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log-analyzer

Analyze log files to extract patterns, errors, and statistics.

1|Updated Feb 25, 2026
Search Tags:#troubleshooting#logs#analysis#patterns#statistics#errors
One-click install
npx skills add https://github.com/winsorllc/upgraded-carnival --skill log-analyzer-winsorllc
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: log-analyzer
Source: https://github.com/winsorllc/upgraded-carnival/tree/main/.pi/skills/log-analyzer
Command: npx skills add https://github.com/winsorllc/upgraded-carnival --skill log-analyzer-winsorllc

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

This Skill helps you quickly parse and analyze log files to identify patterns, errors, and statistics, making troubleshooting and performance monitoring more efficient.

Core Features & Use Cases

  • Pattern Detection: Find specific errors or recurring events within log data.
  • Statistical Analysis: Generate summaries, count log levels, and identify top occurrences.
  • Log Format Handling: Supports common formats like Apache, Nginx, JSON, Syslog, and custom regex.
  • Use Case: Quickly find all 'Connection refused' errors in your application logs from the last 24 hours and count their occurrences.

Quick Start

Analyze the log file named 'app.log' and show a summary of its contents.

Frequently Asked Questions about log-analyzer

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I analyze log files to find specific error patterns and statistics?▼

To analyze log files for errors and statistics, you can parse common formats like Apache, Nginx, JSON, and Syslog to extract recurring events, identify specific error patterns, and generate statistical overviews of log entries.

Can I filter log entries by a specific time range during troubleshooting?▼

Yes, filtering log entries by time range is supported during troubleshooting. This allows you to isolate specific errors, count occurrences, and identify patterns within a defined window, making performance monitoring more efficient.

Does this approach work with custom log formats or only standard ones like Syslog?▼

This approach works with both standard formats like Apache, Nginx, JSON, and Syslog, as well as custom regex formats. This flexibility allows you to parse and analyze diverse application logs for pattern detection and statistical summaries.

What is the best way to count log levels and identify top occurrences in application logs?▼

The best way to count log levels and identify top occurrences is by generating a statistical overview. Analyzing the log file extracts summaries and counts specific log levels, helping you quickly spot recurring errors.

How do I parse Apache and Nginx logs to identify connection refused errors?▼

To parse Apache and Nginx logs for connection refused errors, apply pattern detection to find specific errors within your log data. You can then filter by time range and count the occurrences of these specific error patterns.

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