> monitoring-error-rates
This skill enables Claude to monitor and analyze application error rates to improve reliability. It is used when the user needs to track and understand errors occurring in their application, including HTTP errors, application exceptions, database errors, external API errors, background job errors, and client-side errors. Use this skill when the user asks to "monitor errors", "analyze error rates", "track application errors", or requests help with "error monitoring". It sets up comprehensive erro
curl "https://skillshub.wtf/jeremylongshore/claude-code-plugins-plus-skills/error-rate-monitor?format=md"Overview
This skill automates the process of setting up comprehensive error monitoring and alerting for various components of an application. It helps identify, track, and analyze different types of errors, enabling proactive identification and resolution of issues before they impact users.
How It Works
- Analyze Error Sources: Identifies potential error sources within the application architecture, including HTTP endpoints, database queries, external APIs, background jobs, and client-side code.
- Define Monitoring Criteria: Establishes specific error types and thresholds for each source, such as HTTP status codes (4xx, 5xx), exception types, query timeouts, and API response failures.
- Configure Alerting: Sets up alerts to trigger when error rates exceed defined thresholds, notifying relevant teams or individuals for investigation and remediation.
When to Use This Skill
This skill activates when you need to:
- Set up error monitoring for a new application.
- Analyze existing error rates and identify areas for improvement.
- Configure alerts to be notified of critical errors in real-time.
- Establish error budgets and track progress towards reliability goals.
Examples
Example 1: Setting up Error Monitoring for a Web Application
User request: "Monitor errors in my web application, especially 500 errors and database connection issues."
The skill will:
- Analyze the web application's architecture to identify potential error sources (e.g., HTTP endpoints, database connections).
- Configure monitoring for 500 errors and database connection failures, setting appropriate thresholds and alerts.
Example 2: Analyzing Error Rates in a Background Job Processor
User request: "Analyze error rates for my background job processor. I'm seeing a lot of failed jobs."
The skill will:
- Focus on the background job processor and identify the types of errors occurring (e.g., task failures, timeouts, resource exhaustion).
- Analyze the frequency and patterns of these errors to identify potential root causes.
Best Practices
- Granularity: Monitor errors at a granular level to identify specific problem areas.
- Thresholding: Set appropriate alert thresholds to avoid alert fatigue and focus on critical issues.
- Context: Include relevant context in error messages and alerts to facilitate troubleshooting.
Integration
This skill can be integrated with other monitoring and alerting tools, such as Prometheus, Grafana, and PagerDuty, to provide a comprehensive view of application health and performance. It can also be used in conjunction with incident management tools to streamline incident response workflows.
> related_skills --same-repo
> agent-context-loader
PROACTIVE AUTO-LOADING: Automatically detects and loads AGENTS.md files from the current working directory when starting a session or changing directories. This skill ensures agent-specific instructions are incorporated into Claude Code's context alongside CLAUDE.md, enabling specialized agent behaviors. Triggers automatically when Claude detects it's working in a directory, when starting a new session, or when explicitly requested to "load agent context" or "check for AGENTS.md file".
> Google Cloud Agent SDK Master
Automatic activation for ALL Google Cloud Agent Development Kit (ADK) and Agent Starter Pack operations - multi-agent systems, containerized deployment, RAG agents, and production orchestration. **TRIGGER PHRASES:** - "adk", "agent development kit", "agent starter pack", "multi-agent", "build agent" - "cloud run agent", "gke deployment", "agent engine", "containerized agent" - "rag agent", "react agent", "agent orchestration", "agent templates" **AUTO-INVOKES FOR:** - Agent creation and scaffold
> Vertex AI Media Master
Automatic activation for ALL Google Vertex AI multimodal operations - video processing, audio generation, image creation, and marketing campaigns. **TRIGGER PHRASES:** - "vertex ai", "gemini multimodal", "process video", "generate audio", "create images", "marketing campaign" - "imagen", "video understanding", "multimodal", "content generation", "media assets" **AUTO-INVOKES FOR:** - Video processing and understanding (up to 6 hours) - Audio generation and transcription - Image generation with I
> yaml-master
PROACTIVE YAML INTELLIGENCE: Automatically activates when working with YAML files, configuration management, CI/CD pipelines, Kubernetes manifests, Docker Compose, or any YAML-based workflows. Provides intelligent validation, schema inference, linting, format conversion (JSON/TOML/XML), and structural transformations with deep understanding of YAML specifications and common anti-patterns.