log-analysis

Parse infrastructure logs to extract actionable insights for incident detection.

4|1|Updated Dec 29, 2025

Search Tags:#regex #parsing #log-analysis #incident-response #pattern-recognition #infra-monitoring

Ready to run

npx skills add https://github.com/DoubleslashSE/claude-marketplace --skill log-analysis-doubleslashse

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: log-analysis
Source: https://github.com/DoubleslashSE/claude-marketplace/tree/main/Plugins/infra/skills/log-analysis
Command: npx skills add https://github.com/DoubleslashSE/claude-marketplace --skill log-analysis-doubleslashse

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill enables teams to parse, analyze, and derive actionable insights from infrastructure logs, reducing manual toil and speeding incident response.

Core Features & Use Cases

Log Anatomy and Classification: understand timestamps, severity levels, sources, and messages to structure raw logs for analysis.
Parsing Strategies: supports JSON-structured and plain-text logs with regex-based extraction of fields like timestamp, level, service, and identifiers.
Analysis & Patterns: enables time-based aggregation, pattern recognition, and cross-service correlation to identify anomalies and root causes.
Use Case: during a live incident, quickly summarize error trends and pinpoint the most impactful services for remediation.

Quick Start

To begin, provide the log file path (or stream) to the skill and request a concise incident-focused summary.

Frequently Asked Questions about log-analysis

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

FAQPage Schema

How do I parse unstructured infrastructure logs to find root causes during an incident?▼

Parse unstructured infrastructure logs by applying regex-based extraction to isolate fields like timestamp, level, and service, enabling time-based aggregation and cross-service correlation to pinpoint root causes during incident response.

Can I analyze multi-source logs across different platforms for anomaly detection?▼

Yes, you can analyze multi-source logs across platforms for anomaly detection. The Skill applies pattern recognition and cross-service correlation over extracted log fields to identify anomalies and generate concise incident-focused summaries.

Does this log-analysis approach work with both structured JSON and plain-text logs?▼

Yes, this log-analysis approach works with both structured JSON and plain-text logs. It classifies log anatomy and supports regex-based parsing strategies to extract meaningful fields from unstructured text for infrastructure monitoring.

What is the best way to extract timestamps and severity levels from raw logs?▼

The best way to extract timestamps and severity levels from raw logs is through regex-based field parsing. Understanding log anatomy allows you to structure raw logs for analysis, isolating timestamps, severity levels, sources, and messages.

How do I generate a concise summary of error trends from multi-source infrastructure logs?▼

Generate concise summaries of error trends by performing time-based aggregation and pattern recognition on parsed multi-source infrastructure logs. This highlights the most impactful services for remediation during a live incident.