How does this skill handle complex, multi-component systems?

It implements diagnostic instrumentation at every component boundary to log data entry and exit, allowing you to pinpoint exactly which layer of the stack is failing.

What is the 'Iron Law' of systematic debugging?

The Iron Law mandates that no code fixes can be proposed until a complete root cause investigation is finished, ensuring that symptoms aren't just masked by patches.

Does this skill help with Test-Driven Development (TDD)?

Yes, Phase 4 requires the creation of a minimal failing test case before any fix is implemented, ensuring the solution is automated and verified.

What happens if three different fixes fail to solve the bug?

The process triggers a mandatory architectural review, shifting focus from fixing a specific bug to questioning if the underlying system design is fundamentally sound.

Is this debugging process slower than manual fixing?

While it requires more initial investigation, it is significantly faster than the 'trial and error' approach by preventing regression bugs and ensuring a 95% first-time fix rate.

Systematic Debugging

Name: Systematic Debugging
Author: tianyuanztm

bytianyuanztm

0•

开发者工具

Enforces a rigorous four-phase scientific methodology to identify root causes and implement permanent fixes for complex software bugs.

The Systematic Debugging skill transforms Claude's approach to troubleshooting from trial-and-error to a disciplined engineering process. It follows the 'Iron Law'—prohibiting any code fixes until a root cause is definitively identified. The skill guides the AI through four mandatory phases: exhaustive root cause investigation using diagnostic instrumentation, pattern analysis against working references, minimal hypothesis testing, and implementation verified by failing test cases. This structured approach is specifically designed to eliminate 'voodoo' debugging, prevent regression bugs, and identify when a recurring issue actually signals a fundamental architectural flaw.

主要功能

01Multi-component diagnostic instrumentation for tracing data flow across system boundaries.

02Mandatory root cause investigation phase before any code modifications are proposed.

03Strict architectural review trigger after three unsuccessful fix attempts to prevent thrashing.

04Integrated verification process requiring the creation of failing test cases before fixes.

05Backward data flow tracing techniques to locate the original source of state corruption.

060 GitHub stars

使用场景

01Resolving intermittent race conditions or environment-specific failures in CI/CD pipelines.

02Fixing recurring bugs where previous 'quick patches' have failed to address the underlying problem.

03Debugging complex data flow issues in multi-layered microservices or distributed systems.

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add tianyuanztm/myplan systematic-debugging

For use in Claude.ai and ChatGPT

主要功能

01Multi-component diagnostic instrumentation for tracing data flow across system boundaries.

02Mandatory root cause investigation phase before any code modifications are proposed.

03Strict architectural review trigger after three unsuccessful fix attempts to prevent thrashing.

04Integrated verification process requiring the creation of failing test cases before fixes.

05Backward data flow tracing techniques to locate the original source of state corruption.

060 GitHub stars

使用场景

01Resolving intermittent race conditions or environment-specific failures in CI/CD pipelines.

02Fixing recurring bugs where previous 'quick patches' have failed to address the underlying problem.

03Debugging complex data flow issues in multi-layered microservices or distributed systems.