Diagnose and fix software bugs and performance regressions using structured debugging techniques.
npx skills add https://github.com/wzser/supermatrix --skill diagnose-wzser
Please help me install this Agent Skill. Skill: diagnose Source: https://github.com/wzser/supermatrix/tree/main/platform/skill-master/skills/diagnose Command: npx skills add https://github.com/wzser/supermatrix --skill diagnose-wzser
This Skill aids in efficiently diagnosing and resolving hard bugs and performance regressions, providing a structured approach to problem-solving in software development.
Use the /new command to create a session, then run the /status command to check the session status.
High-intent search queries and answers about installing and using this skill.
Systematically diagnose and fix hard bugs by following a structured debugging loop: reproduce, minimize, hypothesize, instrument, fix, and regression-test. This approach builds a fast, deterministic pass/fail signal to verify the issue is resolved.
To increase the reproduction rate of non-deterministic bugs, apply specialized strategies to build a deterministic feedback loop. This involves targeted instrumentation and adjusting the environment to reliably trigger the issue for diagnosis.
A structured debugging loop resolves performance regressions by enforcing a disciplined process of measuring performance, hypothesizing the cause, instrumenting the code, and verifying the fix. This ensures regressions are systematically isolated and resolved.
Yes, diagnosing issues requires access to debugging tools and the project environment, as well as knowledge of the project's domain and Architecture Decision Records (ADRs) to accurately reproduce and hypothesize the root cause.
A structured approach ensures a disciplined loop of reproduction and regression testing, whereas ad-hoc logging lacks a deterministic pass/fail signal. It guides you to build a fast feedback loop, instrument correctly, and verify fixes reliably.
Without a minimized reproduction case, bug diagnosis becomes inefficient and lacks a deterministic pass/fail signal. The structured debugging loop requires minimizing the issue to build a fast, agent-runnable feedback signal for accurate fixing.
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