GitHub
observability-control
Manage observability stack lifecycle (start, stop, backup, restore, upgrade). Use when controlling the LGTM stack for Claude Code monitoring.
Skills IA tools monitoring
Découvrez les skills tools monitoring, comparez leurs dépôts et consultez leurs instructions.
Catégories: tools monitoring
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Explorer
GitHub
eks-observability
EKS observability with metrics, logging, and tracing. Use when setting up monitoring, configuring logging pipelines, implementing distributed tracing, building production dashboards, troubleshooting EKS issues,...
GitHub
skill-improvement-from-observability
Complete feedback loop from observability insights to skill updates. Use when analyzing enhanced telemetry patterns and automatically improving skills.
GitHub
observability-stack-setup
Automated LGTM + Alloy observability stack deployment using Docker Compose. Use when setting up Claude Code observability infrastructure locally.
GitHub
observability-railway-deploy
Deploy LGTM observability stack to Railway cloud. Use when deploying cloud-hosted observability with team access.
GitHub
project-observability-analyzer
Analyze projects and recommend observability integration. Use when adding observability to projects Claude Code works on.
GitHub
spring-boot-observability
Spring Boot 4 observability with Actuator, Micrometer, and OpenTelemetry. Use when configuring health indicators, custom metrics, distributed tracing, production endpoint exposure, or Kubernetes/Cloud Run probe...
GitHub
datadog-cli
Datadog CLI for debugging and triaging. Use this skill when you need to: search Datadog logs, query metrics, tail logs in real-time, trace distributed requests, investigate errors, compare time periods, find lo...
GitHub
observability
Observability - logging, metrics, tracing. Use when adding monitoring.
GitHub
observability
Observability - logging, metrics, tracing. Use when adding monitoring.
GitHub
plox
Plot timestamped logs as graphs. Use when user wants to visualize log data, plot numeric values over time, count events, track time deltas between events, compare multiple log files, or get statistics from logs...
GitHub
go-grpc
Build gRPC services with Go - protobuf, streaming, interceptors
GitHub
monitoring-observability
Prometheus, Grafana, logging, alerting, and data pipeline observability
GitHub
health-checker
Monitor database health and detect issues across environments
GitHub
comment-creator
Post comments to issues via Fractary CLI with optional FABER context tracking
GitHub
spec-initializer
Initialize spec plugin configuration
GitHub
log-analyzer
Extracts patterns, errors, and insights from operational logs using type-specific analysis templates
GitHub
infra-auditor
Audit infrastructure status, health, and compliance without modifications - provides observability and drift detection
GitHub
opentelemetry
OpenTelemetry observability - use for distributed tracing, metrics, instrumentation, Sentry integration, and monitoring
GitHub
error-tracking
Add Sentry v8 error tracking and performance monitoring to your project services. Use this skill when adding error handling, creating new controllers, instrumenting cron jobs, or tracking database performance....
GitHub
issue-logging-during-ralph-execution
Provides guidance for systematically logging issues during Ralph autonomous execution. Use when: (1) Any problem occurs during task execution, (2) Manual intervention is required, (3) Workflows don't work as ex...
GitHub
plausible
Implements privacy-friendly web analytics with Plausible as a Google Analytics alternative. Use when adding lightweight, cookie-free analytics that are GDPR compliant without consent banners.
GitHub
debugging
Analyzes stack traces, identifies log patterns, provides error solutions, and guides performance profiling, memory debugging, and distributed tracing. Use when debugging errors, analyzing logs, profiling perfor...
GitHub
sentry
Monitors applications with Sentry including error tracking, performance monitoring, and alerting. Use when tracking errors, monitoring performance, setting up alerts, or debugging production issues.
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.