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log-analyze

Correlate text, JSON, Windows Event, and crash dump logs to identify root causes.

1|Updated Apr 22, 2026
Search Tags:#root cause analysis#log analysis#log correlation#performance monitoring#system diagnostics#crash dump#windows event logs
One-click install
npx skills add https://github.com/Herxinsasa/Skills-Collector --skill log-analyze-herxinsasa
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: log-analyze
Source: https://github.com/Herxinsasa/Skills-Collector/tree/main/log-analyze
Command: npx skills add https://github.com/Herxinsasa/Skills-Collector --skill log-analyze-herxinsasa

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

System and application failures scatter evidence across text logs, JSON logs, Windows Event Logs, performance counters, and crash dumps. Manually correlating these disparate sources is slow and error-prone. This Skill automates the collection, parsing, and cross-referencing of multiple log types to rapidly identify root causes, transforming hours of forensic work into a structured, repeatable diagnostic workflow.

Core Features & Use Cases

  • Multi-Format Log Support: Seamlessly analyze .log, .txt, .json, .evtx, .blg, and .dmp files within a unified workflow.
  • Cross-Type Correlation: Align timelines and match process IDs, module names, and trace IDs across different log sources to build complete causal chains.
  • Guided Diagnostic Workflow: Follow a structured seven-step process—from scope confirmation and domain context gathering to single-type analysis, correlation, root cause inference, and report generation.
  • Production-Ready Scripts: Leverages built-in PowerShell and Python scripts for deterministic tasks like .blg to CSV conversion, timeline alignment, and automated dump analysis.
  • Use Case: A production service crashes unexpectedly. Use this Skill to combine the crash dump, Windows Event Logs, application logs, and performance monitor data to trace the failure from memory exhaustion through database timeouts to the final access violation.

Quick Start

Provide the path to your log directory or paste your log content, describe the observed system anomaly, and ask the Skill to analyze the logs and identify the root cause.

Frequently Asked Questions about log-analyze

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

FAQPage Schema
How do I correlate crash dumps with Windows Event Logs to find a root cause?▼

Multi-type log correlation aligns timelines and matches process IDs across crash dumps and Windows Event Logs to identify root causes. This automated cross-referencing builds complete causal chains without requiring manual timeline alignment or destructive operations.

What is the best way to analyze system logs across multiple formats for anomalies?▼

Multi-format log analysis processes .log, .txt, .json, .evtx, .blg, and .dmp files within a unified workflow to detect system anomalies. It applies a structured seven-step diagnostic process from scope confirmation to evidence-based reporting.

Can I use log correlation for embedded systems and production servers?▼

Log correlation applies to production software, embedded systems, and server applications requiring forensic workflows. It parses diverse application logs and performance monitor data to trace failures like memory exhaustion or database timeouts.

How do I convert performance monitor data for timeline alignment during diagnostics?▼

Built-in PowerShell and Python scripts convert .blg performance monitor data to CSV format for deterministic timeline alignment. This automated conversion prepares performance counters for cross-type correlation with other system logs.

Does multi-type log analysis require modifying source code to diagnose faults?▼

Multi-type log analysis identifies root causes through evidence-based diagnostic reporting without modifying code or executing destructive operations. It leverages structured forensic workflows to analyze existing text logs, JSON logs, and crash dumps.

Why do I need to correlate JSON logs and Windows Event Logs for crash analysis?▼

Correlating JSON logs and Windows Event Logs matches trace IDs and module names across disparate sources to build complete causal chains. This cross-type correlation prevents missed evidence that causes incomplete root cause inference during system diagnostics.

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