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grafana
Grafana dashboard and alert management
Skills IA content media monitoring
Découvrez les skills content media monitoring, comparez leurs dépôts et consultez leurs instructions.
Catégories: content media monitoring
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datadog
Datadog monitoring and observability with native dogshell CLI integration
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sentry
Queries Sentry for issues, events, traces, and error analysis. Use when debugging production errors, searching issues, analyzing traces, or getting AI root cause analysis with Seer.
GitHub
pop-routine-measure
Display routine measurement dashboard with metrics, costs, trends, and visualization
GitHub
metrics-monitoring
Implement application metrics (RED, USE), alerting strategies, and monitoring dashboards
GitHub
logging-strategies
Implement structured logging with appropriate levels, context, and correlation for effective debugging and monitoring
GitHub
structured-logging
Apply structured logging best practices using Pino for Node.js applications: JSON output, log levels, context, redaction, correlation IDs, and centralization. Use when implementing logging, reviewing log statem...
GitHub
verify-fix
Mandatory incident fix verification with observables. Invoke after: applying production fixes, before declaring incidents resolved, when someone says 'I think that fixed it'. Requires log entries, metric change...
GitHub
observability
Logging, debugging, profiling, and performance monitoring for development. Use when adding logging, debugging issues, profiling performance, or instrumenting code for observability.
GitHub
go-error-handling
Use when implementing Go error handling with error wrapping, sentinel errors, and custom error types. Use when handling errors in Go applications.
GitHub
agentuity-cli-profile-create
Create a new configuration profile
GitHub
agentuity-cli-profile-create
Create a new configuration profile
GitHub
grafana-billing
Query Prometheus and Loki billing metrics from Grafana. Use when discussing observability costs, active series, ingestion rates, storage usage, or cardinality analysis.
GitHub
site-reliability-engineer
Production monitoring, observability, SLO/SLI management, and incident response. Trigger terms: monitoring, observability, SRE, site reliability, alerting, incident response, SLO, SLI, error budget, Prometheus...
GitHub
sentry-monitor
Sentry error monitoring and user behavior tracking via CLI. Use when: (1) debugging user-reported issues, (2) checking recent errors/crashes, (3) tracing user actions before an error occurred, (4) searching iss...
GitHub
dapr-observability-setup
Configure OpenTelemetry tracing, metrics, and structured logging for DAPR applications. Integrates with Azure Monitor, Jaeger, Prometheus, and other observability backends.
GitHub
dapr-config-validator
Automatically validate DAPR configuration files (dapr.yaml, component YAML files) when they are created or modified. Checks for schema compliance, missing required fields, invalid values, and common misconfigur...
GitHub
dapr-troubleshooter
Proactively detect and diagnose DAPR runtime issues based on error patterns, log analysis, and common misconfigurations. Provides immediate solutions for service invocation failures, state management issues, pu...
GitHub
distributed-tracing
Comprehensive distributed tracing with Jaeger, Zipkin, OpenTelemetry, correlation IDs, and span design.
GitHub
observability
Production observability with structured logging, metrics collection, distributed tracing, and alerting
GitHub
orchestrating-with-kubernetes
The agent implements Kubernetes container orchestration with deployments, services, Helm charts, and production patterns. Use when deploying containerized applications, configuring autoscaling, managing secrets...
GitHub
service-mesh
Advanced service mesh implementation with Istio, Linkerd, traffic management, mTLS, and observability.
GitHub
semantic-searchstatus
Use when you want to check semantic search server status, indexing progress, or watcher state
GitHub
observability-monitoring
Structured logging, metrics, distributed tracing, and alerting strategies
Le classement utilise les étoiles du dépôt GitHub indexé. Plusieurs skills peuvent partager ce nombre : ce n’est ni un nombre d’installations ni une note de qualité.