Monitoring

github-ops is a GitHub operations skill for triaging issues, managing PRs, checking CI failures, preparing releases, and monitoring repository health with the gh CLI. Use the github-ops skill when you need repeatable github-ops usage for a real repository, with auth via gh auth login and clear repo context.

enterprise-agent-ops helps you operate long-lived or cloud-hosted agent systems with observability, safety controls, change management, and recovery planning. Use it when you need a practical guide for agent orchestration, not a one-shot prompt.

dashboard-builder helps you turn metrics into a practical operational dashboard for Grafana, SigNoz, or similar tools. Use the dashboard-builder skill when you need a clear dashboard-builder guide for health, bottlenecks, throughput, and action-focused panels instead of a vanity board.

memory-forensics skill for RAM capture and dump analysis with Volatility 3. Covers install context, usage workflows, artifact extraction, and incident triage across Windows, Linux, macOS, and VM memory.

incident-runbook-templates helps teams create structured incident response runbooks with clear triage, mitigation, escalation, communication, and recovery steps for outages and operational Playbooks.

The shipping-and-launch skill prepares risky releases for production with a pre-launch checklist, monitoring setup, staged rollout planning, success criteria, and rollback strategy. Use it when you need safer Deployment, not just a deploy command. It is designed for engineers and operators who want a structured shipping-and-launch guide.

huggingface-trackio helps track ML training runs with Trackio. Use this skill to log metrics from Python, add training alerts, and retrieve or analyze runs with the trackio CLI. It supports real-time dashboards, Hugging Face Space sync, and JSON output for automation, making huggingface-trackio useful for experiment tracking and data analysis.

analyzing-ransomware-leak-site-intelligence helps monitor ransomware data leak sites, extract victim and group signals, and produce structured threat intelligence for incident response, sector risk review, and adversary tracking.

azure-monitor-query-py helps Python developers query Azure Monitor logs and metrics with azure-monitor-query. Use it for Log Analytics workspaces, Azure resource metrics, backend monitoring, diagnostics, and observability automation. It fits the azure-monitor-query-py skill when you already have workspace IDs, resource URIs, and Azure credentials.

Learn azure-monitor-query-java for Backend Development with install notes, client patterns, and practical logs and metrics usage. This azure-monitor-query-java skill covers the deprecated Azure Monitor Query SDK for Java, points to the newer split packages, and helps you read SKILL.md and examples quickly.

azure-monitor-opentelemetry-exporter-java skill for Java backend Development and Azure Monitor/OpenTelemetry migration. Learn legacy exporter usage, install context, and why the repo recommends azure-monitor-opentelemetry-autoconfigure for new setups. Includes dependency setup, connection string configuration, and practical guidance for traces, metrics, and logs.

azure-monitor-ingestion-java skill for Java backend development that sends custom logs to Azure Monitor via Logs Ingestion API, DCR, and DCE. Use it to understand install steps, client setup, batching, error handling, async patterns, and practical usage with SKILL.md and references/examples.md.

The rank-tracker skill helps SEO teams monitor keyword positions, compare ranking snapshots, group terms by intent, and report SERP changes over time using built-in setup and analysis templates.

neon-postgres-egress-optimizer helps diagnose and reduce Postgres egress by using pg_stat_statements to find overfetching queries, validate measurement windows, and guide app-side fixes such as narrower selects, pagination, and ORM query changes.

performance-engineer is a structured skill for diagnosing bottlenecks, profiling slow systems, and validating fixes with baseline metrics, references, and helper scripts.

get-available-resources checks CPU, GPU, memory, and disk before heavy scientific or ML workflows. It returns a resource snapshot and practical recommendations for parallel processing, GPU acceleration, or memory-safe approaches, helping agents make better execution choices for workflow automation.

aws-cost-operations is an AWS cost and operations skill for estimating costs, reviewing bills, monitoring CloudWatch, checking CloudTrail, and guiding operational decisions. It is well suited for Finance, FinOps, platform teams, and operators who need verified AWS facts and decision-ready output.

observe-whatsapp helps diagnose WhatsApp operations in Kapso: message delivery, webhook retries, API errors, and number health. Use the observe-whatsapp skill to move from a failure signal to the right check fast, with CLI-first steps and API fallback for production troubleshooting.

azure-monitor-ingestion-py is a Python skill for sending custom logs to Azure Monitor Log Analytics with the Logs Ingestion API. It covers the required DCE, DCR, stream name, and authentication setup, making it useful for backend development, install planning, and practical usage with Azure monitoring workflows.

azure-ai-anomalydetector-java helps you build Azure AI Anomaly Detector workflows in Java for time-series monitoring, univariate and multivariate anomaly detection, and backend alerting. Use this skill when you need install-ready SDK guidance, client setup, authentication examples, and practical azure-ai-anomalydetector-java usage for production code.

azure-mgmt-applicationinsights-dotnet is the Azure Resource Manager SDK skill for .NET backend development. It helps you install and use Azure.ResourceManager.ApplicationInsights to create and manage Application Insights components, web tests, workbooks, analytics items, and API keys with clearer auth and environment setup.

datadog-cli helps agents run Datadog CLI workflows for logs, traces, metrics, services, and dashboards. Learn setup with DD_API_KEY and DD_APP_KEY, use npx @leoflores/datadog-cli commands, and handle --site plus dashboard update safety for incident triage.

ml-pipeline-workflow is a practical guide to designing end-to-end MLOps pipelines for data prep, training, validation, deployment, and monitoring, with orchestration patterns for repeatable workflow automation.

deployment-engineer is a CI/CD and release-planning skill for building deployment pipelines, drafting runbooks, and adding verification, rollback, and observability steps. Includes GitHub Actions examples, Kubernetes references, and helper scripts to generate and validate deployment plans.