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Found 356 Skills
Build production-ready gRPC services in Go with mTLS, streaming, and observability. Use when designing Protobuf contracts with Buf or implementing secure service-to-service transport.
Create and manage SLOs in Elastic Observability using the Kibana API. Use when defining SLIs, setting error budgets, or managing SLO lifecycle.
Set up and use Dstl8 for observability. Triggers: install or configure Dstl8 (CLI, sources, MCP); incident triage and investigation; root cause analysis; checking whether a deploy fixed an issue; alerting on recurring patterns; cross-environment correlation; pre-coding context on past incidents and recent issues.
Design and run a monitoring system for a website or web app. Use this skill when setting up uptime checks, defining SLOs, configuring error tracking, choosing what to alert on, designing on-call rotations, or fixing alert fatigue. Triggers on monitoring, alerts, uptime, SLO, SLA, error rate, on-call, pager, alert fatigue, observability, dashboards, what should we monitor. Also triggers when an incident reveals a gap in monitoring.
Generate, write, or run an ad-hoc query against SigNoz observability data — metrics, logs, traces, or exceptions — without wrapping it in a dashboard panel or alert. Make sure to use this skill whenever the user asks "show me error rates", "query logs for timeout errors", "what's the p99 latency for the cart service", "how many requests hit the payment endpoint", "find slow traces", "errors in the last hour", or otherwise asks an exploratory question that needs live observability data — even if they don't say "query" or "search" explicitly.
Design enterprise-grade agent systems with Microsoft's agent framework patterns: role separation, workflow control, policy boundaries, and observability. Use when users need robust organizational agent workflows, governance, and maintainable multi-agent architecture.
Design, audit, and refactor production-safe agentic harnesses with provider-neutral best practices for tools, permissions, planning, context, and observability.
Optimize end-to-end application performance with profiling, observability, and backend/frontend tuning. Use when coordinating performance optimization across the stack.
Query Langfuse traces for debugging LLM calls, analyzing token usage, and investigating workflow executions. Use when debugging AI/LLM behavior, checking trace data, or analyzing observability metrics.
Postgres-backed observability and policy store for the skill system. Provides tables for policy profiles (effect allowlists), skill execution runs, and step-level events. Use when setting up the skill system database or querying execution history.
Implement distributed tracing using logs, including trace context propagation, span logging, correlation IDs, and OpenTelemetry integration for observability
Orchestrate multi-service AWS workflows with autonomous agents. Coordinates across compute, storage, identity, and observability services for intelligent cloud automation.