What is the role of APEX pattern learning?

During the final reflection step, the skill analyzes which debugging patterns worked. This updates a 'trust score' that helps the AI prioritize the most successful strategies for future bugs.

Is a reproduction test case mandatory?

Yes, the workflow requires a minimal reproduction case or documented intermittency pattern before proceeding to ensure the root cause is truly understood.

Can this skill analyze my git history?

Yes, it integrates with git-historian to analyze recent commits, regressions, and related fixes to find the exact point where a bug was introduced.

What happens if all hypotheses fail?

The skill triggers an escalation protocol, prompting a re-examination of evidence, questioning of architectural assumptions, or the spawning of deeper research agents.

How does this skill prevent 'shotgun debugging'?

The skill enforces a strict protocol where users must gather evidence and propose a maximum of three specific, testable hypotheses before making any code changes.

APEX Systematic Debugging

Name: APEX Systematic Debugging
Author: benredmond

bybenredmond

セキュリティとテスト

Implements a hypothesis-driven debugging workflow that utilizes pattern-based intelligence to resolve complex software bugs.

概要

The APEX Debug skill provides a structured, evidence-based framework for troubleshooting within the Claude Code environment. It moves beyond trial-and-error by enforcing a rigorous workflow that includes mandatory bug reproduction, git history analysis, and targeted hypothesis testing. By integrating with historical failure patterns and requiring a final reflection phase, the skill ensures that every bug resolved contributes to a growing collective intelligence, improving future troubleshooting efficiency and updating pattern trust scores for the entire development lifecycle.

主な機能

Automated integration with git-historian and failure-predictor agents
Hypothesis-driven investigation with strict concurrency limits to maintain focus
0 GitHub stars
Mandatory reproduction checklists and structured evidence collection
Post-mortem reflection loop to update pattern trust scores and codebase knowledge
Pattern-based intelligence to identify known failure modes and anti-patterns

ユースケース

Troubleshooting intermittent or complex regressions using historical commit analysis
Systematizing the debugging process for teams to avoid 'shotgun debugging' approaches
Building a long-term knowledge base of codebase-specific failure patterns and fixes

概要

主な機能

Automated integration with git-historian and failure-predictor agents
Hypothesis-driven investigation with strict concurrency limits to maintain focus
0 GitHub stars
Mandatory reproduction checklists and structured evidence collection
Post-mortem reflection loop to update pattern trust scores and codebase knowledge
Pattern-based intelligence to identify known failure modes and anti-patterns

ユースケース

Troubleshooting intermittent or complex regressions using historical commit analysis
Systematizing the debugging process for teams to avoid 'shotgun debugging' approaches
Building a long-term knowledge base of codebase-specific failure patterns and fixes