GitHub
slo-designer
Design Service Level Objectives (SLOs) with SLIs, targets, alerting thresholds, and error budget calculations following Google SRE best practices. Use when defining reliability targets, designing SLOs, calculat...
Skills IA content media monitoring
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GitHub
metrics
Collect and report metrics on agent usage from git history implementing the 8 key metrics defined in agent-metrics.md for measuring agent system health effectiveness and adoption.
GitHub
python-logging-best-practices
Unified Python logging patterns with loguru, platformdirs, RotatingFileHandler. TRIGGERS - loguru, platformdirs, structured logging, JSONL logs, log rotation, XDG directories, python logging setup, machine read...
GitHub
multi-agent-performance-profiling
Multi-agent parallel performance profiling workflow for identifying bottlenecks in data pipelines. Use when investigating performance issues, optimizing ingestion pipelines, profiling database operations, or di...
GitHub
grafana-loki-logcli
Query and explore logs in Grafana Loki via the logcli command-line tool. Use when a user asks to pull logs for analysis.
GitHub
grafana-tempo-query
Query and explore distributed traces in Grafana Tempo. Use when a user asks to pull tracing data for analysis.
GitHub
devops-deployment
Manages deployment, infrastructure, and observability. Use when deploying with PM2, Helmfile/K8s, configuring databases, or setting up Prometheus/Grafana monitoring.
GitHub
observability-with-prometheus-grafana
Production-grade observability stack with Prometheus metrics, Grafana dashboards, PromQL query language, alerting rules, and AI-powered anomaly detection for modern cloud-native applications
GitHub
sentry-setup-metrics
Setup Sentry Metrics in any project. Use when asked to add custom metrics, track counters/gauges/distributions, or instrument application performance. Supports JavaScript and Python.
GitHub
sentry-ruby-setup
Setup Sentry in Ruby apps. Use when asked to add Sentry to Ruby, install sentry-ruby gem, or configure error monitoring for Ruby applications or Rails.
GitHub
sentry-setup-tracing
Setup Sentry Tracing (Performance Monitoring) in any project. Use when asked to enable tracing, track transactions/spans, measure latency, or add performance monitoring. Supports JavaScript, Python, and Ruby.
GitHub
sentry-setup-logging
Setup Sentry Logging in any project. Use when asked to add Sentry logs, enable structured logging, capture console logs, or integrate logging libraries (Pino, Winston, Loguru) with Sentry. Supports JavaScript,...
GitHub
senior-observability
Comprehensive observability skill for monitoring, logging, distributed tracing, alerting, and SLI/SLO implementation across distributed systems. Includes dashboard generation, alert rule creation, error budget...
GitHub
backend-pino
High-performance structured JSON logging for Node.js. Use when building production APIs that need fast, structured logs for observability platforms (Datadog, ELK, CloudWatch). Provides request logging middlewar...
GitHub
application-insights-instrumentation
Automates the integration of Azure Application Insights telemetry into web applications for monitoring, diagnostics, and performance tracking
GitHub
observability-monitoring
Structured logging, metrics, distributed tracing, and alerting strategies
GitHub
sentry-setup
Configure Sentry for error tracking, performance monitoring, and log aggregation. Integrates with Pino to forward logs to Sentry automatically.
GitHub
observability-monitoring
Complete observability stack with structured logging, error tracking, and web analytics.
GitHub
using-sentry
Capture exceptions, add context, create performance spans, and use structured logging with Sentry.
GitHub
using-logging
Use structured logging with Pino throughout your application. Covers log levels, context, and workflow-safe logging patterns.
GitHub
pino-logging-setup
Configure structured logging with Pino. Outputs human-readable colorized logs in development and structured JSON in production for log aggregation services.
GitHub
python-observability-patterns
Observability patterns for Python applications. Triggers on: logging, metrics, tracing, opentelemetry, prometheus, observability, monitoring, structlog, correlation id.
GitHub
tzurot-observability
Contains MANDATORY logging and debugging patterns for Tzurot v3. MUST be consulted before adding logs or debugging production. Covers structured logging, correlation IDs, and Railway log analysis.
GitHub
devtools
Use CDP at localhost:9222 to test/debug websites, automate browser tasks
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.