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    Systematic Bug Debugger

    Systematic Bug Debugger

    by Arnstein Larsen

    Stop guessing and start solving with hypothesis-driven debugging for complex, intermittent, and production-only bugs.

    Updated Jun 2026
    0 installs

    Free

    Included in download

    • Downloadable skill package
    • Works with Claude Code, Cursor
    • Instant install

    Sample input

    The user profile page is intermittently throwing a 500 error in production, but I can't reproduce it locally. Here is the stack trace from the logs.

    Sample output

    Reproduction Hypothesis:

    1. Race condition in DB connection pool (High)
    2. Latency-induced timeout on Auth microservice (Medium)

    Next step: To isolate #2, can we wrap the Auth call in a 500ms delay locally to see if it triggers the same stack trace? Avoid changing the DB config until this is ruled out.

    About This Skill

    Structured Root Cause Analysis

    Ditch the "shotgun debugging" approach of trial-and-error changes. This skill implements a hypothesis-driven debugging framework designed to isolate and resolve complex software defects, from intermittent "Heisenbugs" to environment-specific failures.

    What it does

    The Systematic Bug Debugger guides you through a rigorous diagnostic process. Instead of jumping to a fix, it forces the identification of a minimal reproduction case, maps symptoms to specific architectural layers, and ranks potential causes based on evidence. It acts as a senior staff engineer looking over your shoulder to ensure no assumptions go untested.

    Supported Workflows

    • Reproduction First: Techniques to trigger bugs on demand with the smallest possible input.
    • Hypothesis Ranking: Eliminates "noise" by prioritizing the most likely root causes based on stack traces and logs.
    • Environment Drift: Diagnoses why code "works on my machine" but fails in production.
    • Instrumentation Tactics: Specific advice on where to inject logging or breakpoints to validate a theory.

    Why it's better than standard prompting

    Most AI agents will try to fix code immediately, often leading to "hallucinated fixes" that treat symptoms rather than causes. This skill enforces a systematic methodology—bisection, instrumentation, and regression test design—ensuring that when a fix is finally applied, you have proof it actually works.

    Use Cases

    • Identify root causes for intermittent Heisenbugs and race conditions
    • Design minimal failing test cases to prove a bug exists before fixing it
    • Diagnose environment drift between local development and production
    • Perform forensic stack trace analysis to prioritize technical hypotheses

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    Claude Code, Cursor, Aider, Cline, and Windsurf.

    Frequently Asked Questions

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