Which databases are supported by this skill?

The skill supports major database systems including PostgreSQL via psql, MySQL via the mysql client, and MongoDB via mongosh.

Can I use this for real-time monitoring?

While it can diagnose active issues, it is designed to help you set up permanent monitoring dashboards and runbooks for long-term observability.

What permissions are required to use this skill?

Users must have the necessary credentials and permissions to execute administrative shell commands and database queries on the target systems.

Can this skill automatically resolve deadlocks?

It provides scripts and automation tools to resolve deadlocks, but emphasizes a workflow that includes assessment and validation to ensure data integrity.

Does this skill help with preventing future deadlocks?

Yes, it includes implementation patterns, query optimization guides, and best practices to help developers refactor code and avoid lock contention altogether.

Database Deadlock Detector

Name: Database Deadlock Detector
Author: BbgnsurfTech

byBbgnsurfTech

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Database Management

Detects, resolves, and prevents database deadlocks across PostgreSQL, MySQL, and MongoDB environments to ensure system stability.

About

The Database Deadlock Detector is a specialized skill for Claude Code designed to identify and mitigate transaction conflicts in high-concurrency database environments. It provides automated detection scripts, step-by-step resolution workflows, and implementation patterns for preventing future deadlocks. By integrating with psql, mysql, and mongosh, the skill helps developers analyze lock wait states, optimize query performance, and establish robust monitoring dashboards to maintain database health and application uptime.

Key Features

Generation of monitoring dashboards and observability alerts
Automated deadlock detection for PostgreSQL, MySQL, and MongoDB
Best practice patterns for deadlock prevention and query optimization
3 GitHub stars
Comprehensive resolution guidance for active transaction conflicts
Real-time diagnostic integration via database shell tools

Use Cases

Identifying and terminating stuck transactions in high-traffic production databases
Configuring automated observability stacks to alert on lock-contention events
Refactoring application logic to eliminate circular lock dependencies during development

About

Key Features

Generation of monitoring dashboards and observability alerts
Automated deadlock detection for PostgreSQL, MySQL, and MongoDB
Best practice patterns for deadlock prevention and query optimization
3 GitHub stars
Comprehensive resolution guidance for active transaction conflicts
Real-time diagnostic integration via database shell tools

Use Cases

Identifying and terminating stuck transactions in high-traffic production databases
Configuring automated observability stacks to alert on lock-contention events
Refactoring application logic to eliminate circular lock dependencies during development