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 error tracking and alerting based on defined thresholds.
Installation
Details
Usage
After installing, this skill will be available to your AI coding assistant.
Verify installation:
skills listSkill Instructions
name: monitoring-error-rates description: | 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 error tracking and alerting based on defined thresholds. allowed-tools: Read, Bash, Grep, Glob version: 1.0.0
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.
More by jeremylongshore
View allRabbitmq Queue Setup - Auto-activating skill for Backend Development. Triggers on: rabbitmq queue setup, rabbitmq queue setup Part of the Backend Development skill category.
evaluating-machine-learning-models: This skill allows Claude to evaluate machine learning models using a comprehensive suite of metrics. It should be used when the user requests model performance analysis, validation, or testing. Claude can use this skill to assess model accuracy, precision, recall, F1-score, and other relevant metrics. Trigger this skill when the user mentions "evaluate model", "model performance", "testing metrics", "validation results", or requests a comprehensive "model evaluation".
building-neural-networks: This skill allows Claude to construct and configure neural network architectures using the neural-network-builder plugin. It should be used when the user requests the creation of a new neural network, modification of an existing one, or assistance with defining the layers, parameters, and training process. The skill is triggered by requests involving terms like "build a neural network," "define network architecture," "configure layers," or specific mentions of neural network types (e.g., "CNN," "RNN," "transformer").
Oauth Callback Handler - Auto-activating skill for API Integration. Triggers on: oauth callback handler, oauth callback handler Part of the API Integration skill category.
