发现 content media monitoring 相关 Skills，比较来源仓库和用途，查看适合你工作流的技能说明。
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...
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...
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...
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...
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...
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...
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...
Guides production deployment workflow with safety checks and rollback procedures. Use when deploying applications to staging or production environments.
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....
Comprehensive observability and monitoring workflow that orchestrates metrics collection, logging, distributed tracing, and alerting systems. Handles everything from monitoring architecture design and implement...
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...
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...
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.
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...
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.
Production deployment guidance for Quart applications including Docker, Hypercorn configuration, environment management, monitoring, and performance tuning. Activates when deploying or optimizing for production...
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...
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.
Automatically applies when implementing monitoring and alerting. Ensures proper metric instrumentation, alerts, SLO/SLI definition, dashboards, and observability patterns.
Automatically applies when logging sensitive data. Ensures PII (phone numbers, emails, IDs, payment data) is redacted in all logs and outputs for compliance.
Automatically applies when adding logging and observability. Ensures structured logging, OpenTelemetry tracing, LLM-specific metrics (tokens, cost, latency), and proper log correlation.
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...
Log parsing techniques and analysis methodologies for infrastructure troubleshooting. Use when retrieving, parsing, or analyzing logs from any platform.
Health monitoring knowledge and procedures for infrastructure platforms. Use when assessing system health, running health audits, or setting up monitoring.
默认按已收录数据中的 GitHub 仓库 Stars 排序。Stars 属于来源仓库，同一仓库的多个技能可能共享相同数值；它反映仓库关注度，不代表单个技能的安装量或质量评分。