Runtime Evidence Debugger FAQs

Question 1

How does this skill automate log collection?

Accepted Answer

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.

Question 2

Do I need to manually add logs to my code?

Accepted Answer

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.

Question 3

What programming languages are supported?

Accepted Answer

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.

Question 4

Why use this instead of standard console logs?

Accepted Answer

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.

Question 5

What happens to the debug code after the fix?

Accepted Answer

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

Key Features

Use Cases

Runtime Evidence Debugger

Key Features

Use Cases