and deployment failures.
npx skills add https://github.com/alexfalkowski/bin --skill diagnose-issue
Please help me install this Agent Skill. Skill: diagnose-issue Source: https://github.com/alexfalkowski/bin/tree/main/skills/diagnose-issue Command: npx skills add https://github.com/alexfalkowski/bin --skill diagnose-issue
This skill eliminates the manual, time-consuming process of investigating CI pipeline failures, deployment rollouts, and Kubernetes runtime issues by automating the collection and analysis of diagnostic evidence.
Use the diagnose-issue skill to investigate the latest CI pipeline failure for the current branch.
High-intent search queries and answers about installing and using this skill.
To automate CircleCI pipeline failure diagnosis, this skill analyzes workflow status and job logs to identify the root cause of failing PR checks and build jobs. It securely aggregates diagnostic evidence by executing Ruby collection scripts and parsing JSON output with jq.
Kubernetes deployment failures after a successful CI build occur when runtime pods are unready. This skill correlates the current runtime image against the expected version, checking pod health and service states to pinpoint whether the issue stems from an unready pod or a failed deploy job.
Yes, you need Ruby and jq installed to troubleshoot CI/CD pipelines with this skill. Ruby executes the collection scripts that aggregate status data from CircleCI and Kubernetes, while jq is required to parse the JSON evidence securely during the diagnostic analysis.
Yes, you can check DigitalOcean and UptimeRobot service states during deployment troubleshooting. This skill correlates deployment versions with Kubernetes pod health, DigitalOcean service states, and UptimeRobot monitors to pinpoint rollout failures and verify system health.
The best way to investigate production rollout failures in Kubernetes is to automate the diagnostic analysis of deployment environments. This skill compares the current runtime image against the expected version and identifies if the issue stems from a failed deploy job or an unready Kubernetes pod.
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