What is hypothesis-based debugging?

It is a scientific approach to software troubleshooting where you form specific, testable theories about a bug and collect runtime evidence to prove or disprove them before making code changes.

How does the debug server operate?

The skill automatically launches a lightweight Node.js server on port 3947 that captures structured JSON logs from your application, allowing Claude to analyze program flow in real-time.

Does this skill leave debug code in my repository?

No. The skill follows a strict cleanup protocol that removes all instrumentation blocks, stops the background server, and deletes temporary log files once the fix is verified.

Can I use this for non-JavaScript projects?

While the primary instrumentation templates are optimized for JS/TS, the core methodology and logging schema can be adapted for any language capable of making HTTP requests.

Why is runtime evidence required before fixing?

Runtime evidence ensures that the actual root cause is identified, preventing 'band-aid' fixes that might temporarily hide symptoms while leaving the underlying logic error intact.

Hypothesis-Based Debugger

Name: Hypothesis-Based Debugger
Author: kerdofficial

bykerdofficial

セキュリティとテスト

Automates evidence-based debugging through systematic hypothesis generation, runtime instrumentation, and structured log analysis.

概要

The Hypothesis-Based Debugger transforms Claude into a systematic diagnostic tool that eliminates guesswork from the debugging process. Instead of jumping straight to code changes, this skill enforces a rigorous scientific method: generating testable hypotheses, deploying a local debug server, instrumenting code with non-intrusive loggers, and analyzing runtime evidence. It is particularly effective for troubleshooting complex asynchronous issues, race conditions, and state management bugs where static code analysis falls short, ensuring every fix is backed by hard data.

主な機能

Non-intrusive code instrumentation using designated regions
Comprehensive cleanup phase to remove all debug infrastructure
Real-time runtime log collection via local NDJSON server
Structured hypothesis evaluation and validation tables
0 GitHub stars
Automated hypothesis-driven debugging workflow

ユースケース

Tracing data transformations across multiple function calls to find logic regressions
Identifying the root cause of complex state mutations in large-scale frontend components
Diagnosing intermittent race conditions in asynchronous JavaScript/TypeScript applications

概要

主な機能

Non-intrusive code instrumentation using designated regions
Comprehensive cleanup phase to remove all debug infrastructure
Real-time runtime log collection via local NDJSON server
Structured hypothesis evaluation and validation tables
0 GitHub stars
Automated hypothesis-driven debugging workflow

ユースケース

Tracing data transformations across multiple function calls to find logic regressions
Identifying the root cause of complex state mutations in large-scale frontend components
Diagnosing intermittent race conditions in asynchronous JavaScript/TypeScript applications