How does this skill automate log collection?

It launches a local Node.js server that listens for log events sent from your application via HTTP or the Beacon API, saving them to a structured NDJSON file for Claude to read and analyze.

Do I need to manually add logs to my code?

Yes, Claude will generate specific instrumentation snippets based on its hypotheses. You simply insert these snippets into your code to provide the necessary runtime data.

What programming languages are supported?

The skill provides optimized patterns and snippets for JavaScript, TypeScript, and Python, but the logging server can receive data from any language capable of making HTTP POST requests.

Why use this instead of standard console logs?

Standard logs require manual copy-pasting from a terminal or browser console. This skill enables Claude to read the logs directly, speeding up analysis and preventing human error in reporting.

What happens to the debug code after the fix?

The workflow includes a final cleanup phase where Claude identifies and removes all instrumentation markers once the fix has been verified with runtime evidence.

Runtime Evidence Debugger

Name: Runtime Evidence Debugger
Author: elie222

byelie222

•

9,883

分析と監視

Automates runtime log collection and hypothesis testing to fix complex bugs using empirical evidence instead of guesswork.

概要

The Runtime Evidence Debugger skill provides a structured, hypothesis-driven workflow for resolving difficult software defects. By automating the setup of a local logging server and providing standardized instrumentation patterns, it allows developers to capture real-time values, state transitions, and execution flows. This skill is especially useful for debugging issues that are hard to reproduce or require specific user interactions, as it replaces manual DevTools inspection with programmatically accessible, structured logs that Claude can analyze directly to confirm or reject root-cause hypotheses.

主な機能

Automated local log server setup with session-based tracking
Hypothesis-driven debugging framework to validate specific root causes
Multi-language instrumentation snippets for JavaScript, TypeScript, and Python
Structured NDJSON log analysis for clear evidence-based conclusions
9,883 GitHub stars
Pre- and post-fix verification workflow to ensure permanent resolution

ユースケース

Debugging complex state issues or null/undefined errors in frontend applications
Identifying async timing issues and race conditions in distributed systems
Capturing runtime evidence for bugs that depend on specific user interactions

概要

主な機能

Automated local log server setup with session-based tracking
Hypothesis-driven debugging framework to validate specific root causes
Multi-language instrumentation snippets for JavaScript, TypeScript, and Python
Structured NDJSON log analysis for clear evidence-based conclusions
9,883 GitHub stars
Pre- and post-fix verification workflow to ensure permanent resolution

ユースケース

Debugging complex state issues or null/undefined errors in frontend applications
Identifying async timing issues and race conditions in distributed systems
Capturing runtime evidence for bugs that depend on specific user interactions