AI Agent Skills

Monitor AI agent health, detect anomalies, set up alerting, and maintain observability dashboards for production multi-agent systems. Covers liveness checks, performance…

FIM is an Open Source Host-based file integrity monitoring tool that performs file system analysis, file integrity checking, real time alerting and provides Audit daemon…

Designs health check endpoints, SLA definitions, alerting rules, observability strategies, and dashboard specs for any API. Use whenever the user asks about API monitori…

Guides Qdrant monitoring setup including Prometheus scraping, health probes, Hybrid Cloud metrics, alerting, and log centralization. Use when someone asks 'how to set up…

17-dimension observability audit with tier activation, health scoring, and cost analysis. Covers logging, metrics, tracing, alerting, SLOs, profiling, security observabi…

Configure Harness AI-powered operations (AIDA) via MCP. Set up predictive failure analysis with ML models for memory leaks, disk exhaustion, connection pool sat

AWS cost optimization, monitoring, and operational excellence expert. Use when analyzing AWS bills, estimating costs, setting up CloudWatch alarms, querying logs, auditi…

Decision heuristics for interpreting Honeycomb SLO compliance, budget burn rates, and trigger status — what the numbers mean and what action to take, including detecting…

Master orchestrator for 57 official Datadog agent skills from DataDog/pup and datadog-labs/agent-skills. Use when working with ANY Datadog observability task: A

Workflow for implementing comprehensive monitoring and alerting. Use when the user needs to set up or improve service monitoring.

End-to-end passive reconnaissance for a domain, website or IP — builds an asset inventory covering registration, DNS, subdomains, infrastructure, tech stack, hi

Query Datadog observability data including logs, metrics, monitors, dashboards, hosts, APM spans, and incidents via direct API. Use when investigating production issues,…

Make an ML system a glass box with reproducible runs, MLflow dataset lineage, drift monitoring, alerting, and SHAP explanations. Use when a deployed model needs traceabi…