agentsclimarketplace

Systematic debugging skills dmjgilbert systematic debugging

Skill bg-szy/TOP-SKILLS/skills/marketplace/systematic-debugging__skills-dmjgilbert-systematic-debugging

全球最大的 Claude Code 技能聚合库 · 收录 3900+ 来自 12+ 来源的技能,提供在线搜索与趋势分析看板 / The world's largest Claude Code skill aggregation hub — 3900+ skills from 12+ sources with online search and trend dashboard

Install
npx -y skills add bg-szy/TOP-SKILLS --skill systematic-debugging__skills-dmjgilbert-systematic-debugging

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

2 things to look at

  • no licenseNo license file was found in the repository. Code published without one is not open source by default, so using it at work is a question for whoever answers licensing questions where you are.
  • 4 stars4 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

What its author says it does

Copied from the file, not written here

Four-phase root cause investigation before attempting fixes. Use when debugging bugs, test failures, or unexpected behavior.

SKILL.md

2.5 KB, 537 tokens by cl100k_base, as published. Nobody here has run it

Systematic Debugging

ALWAYS find root cause before attempting fixes. Symptom fixes are failure.

When to Use

  • Encountering bugs or test failures
  • Unexpected behavior in code
  • Before proposing any fix

The Four Phases

Phase 1: Root Cause Investigation

Before proposing any solution:

  1. Read error messages thoroughly - Don't skip warnings or stack traces; they often contain exact solutions
  2. Reproduce consistently - Verify you can trigger the issue reliably with documented steps
  3. Check recent changes - Examine git diff, dependencies, and configuration modifications
  4. Gather diagnostic evidence - In multi-component systems, add instrumentation at component boundaries
  5. Trace data flow - Backward trace from the error to find where bad values originate

Phase 2: Pattern Analysis

Establish the pattern before fixing:

  1. Locate similar working code in the codebase
  2. Read reference implementations completely (not skimmed)
  3. List every difference between working and broken code
  4. Understand all dependencies and assumptions

Phase 3: Hypothesis Testing

Apply scientific method:

  1. State your hypothesis clearly: "I believe X is failing because Y, evidenced by Z"
  2. Test with the smallest possible change
  3. Change only ONE variable at a time
  4. Verify results before proceeding

Phase 4: Implementation

Fix the root cause systematically:

  1. Create a failing test case first (TDD)
  2. Implement a single fix addressing only the root cause
  3. Verify the fix resolves the issue without breaking other tests
  4. If fix doesn't work, return to Phase 1

Red Flags - STOP Immediately

  • Proposing fixes without understanding the issue
  • Attempting multiple simultaneous changes
  • Assuming problems without verification
  • Skipping evidence gathering
  • Making "quick fixes" before investigation

When 3+ Fixes Fail

STOP. This signals an architectural problem, not a fixable bug:

  1. Do not attempt another fix
  2. Return to Phase 1
  3. Question whether the underlying pattern/design is sound
  4. Ask: "Should we refactor architecture vs. continue fixing symptoms?"

Random fixes waste time and create new bugs. Quick patches mask underlying issues.

Results

Systematic approach: 15-30 minutes to resolution with 95% first-time success vs. Trial-and-error: 2-3 hours of thrashing with 40% success and new bugs introduced

What ships with it: 1 file

8.9 KB alongside SKILL.md

Keep looking

Skills are one crate of 328,083. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.