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dev-coding-debug

Testing & Quality
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Systematic debugging workflow enforcing 'The Iron Law': No fixes without root cause investigation first.

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Source SKILL.md: https://github.com/majiayu000/claude-skill-registry/blob/HEAD/skills/development/dev-coding-debug-lastdays03-claude-skills/SKILL.md

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Systematic Debugging (Dev Coding Debug)

Core Principles (The Iron Law)

NO FIXES WITHOUT ROOT CAUSE INVESTIGATION FIRST.

If you haven't completed Phase 1 (Root Cause) and Phase 2 (Pattern Analysis), you cannot propose fixes. Symptom fixes are failure.

🏗️ The Four Phases

Phase 1: Root Cause Investigation

Goal: Understand WHAT and WHY.

  1. Read Errors: sticky to the error message. Don't skip stack traces.
  2. Reproduce: Can you trigger it reliably? If not, gather more data.
  3. Instrumentation: For multi-component systems, log data flow at boundaries.
  4. Trace: Follow the bad value backwards to its source (root-cause-tracing).

Phase 2: Pattern Analysis

Goal: Find the standard before fixing.

  1. Find Working Examples: Locate similar code that works.
  2. Compare: Read reference implementations completely.
  3. Identify Differences: List every difference, however small.

Phase 3: Hypothesis and Testing

Goal: Scientific Method.

  1. Single Hypothesis: "I think X is the root cause because Y".
  2. Test Minimally: Change ONE variable at a time to test the hypothesis.
  3. Verify: If it didn't work, revert and form a NEW hypothesis. NO layering fixes.

Phase 4: Implementation

Goal: Fix the root cause, not the symptom.

  1. Failing Test: Create a minimal reproduction test case (Red).
  2. Single Fix: Address the identified root cause (Green).
  3. Verify: Ensure no regressions.

�️ Supporting Techniques

1. Root Cause Tracing ("Why did this happen?")

Don't just fix the bad value. Find where it came from.

  • Technique: Ask "What called this with a bad value?" repeatedly until you find the source.
  • Rule: Fix at the source, not at the symptom.

2. Defense-in-Depth ("Make it impossible")

Don't just validate at one place.

  • Layer 1 (Entry): Reject invalid input at IDL/API boundary.
  • Layer 2 (Logic): Ensure data makes sense for the operation.
  • Layer 3 (Guard): Environment checks (e.g., test vs prod).
  • Layer 4 (Debug): Logging for forensics.

3. Condition-Based Waiting (No sleep)

Never guess how long something takes.

  • Bad: sleep(50)
  • Good: waitFor(() => condition)
  • Why: Flaky tests often come from arbitrary timeouts.

�🚩 Red Flags (STOP immediately)

  • "Quick fix for now"
  • "Just try changing X"
  • "One more fix attempt" (Limit: 3 attempts. Then question Architecture.)
  • Proposing solutions before tracing.

✅ Quality Standards

  • Reproduction Script: Must exist before fixing.
  • Log Cleanup: All temporary instrumentation removed.
  • Safe YAML: Frontmatter descriptions quoted.

Checklist

  • Phase 1: Did you identify the exact line/reason for failure?
  • Phase 2: Did you compare with a working example?
  • Phase 4: Is there a test case that failed before and passes now?
  • Cleanup: Are all print/console.log removed?