How does this skill detect slow requests?

It identifies requests that exceed predefined latency thresholds recorded in your application logs and presents a list with corresponding timestamps.

When should I trigger this skill?

Trigger it whenever you need to debug recurring errors, analyze system trends, or investigate why an application is performing slowly.

Can it handle structured logging formats like JSON?

Yes, it is designed to work efficiently with structured logging, which facilitates faster data extraction and pattern identification.

What is the primary benefit of using this log analysis skill?

It automates the tedious task of manual log parsing, allowing developers to quickly pinpoint the root cause of errors and performance bottlenecks.

Does it support log aggregation tools?

Yes, the skill is optimized for environments where log aggregation and structured logging are implemented for high-scale observability.

Log Analysis & Performance Troubleshooting

Name: Log Analysis & Performance Troubleshooting
Author: BbgnsurfTech

byBbgnsurfTech

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Analytics & Monitoring

Analyzes application logs to identify performance bottlenecks, recurring error patterns, and system anomalies for improved stability.

About

This skill empowers Claude to perform deep dives into application logs, automating the detection of slow requests, recurring exceptions, and resource exhaustion warnings. By extracting key metrics and timestamps from raw log data, it provides actionable insights into system health, helping developers streamline the debugging process and optimize application performance without manual parsing. Whether you are troubleshooting a production crash or fine-tuning latency, this tool offers structured reports to guide your optimization efforts.

Key Features

Automatic identification of slow requests and latency thresholds
Integration-ready analysis for structured and aggregated logging
Pattern matching for recurring error messages and stack traces
1 GitHub stars
Extraction of KPIs including timestamps and resource usage metrics
Automated summary report generation for performance optimization

Use Cases

Debugging production applications experiencing intermittent performance drops
Identifying the root cause of recurring server errors and exceptions
Auditing system logs for resource usage warnings and anomalies

About

Key Features

Automatic identification of slow requests and latency thresholds
Integration-ready analysis for structured and aggregated logging
Pattern matching for recurring error messages and stack traces
1 GitHub stars
Extraction of KPIs including timestamps and resource usage metrics
Automated summary report generation for performance optimization

Use Cases

Debugging production applications experiencing intermittent performance drops
Identifying the root cause of recurring server errors and exceptions
Auditing system logs for resource usage warnings and anomalies