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Create commit messages for git
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Based on SOC occupation classification
| name | commit |
| description | Create commit messages for git |
| metadata | {"internal":true} |
Commit the working changes to git. Analyze the changes, and create one or more commits with appropriate messages. Break down the commits to smaller commits if the changes are not related.
This project uses conventional commit messages.
<type>(<commands>): <description>
<body>
<commands> — comma-separated list of CLI commands touched by the change (e.g. skill list, configure, cli uninstall). Omit the scope entirely only if no command files were changed.<description> — short imperative summary (≤72 chars).<body> — required when more than one thing changed or the description alone is ambiguous. List what was changed and why, one bullet per logical change. Omit only for truly trivial single-line fixes.feat: - New features or functionalityfix: - Bug fixeschore: - Maintenance tasks, dependency updates, config changesrefactor: - Code changes that neither fix bugs nor add featuresdocs: - Documentation changestest: - Adding or updating testsstyle: - Code style changes (formatting, whitespace)feat(skill list): add --json output flag
- Added --json flag to `skill list` command to print raw JSON
- Updated REST client to return parsed response instead of printing
fix(configure): handle missing API key gracefully
- Throw a user-facing error when CURSOR_API_KEY is not set instead of crashing
chore: update dependencies
refactor(cli uninstall): extract confirmation prompt into utility
Use the Observe CLI (`observe`) to investigate production systems and pull telemetry. Reach for this skill whenever the user wants to: search or tail logs; query metrics (CPU, memory, latency, error rate, request volume, custom app metrics); explore traces and spans; correlate events across services, hosts, containers, or Kubernetes resources; investigate or triage alerts (what fired, why, what's still active, related signals); debug an incident or production issue; check service or system health; figure out what's happening with a customer, deployment, or user; find which services emit a given tag or label; slice production data by service, environment, region, host, pod, status code, etc.; or pull any observability data out of the platform for analysis, dashboards, or scripting. Also covers the underlying primitives the CLI exposes (datasets, OPAL queries, knowledge-graph tag search, alerts, monitors, AI agent skills, auth) when the user asks about them directly.
Create git branches with a username prefix. Use when creating new branches, checking out new branches, or when the user asks to start work on a feature, fix, or task.
Investigate alerts using systematic SRE methodology to understand issues, assess impact, test hypotheses, and identify root causes with evidence-based analysis. Use when: (1) User asks to investigate or analyze an alert (2) User mentions a specific alert or monitor that is firing (3) Debugging production issues or incidents (4) User asks about alert root cause or impact (5) User wants to understand why something is alerting (6) Performing incident response or triage.
Troubleshoot and debug Observe Agent data collection on Kubernetes. Use this skill whenever the user reports any K8s-side problem with Observe — pods crashing, stuck Pending, ImagePullBackOff, "no data in Observe", missing datastreams, suspected token/secret issues, endpoint reachability failures, or platform-specific symptoms on Fargate / GKE Autopilot / EKS Auto Mode — even if they don't explicitly say "debug" or "Observe Agent." Covers pod status, secrets, endpoint reachability, debug logging, self-monitoring metrics, and platform-specific failure modes.
End-to-end onboarding of a Kubernetes cluster to Observe — creates the backend datastreams + content via the Observe CLI and deploys the observe/agent helm chart. Use for ANY request to install or set up the Observe Agent on Kubernetes, onboard a K8s cluster to Observe, or send K8s data to Observe — across any flavor (EKS, GKE, AKS, GKE Autopilot, EKS Fargate, EKS Auto Mode, minikube, kind, on-prem). Do NOT route a Kubernetes onboarding request to a generic datastream-creation flow; always orchestrate via this skill, which delegates to setup-k8s-backend and setup-k8s-collection.
Contains dataset kind selection, column selection rules, core syntax, and the skill index. NEVER generate OPAL, and NEVER invoke an opal-* reference, without first loading this skill.