When should I trigger this skill?

You should trigger this skill whenever you need to troubleshoot performance issues, identify the root cause of recurring errors, or gain a high-level summary of system health.

How does the Log Analysis Tool identify slow requests?

It scans log files for timestamps and duration metrics, flagging any entries that exceed predefined latency thresholds to highlight performance bottlenecks.

Does it support JSON-formatted logs?

While it works with various log formats, implementing structured logging like JSON is highly recommended to facilitate more efficient and accurate analysis by the tool.

Can this skill handle large log files?

Yes, it utilizes efficient command-line tools like Grep and Bash to parse and filter log data directly within your environment, ensuring performance even with large datasets.

Log Analysis Tool

Name: Log Analysis Tool
Author: intent-solutions-io

byintent-solutions-io

Analíticas y Monitorización

Analyzes application logs to automatically identify performance bottlenecks, recurring error patterns, and resource usage anomalies.

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This skill empowers Claude to perform deep-dive log inspections, streamlining the debugging process by automatically extracting insights like slow request durations and frequent exception patterns. By leveraging tools like Grep and Bash, it transforms raw log data into actionable reports, helping developers optimize application stability and performance without manual parsing. It is particularly useful for troubleshooting latency issues, identifying systemic errors in production or staging environments, and establishing better observability patterns.

Características Principales

Automated performance bottleneck identification
Summary report generation with actionable insights
Extraction of resource usage metrics and warnings
Recurring error and exception pattern detection
Support for latency threshold analysis and slow request tracking
0 GitHub stars

Casos de Uso

Auditing application logs to find and resolve slow-loading API endpoints
Monitoring resource exhaustion warnings to prevent system downtime
Debugging intermittent production errors through log pattern analysis

Acerca de

Características Principales

Automated performance bottleneck identification
Summary report generation with actionable insights
Extraction of resource usage metrics and warnings
Recurring error and exception pattern detection
Support for latency threshold analysis and slow request tracking
0 GitHub stars

Casos de Uso

Auditing application logs to find and resolve slow-loading API endpoints
Monitoring resource exhaustion warnings to prevent system downtime
Debugging intermittent production errors through log pattern analysis