log-analysis

Filter and summarize JSON and plain text logs by level, time, and patterns.

1|1|Updated Mar 6, 2026

Search Tags:#logs #json #grep #jq #log-analysis #tail

Ready to run

npx skills add https://github.com/dennisonbertram/go-agent-harness --skill log-analysis-dennisonbertram

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: log-analysis
Source: https://github.com/dennisonbertram/go-agent-harness/tree/main/skills/log-analysis
Command: npx skills add https://github.com/dennisonbertram/go-agent-harness --skill log-analysis-dennisonbertram

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill enables rapid extraction, correlation, and interpretation of log data across various formats (plain text and JSON) to detect issues, monitor health, and diagnose failures.

Core Features & Use Cases

Level and pattern filtering: quickly filter logs by severity and custom text or JSON fields.
Time-based analysis: query logs within specific time ranges to diagnose incidents or performance trends.
Structured log support: parse and analyze JSON logs with jq, extracting key fields for dashboards or reports.

Quick Start

Run a quick log analysis by filtering and aggregating logs using grep, jq, and time-based queries.

Frequently Asked Questions about log-analysis

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

FAQPage Schema

How do I filter application logs by severity and time range for incident response?▼

Log analysis filtering extracts relevant log entries by severity level and time range to facilitate faster incident response. You can apply custom text or JSON field filters alongside time-based queries to isolate specific application failures.

What is the best way to parse structured JSON logs using command-line tools?▼

Parsing structured JSON logs is best handled with jq to extract key fields for dashboards or reports. This allows rapid correlation and interpretation of structured data from applications, services, and pipelines.

Can I analyze plain text logs and real-time log streams without dedicated monitoring software?▼

Plain text and real-time log streams can be analyzed directly using command-line tools like grep and tail. This approach identifies content patterns and summarizes data without requiring dedicated monitoring infrastructure.

How do I extract specific fields from JSON logs to diagnose service failures?▼

Extracting specific fields from JSON logs utilizes jq to parse structured data and isolate failure indicators. This enables rapid interpretation of service health by querying logs within specific time ranges.

Does log analysis work with archived pipeline logs or only real-time streams?▼

Log analysis works with both real-time streams and stored archives from pipelines and services. It identifies and summarizes log data by level, time, and content patterns regardless of whether the logs are live or archived.

Why use grep for log analysis instead of structured logging platforms?▼

Grep provides rapid pattern matching and level filtering for plain text logs without requiring structured logging platforms. It enables quick extraction and interpretation of log data to detect issues and monitor health.