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    Systematic Debugging: 4-Phase Root Cause Methodology

    by DesignBureau

    1

    Stop guessing at bugs. A 4-phase method that makes you find root cause before touching the code. Takes debugging from hours to minutes. Works in any language, with any AI agent.

    $7

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    About this skill

    You're 2 hours into a bug. Tried 4 fixes. Each one "almost worked" but broke something else. Still guessing. Most developers skip straight to trying things. Most AI agents do the same. No method means trial and error. Patch one thing, break two others. This skill fixes that. 4 phases. Your agent loads it and follows it like a playbook. No fixing until you've found root cause. Phase 1, find what's happening. Error messages. Reproduce it. Audit what changed. Gather evidence. Check logs. Trace the data. There are specific commands for each. Phase 2, compare broken code against working code. Find every difference. Know what depends on what before touching anything. Phase 3, one hypothesis. One minimal test. Verify before moving to the next thing. No bundle fixes. Phase 4, write a failing regression test first. Apply the fix. Verify. If it still fails after three attempts, the architecture is wrong. Stop patching. 584 lines. 6 reference files covering Python debugging, Node debugging, stale bytecode detection, and pipeline filter tracing. Plus remote troubleshooting, multi-component diagnostics, and a red flags list that catches every rationalisation agents use to skip steps. "Quick fix for now." "Issue is simple." "Just try changing X." Your agent reads these and catches itself. How to use it Drop the zip in your agent's skills directory. Reference it in config. When your agent hits a bug, tell it to follow the skill.

    How to install

    Drop the file into your AI Agent. Works with Claude, Cursor, ChatGPT, and 20+ more.

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    Permissions

    Terminal / Shell
    Read Files

    Read-only debugging methodology. No credentials, no network, no writes. All shell commands are standard developer tools.

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