Imported from jeremylongshore/tons-of-skills-marketplace (skills/.curated/tracking-application-response-times/SKILL.md). Install upstream with npx skills add jeremylongshore/tons-of-skills-marketplace --skill tracking-application-response-times. Copyright stays with the author (MIT).

Response Time Tracker

Name: tracking-application-response-times
Author: jeremylongshore

Track and analyze response times across API endpoints, database queries, and service calls with P50/P95/P99 percentile reporting and SLO compliance monitoring.

Overview

This skill empowers Claude to proactively monitor and improve application performance by tracking response times across various layers. It provides detailed metrics and insights to identify and resolve performance bottlenecks.

How It Works

Initiate Tracking: The user requests response time tracking.
Configure Monitoring: The plugin automatically begins monitoring API endpoints, database queries, external service calls, frontend rendering, and background jobs.
Report Metrics: The plugin generates reports including P50, P95, P99 percentiles, average, and maximum response times.

When to Use This Skill

This skill activates when you need to:

Identify performance bottlenecks in your application.
Monitor service level objectives (SLOs) related to response times.
Receive alerts about performance degradation.

Examples

Example 1: Diagnosing Slow API Endpoint

User request: "Track response times for the user authentication API endpoint."

The skill will:

Activate the response-time-tracker plugin.
Monitor the specified API endpoint and report response time metrics, highlighting potential bottlenecks.

Example 2: Monitoring Database Query Performance

User request: "Monitor database query performance for the product catalog."

The skill will:

Activate the response-time-tracker plugin.
Track the execution time of database queries related to the product catalog and provide performance insights.

Best Practices

Granularity: Track response times at a granular level (e.g., individual API endpoints, specific database queries) for more precise insights.
Alerting: Configure alerts for significant deviations from baseline performance to proactively address potential issues.
Contextualization: Correlate response time data with other metrics (e.g., CPU usage, memory consumption) to identify root causes.

Integration

This skill can be integrated with other monitoring and alerting tools to provide a comprehensive view of application performance. It can also be used in conjunction with optimization tools to automatically address identified bottlenecks.

Prerequisites

Access to application monitoring infrastructure
Response time data collection in ${CLAUDE_SKILL_DIR}/metrics/response-times/
APM tools or custom instrumentation
Performance SLO definitions

Instructions

Configure monitoring for API endpoints and database queries
Collect response time metrics (P50, P95, P99 percentiles)
Analyze trends and identify performance degradation
Compare against performance baselines and SLOs
Identify bottlenecks and root causes
Generate optimization recommendations

Output

Response time reports with percentile metrics
Performance trend visualizations
Bottleneck identification analysis
SLO compliance status
Optimization recommendations with priorities

Error Handling

If response time tracking fails:

Verify monitoring agent installation
Check instrumentation configuration
Validate metric export endpoints
Ensure data storage availability
Review sampling configuration

Resources

APM tool documentation
Response time monitoring best practices
Percentile-based SLO definitions
Performance optimization guides

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tracking-application-response-times

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