Why is speculation considered an anti-pattern in this framework?

Speculation leads to 'guess-and-check' cycles that waste time and often introduce new bugs without actually solving the root cause of the original issue.

Can this skill be used for front-end and back-end issues?

Yes, it provides patterns for various contexts including API calls, CLI tools, file operations, and general logic debugging across all programming languages.

How does this skill help Claude fix bugs more efficiently?

It prevents the AI from making random guesses by forcing it to verify assumptions through logging, state checks, and branch tracing first.

What is the core principle of Observability-First Debugging?

The core principle is 'Measure before you act,' emphasizing that you should add instrumentation to gather data before forming a hypothesis or attempting a fix.

Observability-First Debugging

Name: Observability-First Debugging
Author: NTCoding

byNTCoding

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분석 및 모니터링

Eliminates guesswork in software development by prioritizing systematic instrumentation and data-driven evidence before attempting code fixes.

소개

Observability-First Debugging is a specialized Claude Code skill designed to break the cycle of speculative debugging and 'guess-and-check' patterns. It guides the AI to systematically instrument code—adding targeted logging, state inspections, and execution traces—to uncover the root cause of issues before proposing solutions. By emphasizing observation over intuition, this skill ensures that debugging remains a repeatable, scientific process, leading to more accurate fixes and reduced frustration during complex troubleshooting sessions.

주요 기능

Template-driven instrumentation for APIs, CLI tools, and file systems
Identification and elimination of common debugging anti-patterns
Emphasis on evidence-based hypothesis formation over speculation
Logical decision tree for determining when to add more visibility
Step-by-step debugging protocol from reproduction to iteration
94 GitHub stars

사용 사례

Resolving file system path issues in different environments through absolute path logging
Troubleshooting cryptic 400-series API errors by inspecting request/response payloads
Debugging inconsistent unit test failures where internal state is unknown

소개

주요 기능

Template-driven instrumentation for APIs, CLI tools, and file systems
Identification and elimination of common debugging anti-patterns
Emphasis on evidence-based hypothesis formation over speculation
Logical decision tree for determining when to add more visibility
Step-by-step debugging protocol from reproduction to iteration
94 GitHub stars

사용 사례

Resolving file system path issues in different environments through absolute path logging
Troubleshooting cryptic 400-series API errors by inspecting request/response payloads
Debugging inconsistent unit test failures where internal state is unknown