developersglobal/ai-agent-skills/debugging-methodology

Claude Code and agent skill by developersglobal/ai-agent-skills

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Systematic root cause analysis for production and development bugs. Hypothesis-driven debugging — never guess-and-check.

Install

npx vskill@latest install developersglobal/ai-agent-skills/debugging-methodology

SKILL.md

Overview

Random code changes in response to errors are not debugging — they're noise generation. This skill enforces a systematic, hypothesis-driven approach: understand the problem, form a hypothesis, test it, confirm the root cause, then fix.

AI agents often cycle through random fixes until something "works." This skill prevents that.

When to Use

  • Any time a test fails unexpectedly
  • Any time you encounter an error or exception
  • When behavior differs between environments
  • When performance degrades unexpectedly

Process

Step 1: Reproduce Reliably
  1. Before doing anything else: reproduce the bug reliably. If you can't reproduce it, you can't fix it.
  2. Write a failing test that captures the bug — this becomes your regression test.
  3. Note the exact conditions that trigger the bug: inputs, environment, sequence of actions.

Verify: You can trigger the bug on demand.

Step 2: Understand Before Diagnosing
  1. Read the full error message — not just the first line.
  2. Read the stack trace from bottom to top — the root cause is usually near the bottom.
  3. Identify: What was the program trying to do? What happened instead?

Verify: You can explain the bug in one sentence without using the word "error."

Step 3: Form a Hypothesis
  1. Based on what you know, form a specific hypothesis: "I think the bug is X because Y."
  2. The hypothesis must be falsifiable — you can design a test that proves or disproves it.
  3. Do not start making code changes until you have a hypothesis.

Verify: Your hypothesis is specific enough to design a test for.

Step 4: Test the Hypothesis
  1. Add targeted logging or a targeted test that confirms or refutes the hypothesis.
  2. Run it. Read the output carefully.
  3. If the hypothesis is wrong: update your understanding, form a new hypothesis, repeat.
  4. If the hypothesis is right: you've found the root cause.

Verify: Root cause is confirmed by evidence, not assumed.

Step 5: Fix the Root Cause (Not the Symptom)
  1. Fix the root cause — not the symptom. Suppressing an error message is not a fix.
  2. Make the minimum change that fixes the root cause.
  3. Run the failing test you wrote in Step 1 — it should now pass.
  4. Run the full test suite — no regressions.

Verify: The specific failing test now passes. Full suite still passes.

Step 6: Prevent Recurrence
  1. If the bug wasn't caught by existing tests: add a test that would have caught it.
  2. If the bug was caused by a bad assumption: document the assumption or add a guard.
  3. Consider: does this class of bug exist elsewhere in the codebase?

Common Rationalizations (and Rebuttals)

ExcuseRebuttal
"Let me just try this and see"Random changes produce random results. Form a hypothesis first.
"It must be a framework bug"It's almost never the framework. Prove it before blaming it.
"Works on my machine"Environment differences are root causes. Find them. Don't dismiss them.
"I'll add a try/catch"That hides the bug. Find and fix the root cause.

Red Flags

  • Making code changes before understanding the bug
  • Adding try/catch to silence errors without investigating root cause
  • "I'll try this and see if it helps"
  • Assuming the bug is in a dependency before proving it
  • Fixing the symptom (error message) rather than the cause

Verification

  • [ ] Bug reproducible on demand
  • [ ] Root cause identified (not just symptom)
  • [ ] Fix targets root cause, not symptom
  • [ ] Reproduction test written and now passes
  • [ ] Full test suite passes with no regressions
  • [ ] Regression test added to prevent future occurrence

References

Security

  • Security scanPassed, 100 of 100Pattern checks on the skill's files.
  • Model reviewNot runA model review is scheduled for the next rescan.

Quality evaluation

  • Task evaluationNot runNo evaluation yet. Run one in Skill Studio.

Source

Popularity

Repository stars
64
Repository forks
10
7-day trend score
21

Stars and forks are for the whole GitHub repository, not this skill alone. Not refreshed yet.

Works with

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