Does this skill change my application logic?

No, the Debug Logging Assistant is strictly designed to add logs without altering control flow, data structures, or functional behavior.

Can it follow my project's specific logging style?

Yes, it inspects your current codebase to match existing log levels, prefixes, and messaging styles for a consistent developer experience.

Will it spam my logs with too much information?

No, it follows a high-signal approach, placing logs only where they explain flow, inputs, or outcomes while avoiding trivial or repetitive steps.

Is sensitive data protected when adding logs?

The workflow includes specific instructions to keep sensitive data out of logs, focusing only on safe identifiers or summary outcomes.

Debug Logging Assistant

Name: Debug Logging Assistant
Author: dmitriiweb

bydmitriiweb

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106

Analytics & Monitoring

Enhances code observability by inserting purposeful, non-intrusive debug logs into critical execution paths.

About

The Debug Logging Assistant is a specialized Claude Code skill designed to improve software observability and troubleshooting without altering existing application behavior. It intelligently identifies high-signal locations—such as external API calls, complex branching logic, and error handlers—to insert concise, meaningful logs that capture essential context. By adhering to established codebase patterns and avoiding 'log spam,' this skill helps developers gain visibility into inputs, outcomes, and execution flows, making it significantly easier to diagnose production issues and understand system state during failures.

Key Features

Excludes sensitive data while capturing essential identifiers and outcomes
Optimizes log placement to avoid performance degradation on hot paths
Maintains consistent logging levels and prefixes based on existing patterns
Identifies high-signal observability gaps in entry points and external calls
106 GitHub stars
Inserts concise, non-functional logs without altering control flow or data

Use Cases

Improving visibility into complex branching logic or third-party API integrations
Troubleshooting intermittent production failures by adding context to error handlers
Enhancing system monitoring during the rollout of new features or refactored code

About

Key Features

Excludes sensitive data while capturing essential identifiers and outcomes
Optimizes log placement to avoid performance degradation on hot paths
Maintains consistent logging levels and prefixes based on existing patterns
Identifies high-signal observability gaps in entry points and external calls
106 GitHub stars
Inserts concise, non-functional logs without altering control flow or data

Use Cases

Improving visibility into complex branching logic or third-party API integrations
Troubleshooting intermittent production failures by adding context to error handlers
Enhancing system monitoring during the rollout of new features or refactored code