GitHub
detecting-anomalies
Detect anomalies in metrics and time-series data using OPAL statistical methods. Use when you need to identify unusual patterns, spikes, drops, or outliers in observability data. Covers statistical outlier dete...
Skills IA content media monitoring
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GitHub
analyzing-apm-data
Monitor application performance using the RED methodology (Rate, Errors, Duration) with Observe. Use when analyzing service health, investigating errors, tracking latency, or building APM dashboards. Covers whe...
GitHub
analyzing-tdigest-metrics
Analyze percentile metrics (tdigest type) using OPAL for latency analysis and SLO tracking. Use when calculating p50, p95, p99 from pre-aggregated duration or latency metrics. Covers the critical double-combine...
GitHub
aggregating-gauge-metrics
Aggregate pre-computed metrics (gauge, counter, delta types) using OPAL. Use when analyzing request counts, error rates, resource utilization, or any numeric metrics over time. Covers align + m() + aggregate pa...
GitHub
time-series-analysis
Analyze event datasets (logs) and intervals over time using OPAL timechart. Use when you need to visualize trends, track metrics over time, or create time-series charts. Covers timechart for temporal binning, b...
GitHub
datadog-auto-detector
Automatically detects Datadog resource mentions (URLs, service queries, natural language) and intelligently fetches condensed context via datadog-analyzer subagent when needed for the conversation (plugin:schov...
GitHub
mz-configure-loki-logging
Configure Grafana Loki logging using mazza-base library for Python/Flask applications with CA certificate (Mazza-specific). Use when setting up Loki logging for Mazza projects or configuring centralized logging...
GitHub
deployment-workflow
Guides production deployment workflow with safety checks and rollback procedures. Use when deploying applications to staging or production environments.
GitHub
aiwferror-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
observability-monitor
Comprehensive observability and monitoring workflow that orchestrates metrics collection, logging, distributed tracing, and alerting systems. Handles everything from monitoring architecture design and implement...
GitHub
dev-log-monitoring
This skill should be used when testing ScreenGraph end-to-end flows (drift detection, agent runs) while monitoring backend and frontend logs in real-time. Use when the user wants to observe system behavior acro...
GitHub
debugging-omnistrate-deployments
Systematically debug failed Omnistrate instance deployments using a progressive workflow that identifies root causes efficiently while avoiding token limits. Applies to deployment failures, probe issues, and he...
GitHub
sbt-benchmark
Use PROACTIVELY for JMH benchmarks in this Spark protobuf project. Handles sbt commands, always cleans before benchmarking, saves output to /tmp logs, and uses log-reader agent to parse results.
GitHub
sentry-monitor
Monitor production errors using Sentry MCP. Query errors, analyze patterns, create issues, and verify error tracking is working. Use after deployment, when debugging production issues, or when verifying Sentry...
GitHub
administration
How to monitor usage, track costs, configure analytics, and measure ROI for Claude Code. Use when user asks about monitoring, telemetry, metrics, costs, analytics, or OpenTelemetry.
GitHub
deployment-guide
Production deployment guidance for Quart applications including Docker, Hypercorn configuration, environment management, monitoring, and performance tuning. Activates when deploying or optimizing for production...
GitHub
debugging-kubernetes-incidents
Use when investigating Kubernetes pod failures, crashes, resource issues, or service degradation. Provides systematic investigation methodology for incident triage, root cause analysis, and remediation planning...
GitHub
generate-report-header
Create standardized report headers with metadata for all agent-generated reports. Use when generating bug reports, security audits, dependency reports, or any worker output requiring consistent formatting.
GitHub
monitoring-alerting
Automatically applies when implementing monitoring and alerting. Ensures proper metric instrumentation, alerts, SLO/SLI definition, dashboards, and observability patterns.
GitHub
pii-redaction
Automatically applies when logging sensitive data. Ensures PII (phone numbers, emails, IDs, payment data) is redacted in all logs and outputs for compliance.
GitHub
observability-logging
Automatically applies when adding logging and observability. Ensures structured logging, OpenTelemetry tracing, LLM-specific metrics (tokens, cost, latency), and proper log correlation.
GitHub
databuddy-node
Use the Databuddy Node.js SDK for server-side tracking with batching, middleware, and deduplication. Use when implementing analytics in Node.js servers, API routes, serverless functions, or when you need server...
GitHub
log-analysis
Log parsing techniques and analysis methodologies for infrastructure troubleshooting. Use when retrieving, parsing, or analyzing logs from any platform.
GitHub
health-checks
Health monitoring knowledge and procedures for infrastructure platforms. Use when assessing system health, running health audits, or setting up monitoring.
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.