ops-log-sift

Analyze log files to extract error patterns and hypothesize root causes.

2|Updated Feb 25, 2026
One-click install
npx skills add https://github.com/gaebalai/claude-code-kit-ko --skill ops-log-sift
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: ops-log-sift
Source: https://github.com/gaebalai/claude-code-kit-ko/tree/main/.claude/skills/ops-log-sift
Command: npx skills add https://github.com/gaebalai/claude-code-kit-ko --skill ops-log-sift

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill automates the complex and time-consuming process of analyzing log files to identify error patterns, hypothesize causes, and suggest actionable steps for incident response, significantly speeding up initial troubleshooting.

Core Features & Use Cases

  • Automated Log Analysis: Extracts error patterns, analyzes their frequency and timeline, and identifies correlations with events like deployments.
  • Hypothesis Generation: Develops up to three potential root cause hypotheses based on the analyzed log data, including supporting evidence and contradictions.
  • Triage and Action Planning: Classifies incident urgency (P1-P3), estimates impact, and proposes concrete investigation and remediation steps.
  • Use Case: When a production service experiences errors, use this Skill with a log file path to quickly get a summary of the issues, potential causes, and recommended next steps for the on-call engineer.

Quick Start

Analyze the log file located at /var/log/app.log and suggest immediate actions.

Frequently Asked Questions about ops-log-sift

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

FAQPage Schema
How do I analyze application logs to find the root cause of an incident?

To analyze application logs for incident root causes, you can use automated log analysis to extract error patterns, assess their frequency and timeline, and generate up to three potential root cause hypotheses with supporting evidence for rapid triage.

Can I use log analysis tools to correlate errors with recent Git deployments?

Yes, log analysis can correlate errors with Git deployments by integrating with Git history, allowing you to identify temporal distributions of error patterns and match them with recent deployment events to pinpoint incident triggers.

What is the best way to triage production errors and plan incident response actions?

The best way to triage production errors is to classify incident urgency (P1-P3), estimate impact, and propose concrete investigation and remediation steps, which streamlines incident response planning for the on-call engineer.

Does automated log analysis work with both structured and unstructured log formats?

Yes, automated log analysis supports both structured and unstructured log formats, enabling you to extract error patterns and generate root cause hypotheses regardless of the log formatting your production service outputs.

How do I troubleshoot a production service incident when I only have log keywords?

To troubleshoot a production service incident using log keywords, you can analyze the specific keywords to extract matching error patterns, assess their frequency, and hypothesize potential root causes for immediate triage.