analytics & monitoring向けのClaudeスキルを発見してください。47個のスキルを閲覧し、AIワークフローに最適な機能を見つけましょう。
Streamlines the process of adding new AI agent cost and token usage trackers to the Splitrail monitoring system.
Monitors execution workflows for errors and inefficiencies to automatically generate actionable GitHub issues for improvements.
Visualizes Claude Code agent team interactions and session logs in a self-contained HTML dashboard.
Provides guidance for managing terminal UI components and real-time token usage tracking logic within the Splitrail ecosystem.
Queries and visualizes local usage metrics across projects to track agent performance, model costs, and development trends.
Implements comprehensive infrastructure monitoring, LLM tracing, and drift detection patterns to ensure production-grade system reliability.
Optimizes full-stack application performance using modern patterns for Core Web Vitals, React rendering, and high-throughput LLM inference.
Optimizes application speed across frontend Core Web Vitals, React rendering, backend profiling, and LLM inference efficiency.
Implements comprehensive monitoring, LLM tracing, and drift detection patterns for production-ready AI applications.
Analyzes local OrchestKit usage data to provide detailed insights into agent performance, model costs, and development trends.
Monitors and analyzes student engagement, retention, and completion metrics to optimize educational outcomes.
Implements structured logging, diagnostic error patterns, and robust observability for React and React Native applications.
Audits architectural patterns against industry best practices while tracking structural health and drift over time.
Measures software quality through actionable DORA metrics, bug escape rates, and automated quality gate enforcement.
Implements comprehensive monitoring, alerting, and observability systems using industry-standard SRE best practices and metrics.
Generates detailed visual reports and usage statistics from your Claude Code interaction history.
Instruments web applications to send telemetry data to Azure Application Insights for comprehensive observability and monitoring.
Diagnoses and resolves Azure production issues using AI-powered diagnostics, log analysis, and system health checks.
Monitors and analyzes Azure resource health using Azure Monitor, Application Insights, and advanced KQL log queries.
Queries and analyzes big data in Azure Data Explorer using Kusto Query Language (KQL) for logs, telemetry, and time series insights.
Implements and enforces comprehensive Sentry v8 error tracking and performance monitoring across TypeScript and Node.js services.
Enhances the Claude Code interface with customizable, multi-line statuslines featuring real-time cost tracking and Git indicators.
Enhances code observability by inserting purposeful, non-intrusive debug logs into critical execution paths.
Measures and optimizes the time between user taps and action completion in mobile applications.
Instruments mobile API requests with distributed tracing and performance spans to monitor latency and correlate client-side issues with backend logs.
Instruments mobile user flows with intent context and friction signals to pinpoint exactly where and why users fail in multi-step processes.
Implements full-stack observability with Sentry to track application performance, distributed tracing, and real-time metrics.
Configures automated Sentry alerts, triages software issues, and manages cross-platform notification workflows to maintain system reliability.
Captures, enriches, and manages application errors using Sentry to improve observability and debugging efficiency.
Standardizes production incident management with specialized playbooks for on-call engineering and post-mortem documentation.
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