debug-with-logs

Name: debug-with-logs
Availability: InStock
Author: gautam-achieveai

Analyzes JSONL logs with DuckDB SQL queries to diagnose software failures.

2|Updated Apr 12, 2026

Search Tags:#debugging #root cause analysis #logging #DuckDB #JSONL

Ready to run

npx skills add https://github.com/gautam-achieveai/ClaudePlugins --skill debug-with-logs

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: debug-with-logs
Source: https://github.com/gautam-achieveai/ClaudePlugins/tree/main/debugging/skills/debug-with-logs
Command: npx skills add https://github.com/gautam-achieveai/ClaudePlugins --skill debug-with-logs

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill provides a systematic approach to debugging issues by leveraging structured JSONL logs and DuckDB queries, enabling users to quickly identify and resolve problems without manual log analysis.

Core Features & Use Cases

Structured Logging: Utilizes a standardized JSONL log format for clear and consistent data collection.
DuckDB Querying: Allows users to execute SQL queries on log data to trace and analyze execution flows.
Debugging Methodology: Offers a 7-step process for debugging, from understanding the problem to verifying the fix.
Use Case: Ideal for developers who need to debug failing tests, broken features, or unexpected behaviors in production systems.

Quick Start

Use the debug-with-logs skill to debug the issue in the application log 'app.log.jsonl'.

Frequently Asked Questions about debug-with-logs

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

FAQPage Schema

How do I debug production issues using structured JSONL logs?▼

Debug production issues using structured JSONL logs by parsing the data with DuckDB SQL queries to trace execution flows. This approach replaces manual log analysis with a systematic 7-step methodology to quickly identify and resolve failures, performance issues, and unexpected behaviors.

What's the best way to find the root cause of a failing test using log data?▼

The best way to find the root cause of a failing test is applying a structured log-first debugging methodology. By querying your application's JSONL log data with DuckDB, you can trace the exact execution flow and isolate the specific failure point without manually reading raw log files.

Do I need a DuckDB MCP server to query JSONL log files for debugging?▼

Yes, you need a DuckDB MCP server to query JSONL log files for debugging. The server enables SQL-based querying directly against the structured log data, which is required to parse the JSONL format and execute the root cause analysis queries.

Can I use SQL queries to analyze application logs for unexpected behaviors?▼

Yes, you can use SQL queries to analyze application logs for unexpected behaviors. By leveraging DuckDB, you can directly query structured JSONL log data to filter, aggregate, and trace events, allowing you to systematically debug performance issues and broken features.

Does this log debugging methodology work without structured logging in my codebase?▼

No, this log debugging methodology does not work without structured logging in your codebase. The root cause analysis process requires logs to be in a standardized JSONL format so that DuckDB can reliably parse the data and execute SQL queries to trace execution flows.

How do I start root cause analysis when debugging an application failure?▼

Start root cause analysis for an application failure by pointing the debugging process to your structured log file, such as 'app.log.jsonl'. The 7-step methodology guides you from understanding the problem to querying the JSONL logs with DuckDB and verifying the fix.