Error Log Summarizer

Parse and de-duplicate error logs into prioritized issues with root-cause hints.

9|1|Updated Mar 15, 2026
One-click install
npx skills add https://github.com/Notysoty/openagentskills --skill error-log-summarizer
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: Error Log Summarizer
Source: https://github.com/Notysoty/openagentskills/tree/main/skills/error-log-summarizer
Command: npx skills add https://github.com/Notysoty/openagentskills --skill error-log-summarizer

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Ingest raw error logs and produce a structured, de-duplicated, prioritized summary with root-cause hints, enabling faster problem understanding and triage.

Core Features & Use Cases

  • De-duplicate and group similar errors across log lines to reduce noise.
  • Rank issues by frequency and severity, surfacing the most impactful problems first.
  • Generate concise root-cause hints for each unique error to guide investigation.

Quick Start

Paste the raw logs into the prompt and request a prioritized error summary.

Frequently Asked Questions about Error Log Summarizer

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

FAQPage Schema
How do I summarize error logs and find root-cause hints for production incidents?

To de-duplicate error logs, similar log lines are parsed and grouped to reduce noise, generating a structured summary with per-issue metadata and root-cause hints for faster incident triage.

What is the best way to de-duplicate CI failure logs across multiple services?

De-duplicating CI failure logs involves grouping similar errors across multiple services to reduce noise, ranking issues by frequency and severity, and outputting a prioritized set of unique issues.

Can I parse monitoring alerts with dynamic message parts and optional timestamps?

Yes, monitoring alerts with dynamic message parts and optional timestamps can be parsed. The process handles dynamic message components and requires a log structure with optional timestamp and source fields.

How do I prioritize error log patterns by frequency and severity during triage?

Prioritizing error log patterns by frequency and severity involves parsing logs to rank unique issues based on occurrence rate and impact, surfacing the most critical problems first for triage.

Does error log summarization work with raw text dumps lacking a strict structured format?

Error log summarization works with raw text dumps containing a recognizable log structure with optional timestamps and source fields, enabling the extraction of unique issues and root-cause hints.