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Found 381 Skills
This skill provides AWS cost optimization, monitoring, and operational best practices with integrated MCP servers for billing analysis, cost estimation, observability, and security assessment.
DigitalOcean management services for monitoring, uptime checks, and resource organization with Projects. Use when setting up observability, alerts, and operational visibility on DigitalOcean.
OpenTelemetry observability - use for distributed tracing, metrics, instrumentation, Sentry integration, and monitoring
You are a monitoring and observability expert specializing in implementing comprehensive monitoring solutions. Set up metrics collection, distributed tracing, log aggregation, and create insightful da
Create Post Incident Records (PIRs) by analysing incidents discovered from PagerDuty. Orchestrates pagerduty-oncall, datadog-analyser, and traffic-spikes-investigator skills to enrich each incident with observability and traffic data, auto-determines severity, and outputs completed PIR forms. Use when asked to "create a PIR", "write a post incident record", "fill out PIR form", "incident report", "analyse incidents", or after on-call shifts need documentation.
Axiom observability API for logs and analytics. Use when user mentions "logs", "query logs", "Axiom", or asks about event analytics.
Use this skill when implementing data validation, data quality monitoring, data lineage tracking, data contracts, or Great Expectations test suites. Triggers on schema validation, data profiling, freshness checks, row-count anomalies, column drift, expectation suites, contract testing between producers and consumers, lineage graphs, data observability, and any task requiring data integrity enforcement across pipelines.
Production-grade logging and observability patterns for ASP.NET Core Razor Pages. Covers structured logging with Serilog, correlation IDs, health checks, request logging, OpenTelemetry integration, and diagnostic best practices. Use when setting up structured logging in ASP.NET Core applications, implementing distributed tracing with OpenTelemetry, or configuring health checks and observability.
Grafana Cloud Application Observability (APM), Frontend Observability (RUM/Faro), and AI Observability. Covers RED metrics (Rate/Error/Duration), service maps, span metrics from traces, Faro JavaScript/React SDK for browser instrumentation, session replay, AI/LLM model monitoring, and integration with traces/logs/profiles for full-stack correlation. Use when setting up APM, configuring frontend monitoring, analyzing service performance, or monitoring AI/LLM applications.
Design carrier- and enterprise-scale backbone networks—core/distribution/edge topology, OSPF, IS-IS, BGP and route policy, WAN/MPLS/SD-WAN, DCI, peering, transit, IX, anycast, ECMP, BFD, FRR, addressing, backbone QoS, capacity, maintenance domains, and observability (NetFlow, SNMP, telemetry); EVPN/VXLAN spine-leaf where relevant. This skill should be used when the user asks about network backbone, backbone architect, BGP design, OSPF, IS-IS, WAN architecture, MPLS, SD-WAN, data center interconnect, DCI, internet peering, transit provider, IX, core network design, route policy, ECMP, network redundancy, spine-leaf, or EVPN—not app HTTP/API (enterprise-integration-api-developer), cloud landing zone or VPC only (cloud-architect, enterprise-cloud-architect), host or endpoint security (information-security-engineer), cloud/Linux sysadmin (cloud-system-administrator), cabling without routing (infrastructure-engineer), or OT/ICS (scada-ics-cyber-security-specialist).
Guides engineering of multi-agent systems—agent roles and specialization, orchestration topologies (supervisor, peer-to-peer, hierarchical, blackboard), task decomposition and routing, inter-agent messaging (A2A-style patterns), shared vs partitioned state, fan-out/fan-in and DAG workflows, synchronization and consensus, conflict resolution, fault tolerance and retries across agents, cost/latency/token budgets, cross-agent observability, testing multi-agent flows, and deployment (queues, durable workflows). Framework-agnostic; high-level LangGraph, Deep Agents, and agenthub—not single-agent loops (agentic-ai-developer), ML training (ai-engineer), strategy-only whiteboard (enterprise-strategist), or PM planning (technical-program-manager). Use for multi-agent system, multi-agent engineer, agent orchestration, supervisor agent, agent topology, fan-out fan-in, agent handoff protocol, multi-agent workflow, agent coordination, blackboard pattern, hierarchical agents, A2A, agent DAG, multi-agent architecture.
NVIDIA RAG Blueprint — deploy, configure, troubleshoot, and manage. Handles any RAG action: deploy, install, start, enable, disable, toggle, change, configure, troubleshoot, debug, fix, shutdown, stop, or tear down any RAG feature or service (VLM, guardrails, query rewriting, models, search, ingestion, observability, summarization, and more).