observability AI Agent Skills

phoenix-observability

21.8k

davila7

Open-source AI observability platform for LLM tracing, evaluation, and monitoring. Use when debugging LLM applications with detailed traces, running evaluations on datasets, or monitoring production AI systems with real-time insights.

langsmith-observability

21.8k

davila7

LLM observability platform for tracing, evaluation, and monitoring. Use when debugging LLM applications, evaluating model outputs against datasets, monitoring production systems, or building systematic testing pipelines for AI applications.

sentry-desktop-setup

376

a5c-ai

Configure Sentry for comprehensive desktop application crash reporting, error monitoring, performance tracking, and release health for Electron and native desktop apps

observability-testing-patterns

215

proffesor-for-testing

Observability and monitoring validation patterns for dashboards, alerting, log aggregation, APM traces, and SLA/SLO verification. Use when testing monitoring infrastructure, dashboard accuracy, alert rules, or metric pipelines.

Logging Patterns

127

Dicklesworthstone

Common logging patterns and practices. This skill is designed to be included in composite skills via the 'includes' feature.

monitoring-observability

97

yonatangross

Monitoring and observability patterns for Prometheus metrics, Grafana dashboards, Langfuse LLM tracing, and drift detection. Use when adding logging, metrics, distributed tracing, LLM cost tracking, or quality drift monitoring.

OpenTelemetry Testing

71

PramodDutta

Testing distributed tracing and observability instrumentation with OpenTelemetry including span verification, metric collection, and log correlation.

Testing in Production Patterns

71

PramodDutta

Safe testing-in-production strategies including feature flags, shadow traffic, canary releases, dark launches, and observability-driven development.

Sentry Error Monitoring & Testing

71

PramodDutta

Integration testing with Sentry for error tracking, performance monitoring, and release health verification in production environments.

dag-performance-profiler

43

curiositech

Profiles DAG execution performance including latency, token usage, cost, and resource consumption. Identifies bottlenecks and optimization opportunities. Activate on 'performance profile', 'execution metrics', 'latency analysis', 'token usage', 'cost analysis'. NOT for execution tracing (use dag-execution-tracer) or failure analysis (use dag-failure-analyzer).

dag-failure-analyzer

43

curiositech

Performs root cause analysis on DAG execution failures. Traces failure propagation, identifies systemic issues, and generates actionable remediation guidance. Activate on 'failure analysis', 'root cause', 'why did it fail', 'debug failure', 'error investigation'. NOT for execution tracing (use dag-execution-tracer) or performance issues (use dag-performance-profiler).

dag-execution-tracer

43

curiositech

Traces complete execution paths through DAG workflows. Records timing, inputs, outputs, and state transitions for all nodes. Activate on 'execution trace', 'trace execution', 'execution path', 'debug execution', 'execution log'. NOT for performance analysis (use dag-performance-profiler) or failure investigation (use dag-failure-analyzer).

dag-pattern-learner

43

curiositech

Learns from DAG execution history to improve future performance. Identifies successful patterns, detects anti-patterns, and provides recommendations. Activate on 'learn patterns', 'execution patterns', 'what worked', 'optimize based on history', 'pattern analysis'. NOT for failure analysis (use dag-failure-analyzer) or performance profiling (use dag-performance-profiler).

golang-observability-opentelemetry

15

bobmatnyc

Instrumenting Go applications with OpenTelemetry for distributed tracing, Prometheus for metrics, and structured logging with slog

golang-grpc

15

bobmatnyc

Production gRPC in Go: protobuf layout, codegen, interceptors, deadlines, error codes, streaming, health checks, TLS, and testing with bufconn

OpenTelemetry

15

bobmatnyc

OpenTelemetry observability patterns: traces, metrics, logs, context propagation, OTLP export, Collector pipelines, and troubleshooting

Datadog Observability

15

bobmatnyc

Full-stack observability with Datadog APM, logs, metrics, synthetics, and RUM. Use when implementing monitoring, tracing, alerting, or cost optimization for production systems.

monitoring-observability

13

williamzujkowski

Master monitoring and observability for distributed systems

service-mesh

13

williamzujkowski

A service mesh is an infrastructure layer that provides transparent service-to-service communication with built-in observability, traffic management, and security features without requiring application code changes.

aws-advanced-patterns

13

williamzujkowski

Orchestration & Events:

Observability with Prometheus & Grafana

10

bobmatnyc

Production-grade observability stack with Prometheus metrics, Grafana dashboards, PromQL query language, alerting rules, and AI-powered anomaly detection for modern cloud-native applications

logging-and-monitoring

7

louloulin

Comprehensive logging, monitoring, and observability expert for distributed systems

implementing-runtime-security-with-tetragon

2

mukul975

Implement eBPF-based runtime security observability and enforcement in Kubernetes clusters using Cilium Tetragon for kernel-level threat detection and policy enforcement.

Agent Dashboard

1

hanabi-jpn

Real-time agent monitoring with health scoring, cost tracking, and web dashboard

newrelic-cli-skills

vince-winkintel

Monitor, query, and manage New Relic observability data via the newrelic CLI. Covers NRQL queries, APM performance triage, deployment markers, alert management, infrastructure monitoring, and agent diagnostics. Use when user asks about application performance, error rates, slow transactions, deployment tracking, or New Relic configuration.

senior-observability

arielperez82

Comprehensive observability skill for monitoring, logging, distributed tracing, alerting, and SLI/SLO implementation across distributed systems. Includes dashboard generation, alert rule creation, error budget calculation, and metrics analysis. Use when implementing monitoring stacks, designing alerting strategies, setting up distributed tracing, or defining SLO frameworks.